From 6704d8e98a6f310cb0dd5fc74a3f8b7937cda73b Mon Sep 17 00:00:00 2001
From: Yoshi Automation Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -220,6 +223,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -253,10 +259,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"status": { # `ServicePerimeterConfig` specifies a set of Google Cloud resources that describe specific Service Perimeter configuration. # Current ServicePerimeter configuration. Specifies sets of resources, restricted services and access levels that determine perimeter content and boundaries.
@@ -274,6 +297,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -313,6 +339,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -346,10 +375,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"title": "A String", # Human readable title. Must be unique within the Policy.
@@ -454,6 +500,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -493,6 +542,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -526,10 +578,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"status": { # `ServicePerimeterConfig` specifies a set of Google Cloud resources that describe specific Service Perimeter configuration. # Current ServicePerimeter configuration. Specifies sets of resources, restricted services and access levels that determine perimeter content and boundaries.
@@ -547,6 +616,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -586,6 +658,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -619,10 +694,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"title": "A String", # Human readable title. Must be unique within the Policy.
@@ -669,6 +761,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -708,6 +803,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -741,10 +839,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"status": { # `ServicePerimeterConfig` specifies a set of Google Cloud resources that describe specific Service Perimeter configuration. # Current ServicePerimeter configuration. Specifies sets of resources, restricted services and access levels that determine perimeter content and boundaries.
@@ -762,6 +877,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -801,6 +919,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -834,10 +955,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"title": "A String", # Human readable title. Must be unique within the Policy.
@@ -890,6 +1028,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -929,6 +1070,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -962,10 +1106,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"status": { # `ServicePerimeterConfig` specifies a set of Google Cloud resources that describe specific Service Perimeter configuration. # Current ServicePerimeter configuration. Specifies sets of resources, restricted services and access levels that determine perimeter content and boundaries.
@@ -983,6 +1144,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -1022,6 +1186,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -1055,10 +1222,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"title": "A String", # Human readable title. Must be unique within the Policy.
@@ -1127,6 +1311,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -1166,6 +1353,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -1199,10 +1389,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"status": { # `ServicePerimeterConfig` specifies a set of Google Cloud resources that describe specific Service Perimeter configuration. # Current ServicePerimeter configuration. Specifies sets of resources, restricted services and access levels that determine perimeter content and boundaries.
@@ -1220,6 +1427,9 @@ Method Details
"sources": [ # Sources that this EgressPolicy authorizes access from. If this field is not empty, then `source_restriction` must be set to `SOURCE_RESTRICTION_ENABLED`.
{ # The source that EgressPolicy authorizes access from inside the ServicePerimeter to somewhere outside the ServicePerimeter boundaries.
"accessLevel": "A String", # An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.
},
],
@@ -1259,6 +1469,9 @@ Method Details
"sources": [ # Sources that this IngressPolicy authorizes access from.
{ # The source that IngressPolicy authorizes access from.
"accessLevel": "A String", # An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.
+ "pscEndpoint": { # Specifies the Private Service Connect endpoint that an API call refers to. # A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in.
+ "forwardingRule": "A String", # The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.
+ },
"resource": "A String", # A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.
},
],
@@ -1292,10 +1505,27 @@ Method Details
"A String",
],
"vpcAccessibleServices": { # Specifies how APIs are allowed to communicate within the Service Perimeter. # Configuration for APIs allowed within Perimeter.
+ "allowedServicePatterns": [ # Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.
+ { # Service patterns used to allow access.
+ "modifiers": [ # Modifiers to apply to the requests that match the URL pattern.
+ { # Modifier to apply to the API requests.
+ "addRequestHeader": { # Adds a request header to the API. # Adds additional HTTP request headers.
+ "key": "A String", # HTTP header key.
+ "value": "A String", # HTTP header value.
+ },
+ },
+ ],
+ "pattern": "A String", # URL pattern to allow. Only patterns of ".googleapis.com/*", "www.googleapis.com//*" and "*.appspot.com/* forms are supported, where should be alphanumerical name.
+ "service": "A String", # Supported service to allow.
+ },
+ ],
"allowedServices": [ # The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.
"A String",
],
"enableRestriction": True or False, # Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.
+ "servicePatternsEnforcementScopes": [ # Defines the enforcement scopes of service patterns.
+ "A String",
+ ],
},
},
"title": "A String", # Human readable title. Must be unique within the Policy.
diff --git a/googleapiclient/discovery_cache/documents/accesscontextmanager.v1.json b/googleapiclient/discovery_cache/documents/accesscontextmanager.v1.json
index b7b4c693a3..96488cc53e 100644
--- a/googleapiclient/discovery_cache/documents/accesscontextmanager.v1.json
+++ b/googleapiclient/discovery_cache/documents/accesscontextmanager.v1.json
@@ -1331,7 +1331,7 @@
}
}
},
-"revision": "20260506",
+"revision": "20260707",
"rootUrl": "https://accesscontextmanager.googleapis.com/",
"schemas": {
"AccessContextManagerOperationMetadata": {
@@ -1427,6 +1427,21 @@
},
"type": "object"
},
+"AddRequestHeader": {
+"description": "Adds a request header to the API.",
+"id": "AddRequestHeader",
+"properties": {
+"key": {
+"description": "HTTP header key.",
+"type": "string"
+},
+"value": {
+"description": "HTTP header value.",
+"type": "string"
+}
+},
+"type": "object"
+},
"ApiOperation": {
"description": "Identification for an API Operation.",
"id": "ApiOperation",
@@ -1859,6 +1874,10 @@
"description": "An AccessLevel resource name that allows protected resources inside the ServicePerimeters to access outside the ServicePerimeter boundaries. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If an AccessLevel name is not specified, only resources within the perimeter can be accessed through Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all EgressSources will be allowed.",
"type": "string"
},
+"pscEndpoint": {
+"$ref": "PrivateServiceConnectEndpoint",
+"description": "A PrivateServiceConnectEndpoint that is allowed to access data outside the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in."
+},
"resource": {
"description": "A Google Cloud resource from the service perimeter that you want to allow to access data outside the perimeter. This field supports only projects. The project format is `projects/{project_number}`. You can't use `*` in this field to allow all Google Cloud resources.",
"type": "string"
@@ -2070,6 +2089,10 @@
"description": "An AccessLevel resource name that allow resources within the ServicePerimeters to be accessed from the internet. AccessLevels listed must be in the same policy as this ServicePerimeter. Referencing a nonexistent AccessLevel will cause an error. If no AccessLevel names are listed, resources within the perimeter can only be accessed via Google Cloud calls with request origins within the perimeter. Example: `accessPolicies/MY_POLICY/accessLevels/MY_LEVEL`. If a single `*` is specified for `access_level`, then all IngressSources will be allowed.",
"type": "string"
},
+"pscEndpoint": {
+"$ref": "PrivateServiceConnectEndpoint",
+"description": "A PrivateServiceConnectEndpoint that is allowed to access the perimeter. The Private Service Connect endpoint may be in any organization, not just the organization that the perimeter is defined in."
+},
"resource": {
"description": "A Google Cloud resource that is allowed to ingress the perimeter. Requests from these resources will be allowed to access perimeter data. Currently only projects and VPCs are allowed. Project format: `projects/{project_number}` VPC network format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/networks/{NAME}`. The project may be in any Google Cloud organization, not just the organization that the perimeter is defined in. `*` is not allowed, the case of allowing all Google Cloud resources only is not supported.",
"type": "string"
@@ -2271,6 +2294,17 @@
},
"type": "object"
},
+"Modifier": {
+"description": "Modifier to apply to the API requests.",
+"id": "Modifier",
+"properties": {
+"addRequestHeader": {
+"$ref": "AddRequestHeader",
+"description": "Adds additional HTTP request headers."
+}
+},
+"type": "object"
+},
"Operation": {
"description": "This resource represents a long-running operation that is the result of a network API call.",
"id": "Operation",
@@ -2374,6 +2408,17 @@
},
"type": "object"
},
+"PrivateServiceConnectEndpoint": {
+"description": "Specifies the Private Service Connect endpoint that an API call refers to.",
+"id": "PrivateServiceConnectEndpoint",
+"properties": {
+"forwardingRule": {
+"description": "The full resource name of the global forwarding rule that identifies a Private Service Connect endpoint. Forwarding rule format: `//compute.googleapis.com/projects/{PROJECT_ID}/global/forwardingRules/{FORWARDING_RULE_ID}`.",
+"type": "string"
+}
+},
+"type": "object"
+},
"ReplaceAccessLevelsRequest": {
"description": "A request to replace all existing Access Levels in an Access Policy with the Access Levels provided. This is done atomically.",
"id": "ReplaceAccessLevelsRequest",
@@ -2457,6 +2502,28 @@
},
"type": "object"
},
+"ServicePattern": {
+"description": "Service patterns used to allow access.",
+"id": "ServicePattern",
+"properties": {
+"modifiers": {
+"description": "Modifiers to apply to the requests that match the URL pattern.",
+"items": {
+"$ref": "Modifier"
+},
+"type": "array"
+},
+"pattern": {
+"description": "URL pattern to allow. Only patterns of \".googleapis.com/*\", \"www.googleapis.com//*\" and \"*.appspot.com/* forms are supported, where should be alphanumerical name.",
+"type": "string"
+},
+"service": {
+"description": "Supported service to allow.",
+"type": "string"
+}
+},
+"type": "object"
+},
"ServicePerimeter": {
"description": "`ServicePerimeter` describes a set of Google Cloud resources which can freely import and export data amongst themselves, but not export outside of the `ServicePerimeter`. If a request with a source within this `ServicePerimeter` has a target outside of the `ServicePerimeter`, the request will be blocked. Otherwise the request is allowed. There are two types of Service Perimeter - Regular and Bridge. Regular Service Perimeters cannot overlap, a single Google Cloud project or VPC network can only belong to a single regular Service Perimeter. Service Perimeter Bridges can contain only Google Cloud projects as members, a single Google Cloud project may belong to multiple Service Perimeter Bridges.",
"id": "ServicePerimeter",
@@ -2736,6 +2803,13 @@
"description": "Specifies how APIs are allowed to communicate within the Service Perimeter.",
"id": "VpcAccessibleServices",
"properties": {
+"allowedServicePatterns": {
+"description": "Specifies which Google services are allowed to be accessed from VPC networks in the service perimeter.",
+"items": {
+"$ref": "ServicePattern"
+},
+"type": "array"
+},
"allowedServices": {
"description": "The list of APIs usable within the Service Perimeter. Must be empty unless 'enable_restriction' is True. You can specify a list of individual services, as well as include the 'RESTRICTED-SERVICES' value, which automatically includes all of the services protected by the perimeter.",
"items": {
@@ -2746,6 +2820,21 @@
"enableRestriction": {
"description": "Whether to restrict API calls within the Service Perimeter to the list of APIs specified in 'allowed_services'.",
"type": "boolean"
+},
+"servicePatternsEnforcementScopes": {
+"description": "Defines the enforcement scopes of service patterns.",
+"items": {
+"enum": [
+"SERVICE_PATTERNS_ENFORCEMENT_SCOPE_UNSPECIFIED",
+"GOOGLE_APIS_VIA_PRIVATE_PATH"
+],
+"enumDescriptions": [
+"Default value. This can not be used.",
+"Enables VPC Accessible Services enforcement for all APIs (including unsupported APIs) for Private Google Access configured with Private VIP and Private Service Connect Endpoint for Global Google APIs that uses 'all-apis' bundle."
+],
+"type": "string"
+},
+"type": "array"
}
},
"type": "object"
From 11ebd1d4065691d097b7ed6a626c3056061efea0 Mon Sep 17 00:00:00 2001
From: Yoshi Automation Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1287,7 +1288,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -2220,7 +2222,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
diff --git a/docs/dyn/aiplatform_v1.html b/docs/dyn/aiplatform_v1.html
index a4068f89e1..aff6463c36 100644
--- a/docs/dyn/aiplatform_v1.html
+++ b/docs/dyn/aiplatform_v1.html
@@ -139,6 +139,11 @@ Instance Methods
Returns the media Resource.
+
+ memoryBanks()
+
Returns the memoryBanks Resource.
+ diff --git a/docs/dyn/aiplatform_v1.memoryBanks.html b/docs/dyn/aiplatform_v1.memoryBanks.html new file mode 100644 index 0000000000..64aefa6fca --- /dev/null +++ b/docs/dyn/aiplatform_v1.memoryBanks.html @@ -0,0 +1,96 @@ + + + +
+ memories()
+
Returns the memories Resource.
+ +
+ operations()
+
Returns the operations Resource.
+ +
+ close()
Close httplib2 connections.
+close()
+ Close httplib2 connections.+
+ operations()
+
Returns the operations Resource.
+ +
+ close()
Close httplib2 connections.
+close()
+ Close httplib2 connections.+
Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+ close()
Close httplib2 connections.
+ +Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+ +Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+ +Retrieves the next page of results.
+
+ wait(name, timeout=None, x__xgafv=None)
Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+cancel(name, x__xgafv=None)
+ Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+Args:
+ name: string, The name of the operation resource to be cancelled. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+close()
+ Close httplib2 connections.+
delete(name, x__xgafv=None)
+ Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation resource to be deleted. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+get(name, x__xgafv=None)
+ Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+Args:
+ name: string, The name of the operation resource. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+ Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation's parent resource. (required)
+ filter: string, The standard list filter.
+ pageSize: integer, The standard list page size.
+ pageToken: string, The standard list page token.
+ returnPartialSuccess: boolean, When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `"projects/example/locations/-"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # The response message for Operations.ListOperations.
+ "nextPageToken": "A String", # The standard List next-page token.
+ "operations": [ # A list of operations that matches the specified filter in the request.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ },
+ ],
+ "unreachable": [ # Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.
+ "A String",
+ ],
+}
+list_next()
+ Retrieves the next page of results. + + Args: + previous_request: The request for the previous page. (required) + previous_response: The response from the request for the previous page. (required) + + Returns: + A request object that you can call 'execute()' on to request the next + page. Returns None if there are no more items in the collection. ++
wait(name, timeout=None, x__xgafv=None)
+ Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+
+Args:
+ name: string, The name of the operation resource to wait on. (required)
+ timeout: string, The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+ close()
Close httplib2 connections.
+ +Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+ +Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+ +Retrieves the next page of results.
+
+ wait(name, timeout=None, x__xgafv=None)
Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+cancel(name, x__xgafv=None)
+ Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+Args:
+ name: string, The name of the operation resource to be cancelled. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+close()
+ Close httplib2 connections.+
delete(name, x__xgafv=None)
+ Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation resource to be deleted. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+get(name, x__xgafv=None)
+ Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+Args:
+ name: string, The name of the operation resource. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+ Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation's parent resource. (required)
+ filter: string, The standard list filter.
+ pageSize: integer, The standard list page size.
+ pageToken: string, The standard list page token.
+ returnPartialSuccess: boolean, When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `"projects/example/locations/-"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # The response message for Operations.ListOperations.
+ "nextPageToken": "A String", # The standard List next-page token.
+ "operations": [ # A list of operations that matches the specified filter in the request.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ },
+ ],
+ "unreachable": [ # Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.
+ "A String",
+ ],
+}
+list_next()
+ Retrieves the next page of results. + + Args: + previous_request: The request for the previous page. (required) + previous_response: The response from the request for the previous page. (required) + + Returns: + A request object that you can call 'execute()' on to request the next + page. Returns None if there are no more items in the collection. ++
wait(name, timeout=None, x__xgafv=None)
+ Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+
+Args:
+ name: string, The name of the operation resource to wait on. (required)
+ timeout: string, The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+delete(name, x__xgafv=None)
+ Deletes an Evaluation Item.
+
+Args:
+ name: string, Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+get(name, x__xgafv=None)
+ Gets an Evaluation Item.
+
+Args:
+ name: string, Required. The name of the EvaluationItem resource. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.
+ "createTime": "A String", # Output only. Timestamp when this item was created.
+ "displayName": "A String", # Required. The display name of the EvaluationItem.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error for the evaluation item.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "evaluationItemType": "A String", # Required. The type of the EvaluationItem.
+ "evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
+ "candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
+ { # Responses from model or agent.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
},
},
],
- "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
- },
- },
- },
- "text": "A String", # Text prompt.
- "value": "", # Fields and values that can be used to populate the prompt template.
- },
- "rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
- "a_key": { # A group of rubrics, used for grouping rubrics based on a metric or a version.
- "displayName": "A String", # Human-readable name for the group. This should be unique within a given context if used for display or selection. Example: "Instruction Following V1", "Content Quality - Summarization Task".
- "groupId": "A String", # Unique identifier for the group.
- "rubrics": [ # Rubrics that are part of this group.
- { # Message representing a single testable criterion for evaluation. One input prompt could have multiple rubrics.
- "content": { # Content of the rubric, defining the testable criteria. # Required. The actual testable criteria for the rubric.
- "property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
- "description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
- },
- },
- "importance": "A String", # Optional. The relative importance of this rubric.
- "rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
- "type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
},
],
},
- },
- },
- },
- "gcsUri": "A String", # The Cloud Storage object where the request or response is stored.
- "labels": { # Optional. Labels for the EvaluationItem.
- "a_key": "A String",
- },
- "metadata": "", # Optional. Metadata for the EvaluationItem.
- "name": "A String", # Identifier. The resource name of the EvaluationItem. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}`
-}
-delete(name, x__xgafv=None)
- Deletes an Evaluation Item.
-
-Args:
- name: string, Required. The name of the EvaluationItem resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (required)
- x__xgafv: string, V1 error format.
- Allowed values
- 1 - v1 error format
- 2 - v2 error format
-
-Returns:
- An object of the form:
-
- { # This resource represents a long-running operation that is the result of a network API call.
- "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
- "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
- "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
- {
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- ],
- "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
- },
- "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
- "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
-}
-get(name, x__xgafv=None)
- Gets an Evaluation Item.
-
-Args:
- name: string, Required. The name of the EvaluationItem resource. Format: `projects/{project}/locations/{location}/evaluationItems/{evaluation_item}` (required)
- x__xgafv: string, V1 error format.
- Allowed values
- 1 - v1 error format
- 2 - v2 error format
-
-Returns:
- An object of the form:
-
- { # EvaluationItem is a single evaluation request or result. The content of an EvaluationItem is immutable - it cannot be updated once created. EvaluationItems can be deleted when no longer needed.
- "createTime": "A String", # Output only. Timestamp when this item was created.
- "displayName": "A String", # Required. The display name of the EvaluationItem.
- "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error for the evaluation item.
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
- "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
- {
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- ],
- "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
- },
- "evaluationItemType": "A String", # Required. The type of the EvaluationItem.
- "evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
- "candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
- { # Responses from model or agent.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -826,8 +8062,562 @@ Method Details
"text": "A String", # Text response.
"value": "", # Fields and values that can be used to populate the response template.
},
- ],
- "goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ ],
+ "goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -842,6 +8632,560 @@ Method Details
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
@@ -921,6 +9265,10 @@ Method Details
},
},
"text": "A String", # Text prompt.
+ "userScenario": { # User scenario to help simulate multi-turn agent running results. # Optional. The generated user scenario used to drive multi-turn agent running results.
+ "conversationPlan": "A String", # Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.
+ "startingPrompt": "A String", # Required. The prompt that starts the conversation between the simulated user and the agent under test.
+ },
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
@@ -947,6 +9295,15 @@ Method Details
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while evaluating the candidate for the metric.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
@@ -956,40 +9313,1148 @@ Method Details
"property": { # Defines criteria based on a specific property. # Evaluation criteria based on a specific property.
"description": "A String", # Description of the property being evaluated. Example: "The model's response is grammatically correct."
},
- },
- "importance": "A String", # Optional. The relative importance of this rubric.
- "rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
- "type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
+ },
+ "importance": "A String", # Optional. The relative importance of this rubric.
+ "rubricId": "A String", # Unique identifier for the rubric. This ID is used to refer to this rubric, e.g., in RubricVerdict.
+ "type": "A String", # Optional. A type designator for the rubric, which can inform how it's evaluated or interpreted by systems or users. It's recommended to use consistent, well-defined, upper snake_case strings. Examples: "SUMMARIZATION_QUALITY", "SAFETY_HARMFUL_CONTENT", "INSTRUCTION_ADHERENCE".
+ },
+ "reasoning": "A String", # Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.
+ "verdict": True or False, # Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail".
+ },
+ ],
+ "score": 3.14, # Optional. The score for the metric.
+ },
+ ],
+ "evaluationRequest": "A String", # Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}
+ "evaluationRun": "A String", # Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}
+ "metadata": "", # Optional. Metadata about the evaluation result.
+ "metric": "A String", # Required. The metric that was evaluated.
+ "request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
+ "candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
+ { # Responses from model or agent.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
+ "candidate": "A String", # Required. The name of the candidate that produced the response.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "text": "A String", # Text response.
+ "value": "", # Fields and values that can be used to populate the response template.
+ },
+ ],
+ "goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
},
- "reasoning": "A String", # Optional. Human-readable reasoning or explanation for the verdict. This can include specific examples or details from the evaluated content that justify the given verdict.
- "verdict": True or False, # Required. Outcome of the evaluation against the rubric, represented as a boolean. `true` indicates a "Pass", `false` indicates a "Fail".
- },
- ],
- "score": 3.14, # Optional. The score for the metric.
- },
- ],
- "evaluationRequest": "A String", # Required. The request item that was evaluated. Format: projects/{project}/locations/{location}/evaluationItems/{evaluation_item}
- "evaluationRun": "A String", # Required. The evaluation run that was used to generate the result. Format: projects/{project}/locations/{location}/evaluationRuns/{evaluation_run}
- "metadata": "", # Optional. Metadata about the evaluation result.
- "metric": "A String", # Required. The metric that was evaluated.
- "request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
- "candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
- { # Responses from model or agent.
- "candidate": "A String", # Required. The name of the candidate that produced the response.
- "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
- "code": 42, # The status code, which should be an enum value of google.rpc.Code.
- "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
- {
- "a_key": "", # Properties of the object. Contains field @type with type URL.
- },
- ],
- "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
- },
- "text": "A String", # Text response.
- "value": "", # Fields and values that can be used to populate the response template.
+ ],
},
- ],
- "goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -1004,6 +10469,560 @@ Method Details
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
@@ -1083,6 +11102,10 @@ Method Details
},
},
"text": "A String", # Text prompt.
+ "userScenario": { # User scenario to help simulate multi-turn agent running results. # Optional. The generated user scenario used to drive multi-turn agent running results.
+ "conversationPlan": "A String", # Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.
+ "startingPrompt": "A String", # Required. The prompt that starts the conversation between the simulated user and the agent under test.
+ },
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
@@ -1150,6 +11173,560 @@ Method Details
"evaluationRequest": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # The request to evaluate.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -1165,6 +11742,560 @@ Method Details
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -1173,12 +12304,566 @@ Method Details
"a_key": "", # Properties of the object. Contains field @type with type URL.
},
],
- "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "text": "A String", # Text response.
+ "value": "", # Fields and values that can be used to populate the response template.
+ },
+ "prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
},
- "text": "A String", # Text response.
- "value": "", # Fields and values that can be used to populate the response template.
- },
- "prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
@@ -1258,6 +12943,10 @@ Method Details
},
},
"text": "A String", # Text prompt.
+ "userScenario": { # User scenario to help simulate multi-turn agent running results. # Optional. The generated user scenario used to drive multi-turn agent running results.
+ "conversationPlan": "A String", # Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.
+ "startingPrompt": "A String", # Required. The prompt that starts the conversation between the simulated user and the agent under test.
+ },
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
@@ -1284,6 +12973,15 @@ Method Details
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while evaluating the candidate for the metric.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
@@ -1312,6 +13010,560 @@ Method Details
"request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -1327,6 +13579,560 @@ Method Details
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -1341,6 +14147,560 @@ Method Details
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
@@ -1420,6 +14780,10 @@ Method Details
},
},
"text": "A String", # Text prompt.
+ "userScenario": { # User scenario to help simulate multi-turn agent running results. # Optional. The generated user scenario used to drive multi-turn agent running results.
+ "conversationPlan": "A String", # Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.
+ "startingPrompt": "A String", # Required. The prompt that starts the conversation between the simulated user and the agent under test.
+ },
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
diff --git a/docs/dyn/aiplatform_v1.projects.locations.evaluationMetrics.html b/docs/dyn/aiplatform_v1.projects.locations.evaluationMetrics.html
new file mode 100644
index 0000000000..b853265a44
--- /dev/null
+++ b/docs/dyn/aiplatform_v1.projects.locations.evaluationMetrics.html
@@ -0,0 +1,1744 @@
+
+
+
+Agent Platform API . projects . locations . evaluationMetrics
+Instance Methods
+
+ close()
+Close httplib2 connections.
+
+ create(parent, body=None, evaluationMetricId=None, x__xgafv=None)
+Creates an EvaluationMetric.
+
+Deletes an EvaluationMetric.
+
+Gets an EvaluationMetric.
+
+ list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)
+Lists EvaluationMetrics.
+
+Retrieves the next page of results.
+Method Details
+
+ close()
+ Close httplib2 connections.
+
+
+
+ create(parent, body=None, evaluationMetricId=None, x__xgafv=None)
+ Creates an EvaluationMetric.
+
+Args:
+ parent: string, Required. The resource name of the Location to create the EvaluationMetric in. Format: `projects/{project}/locations/{location}` (required)
+ body: object, The request body.
+ The object takes the form of:
+
+{ # EvaluationMetric is a resource that represents a reusable metric configuration.
+ "createTime": "A String", # Output only. The time when the EvaluationMetric was created.
+ "description": "A String", # Optional. A description of the EvaluationMetric.
+ "displayName": "A String", # Required. The user-friendly display name for the EvaluationMetric.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI that stores the metric specification..
+ "labels": { # Optional. Labels for the evaluation metric.
+ "a_key": "A String",
+ },
+ "metric": { # The metric used for running evaluations. # Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.
+ "aggregationMetrics": [ # Optional. The aggregation metrics to use.
+ "A String",
+ ],
+ "bleuSpec": { # Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1. # Spec for bleu metric.
+ "useEffectiveOrder": True or False, # Optional. Whether to use_effective_order to compute bleu score.
+ },
+ "computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
+ "parameters": { # Optional. A map of parameters for the metric, e.g. {"rouge_type": "rougeL"}.
+ "a_key": "", # Properties of the object.
+ },
+ "type": "A String", # Required. The type of the computation based metric.
+ },
+ "customCodeExecutionSpec": { # Specificies a metric that is populated by evaluating user-defined Python code. # Spec for Custom Code Execution metric.
+ "evaluationFunction": "A String", # Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -> float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text="The answer is 4."), reference=EvaluationInstance.InstanceData(text="4") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -> float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function.
+ },
+ "exactMatchSpec": { # Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0. # Spec for exact match metric.
+ },
+ "llmBasedMetricSpec": { # Specification for an LLM based metric. # Spec for an LLM based metric.
+ "additionalConfig": { # Optional. Optional additional configuration for the metric.
+ "a_key": "", # Properties of the object.
+ },
+ "judgeAutoraterConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Optional. Optional configuration for the judge LLM (Autorater).
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "metricPromptTemplate": "A String", # Required. Template for the prompt sent to the judge model.
+ "predefinedRubricGenerationSpec": { # The spec for a pre-defined metric. # Dynamically generate rubrics using a predefined spec.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "resultParserConfig": { # Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters. # Optional. The parser config for the metric result.
+ "customCodeParserConfig": { # Configuration for parsing the LLM response using custom code. # Optional. Use custom code to parse the LLM response.
+ "parsingFunction": "A String", # Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation
+ },
+ },
+ "rubricGenerationSpec": { # Specification for how rubrics should be generated. # Dynamically generate rubrics using this specification.
+ "modelConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation.
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "promptTemplate": "A String", # Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.
+ "rubricContentType": "A String", # The type of rubric content to be generated.
+ "rubricTypeOntology": [ # Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology.
+ "A String",
+ ],
+ },
+ "rubricGroupKey": "A String", # Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.
+ "systemInstruction": "A String", # Optional. System instructions for the judge model.
+ },
+ "metadata": { # Metadata about the metric, used for visualization and organization. # Optional. Metadata about the metric, used for visualization and organization.
+ "otherMetadata": { # Optional. Flexible metadata for user-defined attributes.
+ "a_key": "", # Properties of the object.
+ },
+ "scoreRange": { # The range of possible scores for this metric, used for plotting. # Optional. The range of possible scores for this metric, used for plotting.
+ "description": "A String", # Optional. The description of the score explaining the directionality etc.
+ "max": 3.14, # Required. The maximum value of the score range (inclusive).
+ "min": 3.14, # Required. The minimum value of the score range (inclusive).
+ "step": 3.14, # Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous.
+ },
+ "title": "A String", # Optional. The user-friendly name for the metric. If not set for a registered metric, it will default to the metric's display name.
+ },
+ "pairwiseMetricSpec": { # Spec for pairwise metric. # Spec for pairwise metric.
+ "baselineResponseFieldName": "A String", # Optional. The field name of the baseline response.
+ "candidateResponseFieldName": "A String", # Optional. The field name of the candidate response.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pairwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pairwise metric.
+ },
+ "pointwiseMetricSpec": { # Spec for pointwise metric. # Spec for pointwise metric.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pointwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pointwise metric.
+ },
+ "predefinedMetricSpec": { # The spec for a pre-defined metric. # The spec for a pre-defined metric.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "rougeSpec": { # Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1. # Spec for rouge metric.
+ "rougeType": "A String", # Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
+ "splitSummaries": True or False, # Optional. Whether to split summaries while using rougeLsum.
+ "useStemmer": True or False, # Optional. Whether to use stemmer to compute rouge score.
+ },
+ },
+ "name": "A String", # Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`
+ "updateTime": "A String", # Output only. The time when the EvaluationMetric was last updated.
+}
+
+ evaluationMetricId: string, Optional. The ID to use for the EvaluationMetric, which will become the final component of the EvaluationMetric's resource name. This value should be 1-63 characters, and valid characters are /a-z-/. The first character must be a lowercase letter, and the last character must be a lowercase letter or number.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # EvaluationMetric is a resource that represents a reusable metric configuration.
+ "createTime": "A String", # Output only. The time when the EvaluationMetric was created.
+ "description": "A String", # Optional. A description of the EvaluationMetric.
+ "displayName": "A String", # Required. The user-friendly display name for the EvaluationMetric.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI that stores the metric specification..
+ "labels": { # Optional. Labels for the evaluation metric.
+ "a_key": "A String",
+ },
+ "metric": { # The metric used for running evaluations. # Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.
+ "aggregationMetrics": [ # Optional. The aggregation metrics to use.
+ "A String",
+ ],
+ "bleuSpec": { # Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1. # Spec for bleu metric.
+ "useEffectiveOrder": True or False, # Optional. Whether to use_effective_order to compute bleu score.
+ },
+ "computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
+ "parameters": { # Optional. A map of parameters for the metric, e.g. {"rouge_type": "rougeL"}.
+ "a_key": "", # Properties of the object.
+ },
+ "type": "A String", # Required. The type of the computation based metric.
+ },
+ "customCodeExecutionSpec": { # Specificies a metric that is populated by evaluating user-defined Python code. # Spec for Custom Code Execution metric.
+ "evaluationFunction": "A String", # Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -> float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text="The answer is 4."), reference=EvaluationInstance.InstanceData(text="4") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -> float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function.
+ },
+ "exactMatchSpec": { # Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0. # Spec for exact match metric.
+ },
+ "llmBasedMetricSpec": { # Specification for an LLM based metric. # Spec for an LLM based metric.
+ "additionalConfig": { # Optional. Optional additional configuration for the metric.
+ "a_key": "", # Properties of the object.
+ },
+ "judgeAutoraterConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Optional. Optional configuration for the judge LLM (Autorater).
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "metricPromptTemplate": "A String", # Required. Template for the prompt sent to the judge model.
+ "predefinedRubricGenerationSpec": { # The spec for a pre-defined metric. # Dynamically generate rubrics using a predefined spec.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "resultParserConfig": { # Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters. # Optional. The parser config for the metric result.
+ "customCodeParserConfig": { # Configuration for parsing the LLM response using custom code. # Optional. Use custom code to parse the LLM response.
+ "parsingFunction": "A String", # Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation
+ },
+ },
+ "rubricGenerationSpec": { # Specification for how rubrics should be generated. # Dynamically generate rubrics using this specification.
+ "modelConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation.
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "promptTemplate": "A String", # Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.
+ "rubricContentType": "A String", # The type of rubric content to be generated.
+ "rubricTypeOntology": [ # Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology.
+ "A String",
+ ],
+ },
+ "rubricGroupKey": "A String", # Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.
+ "systemInstruction": "A String", # Optional. System instructions for the judge model.
+ },
+ "metadata": { # Metadata about the metric, used for visualization and organization. # Optional. Metadata about the metric, used for visualization and organization.
+ "otherMetadata": { # Optional. Flexible metadata for user-defined attributes.
+ "a_key": "", # Properties of the object.
+ },
+ "scoreRange": { # The range of possible scores for this metric, used for plotting. # Optional. The range of possible scores for this metric, used for plotting.
+ "description": "A String", # Optional. The description of the score explaining the directionality etc.
+ "max": 3.14, # Required. The maximum value of the score range (inclusive).
+ "min": 3.14, # Required. The minimum value of the score range (inclusive).
+ "step": 3.14, # Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous.
+ },
+ "title": "A String", # Optional. The user-friendly name for the metric. If not set for a registered metric, it will default to the metric's display name.
+ },
+ "pairwiseMetricSpec": { # Spec for pairwise metric. # Spec for pairwise metric.
+ "baselineResponseFieldName": "A String", # Optional. The field name of the baseline response.
+ "candidateResponseFieldName": "A String", # Optional. The field name of the candidate response.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pairwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pairwise metric.
+ },
+ "pointwiseMetricSpec": { # Spec for pointwise metric. # Spec for pointwise metric.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pointwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pointwise metric.
+ },
+ "predefinedMetricSpec": { # The spec for a pre-defined metric. # The spec for a pre-defined metric.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "rougeSpec": { # Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1. # Spec for rouge metric.
+ "rougeType": "A String", # Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
+ "splitSummaries": True or False, # Optional. Whether to split summaries while using rougeLsum.
+ "useStemmer": True or False, # Optional. Whether to use stemmer to compute rouge score.
+ },
+ },
+ "name": "A String", # Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`
+ "updateTime": "A String", # Output only. The time when the EvaluationMetric was last updated.
+}
+
+
+
+ delete(name, x__xgafv=None)
+ Deletes an EvaluationMetric.
+
+Args:
+ name: string, Required. The name of the EvaluationMetric resource to be deleted. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+
+
+ get(name, x__xgafv=None)
+ Gets an EvaluationMetric.
+
+Args:
+ name: string, Required. The name of the EvaluationMetric resource. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # EvaluationMetric is a resource that represents a reusable metric configuration.
+ "createTime": "A String", # Output only. The time when the EvaluationMetric was created.
+ "description": "A String", # Optional. A description of the EvaluationMetric.
+ "displayName": "A String", # Required. The user-friendly display name for the EvaluationMetric.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI that stores the metric specification..
+ "labels": { # Optional. Labels for the evaluation metric.
+ "a_key": "A String",
+ },
+ "metric": { # The metric used for running evaluations. # Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.
+ "aggregationMetrics": [ # Optional. The aggregation metrics to use.
+ "A String",
+ ],
+ "bleuSpec": { # Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1. # Spec for bleu metric.
+ "useEffectiveOrder": True or False, # Optional. Whether to use_effective_order to compute bleu score.
+ },
+ "computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
+ "parameters": { # Optional. A map of parameters for the metric, e.g. {"rouge_type": "rougeL"}.
+ "a_key": "", # Properties of the object.
+ },
+ "type": "A String", # Required. The type of the computation based metric.
+ },
+ "customCodeExecutionSpec": { # Specificies a metric that is populated by evaluating user-defined Python code. # Spec for Custom Code Execution metric.
+ "evaluationFunction": "A String", # Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -> float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text="The answer is 4."), reference=EvaluationInstance.InstanceData(text="4") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -> float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function.
+ },
+ "exactMatchSpec": { # Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0. # Spec for exact match metric.
+ },
+ "llmBasedMetricSpec": { # Specification for an LLM based metric. # Spec for an LLM based metric.
+ "additionalConfig": { # Optional. Optional additional configuration for the metric.
+ "a_key": "", # Properties of the object.
+ },
+ "judgeAutoraterConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Optional. Optional configuration for the judge LLM (Autorater).
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "metricPromptTemplate": "A String", # Required. Template for the prompt sent to the judge model.
+ "predefinedRubricGenerationSpec": { # The spec for a pre-defined metric. # Dynamically generate rubrics using a predefined spec.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "resultParserConfig": { # Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters. # Optional. The parser config for the metric result.
+ "customCodeParserConfig": { # Configuration for parsing the LLM response using custom code. # Optional. Use custom code to parse the LLM response.
+ "parsingFunction": "A String", # Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation
+ },
+ },
+ "rubricGenerationSpec": { # Specification for how rubrics should be generated. # Dynamically generate rubrics using this specification.
+ "modelConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation.
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "promptTemplate": "A String", # Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.
+ "rubricContentType": "A String", # The type of rubric content to be generated.
+ "rubricTypeOntology": [ # Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology.
+ "A String",
+ ],
+ },
+ "rubricGroupKey": "A String", # Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.
+ "systemInstruction": "A String", # Optional. System instructions for the judge model.
+ },
+ "metadata": { # Metadata about the metric, used for visualization and organization. # Optional. Metadata about the metric, used for visualization and organization.
+ "otherMetadata": { # Optional. Flexible metadata for user-defined attributes.
+ "a_key": "", # Properties of the object.
+ },
+ "scoreRange": { # The range of possible scores for this metric, used for plotting. # Optional. The range of possible scores for this metric, used for plotting.
+ "description": "A String", # Optional. The description of the score explaining the directionality etc.
+ "max": 3.14, # Required. The maximum value of the score range (inclusive).
+ "min": 3.14, # Required. The minimum value of the score range (inclusive).
+ "step": 3.14, # Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous.
+ },
+ "title": "A String", # Optional. The user-friendly name for the metric. If not set for a registered metric, it will default to the metric's display name.
+ },
+ "pairwiseMetricSpec": { # Spec for pairwise metric. # Spec for pairwise metric.
+ "baselineResponseFieldName": "A String", # Optional. The field name of the baseline response.
+ "candidateResponseFieldName": "A String", # Optional. The field name of the candidate response.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pairwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pairwise metric.
+ },
+ "pointwiseMetricSpec": { # Spec for pointwise metric. # Spec for pointwise metric.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pointwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pointwise metric.
+ },
+ "predefinedMetricSpec": { # The spec for a pre-defined metric. # The spec for a pre-defined metric.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "rougeSpec": { # Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1. # Spec for rouge metric.
+ "rougeType": "A String", # Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
+ "splitSummaries": True or False, # Optional. Whether to split summaries while using rougeLsum.
+ "useStemmer": True or False, # Optional. Whether to use stemmer to compute rouge score.
+ },
+ },
+ "name": "A String", # Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`
+ "updateTime": "A String", # Output only. The time when the EvaluationMetric was last updated.
+}
+
+
+
+ list(parent, filter=None, orderBy=None, pageSize=None, pageToken=None, x__xgafv=None)
+ Lists EvaluationMetrics.
+
+Args:
+ parent: string, Required. The resource name of the Location from which to list the EvaluationMetrics. Format: `projects/{project}/locations/{location}` (required)
+ filter: string, Optional. Filter expression that matches a subset of the EvaluationMetrics to show. For field names both snake_case and camelCase are supported. For more information about filter syntax, see [AIP-160](https://google.aip.dev/160).
+ orderBy: string, Optional. A comma-separated list of fields to order by, sorted in ascending order by default. Use `desc` after a field name for descending.
+ pageSize: integer, Optional. The maximum number of EvaluationMetrics to return.
+ pageToken: string, Optional. A page token, received from a previous `ListEvaluationMetrics` call. Provide this to retrieve the subsequent page.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # Response message for EvaluationMetricService.ListEvaluationMetrics.
+ "evaluationMetrics": [ # List of EvaluationMetrics in the requested page.
+ { # EvaluationMetric is a resource that represents a reusable metric configuration.
+ "createTime": "A String", # Output only. The time when the EvaluationMetric was created.
+ "description": "A String", # Optional. A description of the EvaluationMetric.
+ "displayName": "A String", # Required. The user-friendly display name for the EvaluationMetric.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI that stores the metric specification..
+ "labels": { # Optional. Labels for the evaluation metric.
+ "a_key": "A String",
+ },
+ "metric": { # The metric used for running evaluations. # Optional. The metric configuration. Only LLMMetric and CustomCodeExecutionMetric are supported.
+ "aggregationMetrics": [ # Optional. The aggregation metrics to use.
+ "A String",
+ ],
+ "bleuSpec": { # Spec for bleu score metric - calculates the precision of n-grams in the prediction as compared to reference - returns a score ranging between 0 to 1. # Spec for bleu metric.
+ "useEffectiveOrder": True or False, # Optional. Whether to use_effective_order to compute bleu score.
+ },
+ "computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
+ "parameters": { # Optional. A map of parameters for the metric, e.g. {"rouge_type": "rougeL"}.
+ "a_key": "", # Properties of the object.
+ },
+ "type": "A String", # Required. The type of the computation based metric.
+ },
+ "customCodeExecutionSpec": { # Specificies a metric that is populated by evaluating user-defined Python code. # Spec for Custom Code Execution metric.
+ "evaluationFunction": "A String", # Required. Python function. Expected user to define the following function, e.g.: def evaluate(instance: dict[str, Any]) -> float: Please include this function signature in the code snippet. Instance is the evaluation instance, any fields populated in the instance are available to the function as instance[field_name]. Example: Example input: ``` instance= EvaluationInstance( response=EvaluationInstance.InstanceData(text="The answer is 4."), reference=EvaluationInstance.InstanceData(text="4") ) ``` Example converted input: ``` { 'response': {'text': 'The answer is 4.'}, 'reference': {'text': '4'} } ``` Example python function: ``` def evaluate(instance: dict[str, Any]) -> float: if instance'response' == instance'reference': return 1.0 return 0.0 ``` CustomCodeExecutionSpec is also supported in Batch Evaluation (EvalDataset RPC) and Tuning Evaluation. Each line in the input jsonl file will be converted to dict[str, Any] and passed to the evaluation function.
+ },
+ "exactMatchSpec": { # Spec for exact match metric - returns 1 if prediction and reference exactly matches, otherwise 0. # Spec for exact match metric.
+ },
+ "llmBasedMetricSpec": { # Specification for an LLM based metric. # Spec for an LLM based metric.
+ "additionalConfig": { # Optional. Optional additional configuration for the metric.
+ "a_key": "", # Properties of the object.
+ },
+ "judgeAutoraterConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Optional. Optional configuration for the judge LLM (Autorater).
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "metricPromptTemplate": "A String", # Required. Template for the prompt sent to the judge model.
+ "predefinedRubricGenerationSpec": { # The spec for a pre-defined metric. # Dynamically generate rubrics using a predefined spec.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "resultParserConfig": { # Config for parsing LLM responses. It can be used to parse the LLM response to be evaluated, or the LLM response from LLM-based metrics/Autoraters. # Optional. The parser config for the metric result.
+ "customCodeParserConfig": { # Configuration for parsing the LLM response using custom code. # Optional. Use custom code to parse the LLM response.
+ "parsingFunction": "A String", # Required. Python function for parsing results. The function should be defined within this string. The function takes a list of strings (LLM responses) and should return either a list of dictionaries (for rubrics) or a single dictionary (for a metric result). Example function signature: def parse(responses: list[str]) -> list[dict[str, Any]] | dict[str, Any]: When parsing rubrics, return a list of dictionaries, where each dictionary represents a Rubric. Example for rubrics: [ { "content": {"property": {"description": "The response is factual."}}, "type": "FACTUALITY", "importance": "HIGH" }, { "content": {"property": {"description": "The response is fluent."}}, "type": "FLUENCY", "importance": "MEDIUM" } ] When parsing critique results, return a dictionary representing a MetricResult. Example for a metric result: { "score": 0.8, "explanation": "The model followed most instructions.", "rubric_verdicts": [...] } ... code for result extraction and aggregation
+ },
+ },
+ "rubricGenerationSpec": { # Specification for how rubrics should be generated. # Dynamically generate rubrics using this specification.
+ "modelConfig": { # The configs for autorater. This is applicable to both EvaluateInstances and EvaluateDataset. # Configuration for the model used in rubric generation. Configs including sampling count and base model can be specified here. Flipping is not supported for rubric generation.
+ "autoraterModel": "A String", # Optional. The fully qualified name of the publisher model or tuned autorater endpoint to use. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
+ "flipEnabled": True or False, # Optional. Default is true. Whether to flip the candidate and baseline responses. This is only applicable to the pairwise metric. If enabled, also provide PairwiseMetricSpec.candidate_response_field_name and PairwiseMetricSpec.baseline_response_field_name. When rendering PairwiseMetricSpec.metric_prompt_template, the candidate and baseline fields will be flipped for half of the samples to reduce bias.
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Configuration options for model generation and outputs.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ ],
+ },
+ "voiceConfig": { # Configuration for a voice. # The configuration for the voice to use.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
+ },
+ "stopSequences": [ # Optional. A list of character sequences that will stop the model from generating further tokens. If a stop sequence is generated, the output will end at that point. This is useful for controlling the length and structure of the output. For example, you can use ["\n", "###"] to stop generation at a new line or a specific marker.
+ "A String",
+ ],
+ "temperature": 3.14, # Optional. Controls the randomness of the output. A higher temperature results in more creative and diverse responses, while a lower temperature makes the output more predictable and focused. The valid range is (0.0, 2.0].
+ "thinkingConfig": { # Configuration for the model's thinking features. "Thinking" is a process where the model breaks down a complex task into smaller, manageable steps. This allows the model to reason about the task, plan its approach, and execute the plan to generate a high-quality response. # Optional. Configuration for thinking features. An error will be returned if this field is set for models that don't support thinking.
+ "includeThoughts": True or False, # Optional. If true, the model will include its thoughts in the response. "Thoughts" are the intermediate steps the model takes to arrive at the final response. They can provide insights into the model's reasoning process and help with debugging. If this is true, thoughts are returned only when available.
+ "thinkingBudget": 42, # Optional. The token budget for the model's thinking process. The model will make a best effort to stay within this budget. This can be used to control the trade-off between response quality and latency.
+ "thinkingLevel": "A String", # Optional. The number of thoughts tokens that the model should generate.
+ },
+ "topK": 3.14, # Optional. Specifies the top-k sampling threshold. The model considers only the top k most probable tokens for the next token. This can be useful for generating more coherent and less random text. For example, a `top_k` of 40 means the model will choose the next word from the 40 most likely words.
+ "topP": 3.14, # Optional. Specifies the nucleus sampling threshold. The model considers only the smallest set of tokens whose cumulative probability is at least `top_p`. This helps generate more diverse and less repetitive responses. For example, a `top_p` of 0.9 means the model considers tokens until the cumulative probability of the tokens to select from reaches 0.9. It's recommended to adjust either temperature or `top_p`, but not both.
+ },
+ "samplingCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
+ },
+ "promptTemplate": "A String", # Template for the prompt used to generate rubrics. The details should be updated based on the most-recent recipe requirements.
+ "rubricContentType": "A String", # The type of rubric content to be generated.
+ "rubricTypeOntology": [ # Optional. An optional, pre-defined list of allowed types for generated rubrics. If this field is provided, it implies `include_rubric_type` should be true, and the generated rubric types should be chosen from this ontology.
+ "A String",
+ ],
+ },
+ "rubricGroupKey": "A String", # Use a pre-defined group of rubrics associated with the input. Refers to a key in the rubric_groups map of EvaluationInstance.
+ "systemInstruction": "A String", # Optional. System instructions for the judge model.
+ },
+ "metadata": { # Metadata about the metric, used for visualization and organization. # Optional. Metadata about the metric, used for visualization and organization.
+ "otherMetadata": { # Optional. Flexible metadata for user-defined attributes.
+ "a_key": "", # Properties of the object.
+ },
+ "scoreRange": { # The range of possible scores for this metric, used for plotting. # Optional. The range of possible scores for this metric, used for plotting.
+ "description": "A String", # Optional. The description of the score explaining the directionality etc.
+ "max": 3.14, # Required. The maximum value of the score range (inclusive).
+ "min": 3.14, # Required. The minimum value of the score range (inclusive).
+ "step": 3.14, # Optional. The distance between discrete steps in the range. If unset, the range is assumed to be continuous.
+ },
+ "title": "A String", # Optional. The user-friendly name for the metric. If not set for a registered metric, it will default to the metric's display name.
+ },
+ "pairwiseMetricSpec": { # Spec for pairwise metric. # Spec for pairwise metric.
+ "baselineResponseFieldName": "A String", # Optional. The field name of the baseline response.
+ "candidateResponseFieldName": "A String", # Optional. The field name of the candidate response.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. When this config is set, the default output is replaced with the raw output string. If a custom format is chosen, the `pairwise_choice` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pairwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pairwise metric.
+ },
+ "pointwiseMetricSpec": { # Spec for pointwise metric. # Spec for pointwise metric.
+ "customOutputFormatConfig": { # Spec for custom output format configuration. # Optional. CustomOutputFormatConfig allows customization of metric output. By default, metrics return a score and explanation. When this config is set, the default output is replaced with either: - The raw output string. - A parsed output based on a user-defined schema. If a custom format is chosen, the `score` and `explanation` fields in the corresponding metric result will be empty.
+ "returnRawOutput": True or False, # Optional. Whether to return raw output.
+ },
+ "metricPromptTemplate": "A String", # Required. Metric prompt template for pointwise metric.
+ "systemInstruction": "A String", # Optional. System instructions for pointwise metric.
+ },
+ "predefinedMetricSpec": { # The spec for a pre-defined metric. # The spec for a pre-defined metric.
+ "metricSpecName": "A String", # Required. The name of a pre-defined metric, such as "instruction_following_v1" or "text_quality_v1".
+ "metricSpecParameters": { # Optional. The parameters needed to run the pre-defined metric.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "rougeSpec": { # Spec for rouge score metric - calculates the recall of n-grams in prediction as compared to reference - returns a score ranging between 0 and 1. # Spec for rouge metric.
+ "rougeType": "A String", # Optional. Supported rouge types are rougen[1-9], rougeL, and rougeLsum.
+ "splitSummaries": True or False, # Optional. Whether to split summaries while using rougeLsum.
+ "useStemmer": True or False, # Optional. Whether to use stemmer to compute rouge score.
+ },
+ },
+ "name": "A String", # Identifier. The resource name of the EvaluationMetric. Format: `projects/{project}/locations/{location}/evaluationMetrics/{evaluation_metric}`
+ "updateTime": "A String", # Output only. The time when the EvaluationMetric was last updated.
+ },
+ ],
+ "nextPageToken": "A String", # A token to retrieve the next page of results.
+}
+
+
+
+ list_next()
+ Retrieves the next page of results.
+
+ Args:
+ previous_request: The request for the previous page. (required)
+ previous_response: The response from the request for the previous page. (required)
+
+ Returns:
+ A request object that you can call 'execute()' on to request the next
+ page. Returns None if there are no more items in the collection.
+
+
+
+
\ No newline at end of file
diff --git a/docs/dyn/aiplatform_v1.projects.locations.evaluationRuns.html b/docs/dyn/aiplatform_v1.projects.locations.evaluationRuns.html
index 75cde2d646..9f867fadb4 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.evaluationRuns.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.evaluationRuns.html
@@ -307,12 +307,30 @@ Method Details
},
"sampleCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
},
+ "cloudLoggingConfig": { # Specifies configuration for exporting evaluation results to Cloud Logging. # Optional. Configuration for exporting evaluation results to Cloud Logging.
+ "project": "A String", # Optional. Google Cloud project to write logs to. Defaults to the request project.
+ "resourceLabels": { # Optional. MonitoredResource labels to associate the log with. The backend will automatically inject project and location.
+ "a_key": "A String",
+ },
+ "resourceType": "A String", # Optional. MonitoredResource type. Defaults to "global" if unspecified.
+ "tracingContext": { # Tracing context for Observability correlation. # Optional. Tracing context for the evaluation run.
+ "conversationId": "A String", # Optional. Unique identifier for a conversation (session thread), used to store and correlate messages within a conversation. The value corresponds to the `gen_ai.conversation.id` field in the the OpenTelemetry GenAI attributes.
+ "spanId": "A String", # Optional. ID of the Cloud Trace span associated with the current operation in which the log is being written. e.g., `7a2190356c3fc94b`. If a span is being evaluated, this field should be populated.
+ "traceId": "A String", # Optional. Trace ID being written to Cloud Trace in association with this log entry. e.g., `12345`, the numeric ID from the resource name. If a trace or span is being evaluated, this field should be populated.
+ },
+ },
"datasetCustomMetrics": [ # Optional. Specifications for custom dataset-level aggregations.
{ # Defines a custom dataset-level aggregation.
"aggregationFunction": "A String", # Required. The Python code string containing the aggregation function. Expected function signature: `def aggregate(instances: list[dict[str, Any]]) -> dict[str, float]:` The `instances` argument is a list of dictionaries, where each dictionary represents a single evaluation result item. The structure of each dictionary corresponds to the fields in the `EvaluationResult` message. This includes: - `"request"`: Contains the original input data and model inputs (from `EvaluationResult.EvaluationRequest`). - `"candidate_results"`: Contains the results of any instance-level metrics (from `EvaluationResult.CandidateResults`). Example of a single item in the `instances` list: { "request": { "prompt": {"text": "What is the capital of France?"}, "golden_response": {"text": "Paris"}, "candidate_responses": [{"candidate": "model-v1", "text": "Paris"}] }, "candidate_results": [ {"metric": "exact_match", "score": 1.0}, {"metric": "bleu", "score": 0.9} ] }
"displayName": "A String", # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like "dataset_custom_metric_1", "dataset_custom_metric_2", etc., will be generated based on the order in the repeated field.
},
],
+ "lossAnalysisConfig": [ # Optional. Specifications for loss analysis. Each config can be specified for one metric.
+ { # Configuration for the loss analysis job.
+ "candidate": "A String", # Required. The candidate model/agent to analyze (e.g., "gemini-3.0-pro"). This targets the specific CandidateResult within the EvaluationResult.
+ "metric": "A String", # Required. The metric to analyze (e.g., "tool_use_quality"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.
+ },
+ ],
"metrics": [ # Optional. The metrics to be calculated in the evaluation run. Required when analysis_configs is not set.
{ # The metric used for evaluation runs.
"computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -1666,6 +1684,243 @@ Method Details
"modelName": "A String", # The model name to use for multi-turn agent scraping to get next user message, e.g. "gemini-3-flash-preview".
},
},
+ "agents": { # Optional. Contains the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
"generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Generation config.
"audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
"candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
@@ -1807,6 +2062,10 @@ Method Details
},
"model": "A String", # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model formats: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` or `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
"parallelism": 42, # Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.
+ "promptTemplate": { # Prompt template used for inference. # Optional. The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. If not specified, the prompt template in the EvaluationConfig will be used.
+ "gcsUri": "A String", # Prompt template stored in Cloud Storage. Format: "gs://my-bucket/file-name.txt".
+ "promptTemplate": "A String", # Inline prompt template. Template variables should be in the format "{var_name}". Example: "Translate the following from {source_lang} to {target_lang}: {text}"
+ },
},
},
"labels": { # Optional. Labels for the evaluation run.
@@ -1998,12 +2257,30 @@ Method Details
},
"sampleCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
},
+ "cloudLoggingConfig": { # Specifies configuration for exporting evaluation results to Cloud Logging. # Optional. Configuration for exporting evaluation results to Cloud Logging.
+ "project": "A String", # Optional. Google Cloud project to write logs to. Defaults to the request project.
+ "resourceLabels": { # Optional. MonitoredResource labels to associate the log with. The backend will automatically inject project and location.
+ "a_key": "A String",
+ },
+ "resourceType": "A String", # Optional. MonitoredResource type. Defaults to "global" if unspecified.
+ "tracingContext": { # Tracing context for Observability correlation. # Optional. Tracing context for the evaluation run.
+ "conversationId": "A String", # Optional. Unique identifier for a conversation (session thread), used to store and correlate messages within a conversation. The value corresponds to the `gen_ai.conversation.id` field in the the OpenTelemetry GenAI attributes.
+ "spanId": "A String", # Optional. ID of the Cloud Trace span associated with the current operation in which the log is being written. e.g., `7a2190356c3fc94b`. If a span is being evaluated, this field should be populated.
+ "traceId": "A String", # Optional. Trace ID being written to Cloud Trace in association with this log entry. e.g., `12345`, the numeric ID from the resource name. If a trace or span is being evaluated, this field should be populated.
+ },
+ },
"datasetCustomMetrics": [ # Optional. Specifications for custom dataset-level aggregations.
{ # Defines a custom dataset-level aggregation.
"aggregationFunction": "A String", # Required. The Python code string containing the aggregation function. Expected function signature: `def aggregate(instances: list[dict[str, Any]]) -> dict[str, float]:` The `instances` argument is a list of dictionaries, where each dictionary represents a single evaluation result item. The structure of each dictionary corresponds to the fields in the `EvaluationResult` message. This includes: - `"request"`: Contains the original input data and model inputs (from `EvaluationResult.EvaluationRequest`). - `"candidate_results"`: Contains the results of any instance-level metrics (from `EvaluationResult.CandidateResults`). Example of a single item in the `instances` list: { "request": { "prompt": {"text": "What is the capital of France?"}, "golden_response": {"text": "Paris"}, "candidate_responses": [{"candidate": "model-v1", "text": "Paris"}] }, "candidate_results": [ {"metric": "exact_match", "score": 1.0}, {"metric": "bleu", "score": 0.9} ] }
"displayName": "A String", # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like "dataset_custom_metric_1", "dataset_custom_metric_2", etc., will be generated based on the order in the repeated field.
},
],
+ "lossAnalysisConfig": [ # Optional. Specifications for loss analysis. Each config can be specified for one metric.
+ { # Configuration for the loss analysis job.
+ "candidate": "A String", # Required. The candidate model/agent to analyze (e.g., "gemini-3.0-pro"). This targets the specific CandidateResult within the EvaluationResult.
+ "metric": "A String", # Required. The metric to analyze (e.g., "tool_use_quality"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.
+ },
+ ],
"metrics": [ # Optional. The metrics to be calculated in the evaluation run. Required when analysis_configs is not set.
{ # The metric used for evaluation runs.
"computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -3357,120 +3634,357 @@ Method Details
"modelName": "A String", # The model name to use for multi-turn agent scraping to get next user message, e.g. "gemini-3-flash-preview".
},
},
- "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Generation config.
- "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
- "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
- "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
- "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
- "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
- "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
- "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
- "compressionQuality": 42, # Optional. The compression quality of the output image.
- "mimeType": "A String", # Optional. The image format that the output should be saved as.
- },
- "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
- "personGeneration": "A String", # Optional. Controls whether the model can generate people.
- "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
- },
- "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
- "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
- "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
- "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
- "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
- { # Configuration for the model to configure output formatting and delivery.
- "audio": { # Configuration for audio-specific output formatting. # Audio output format.
- "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
- "delivery": "A String", # Optional. Delivery mode for the generated content.
- "mimeType": "A String", # Optional. The MIME type of the audio output.
- "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
- },
- "image": { # Configuration for image-specific output formatting. # Image output format.
- "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
- "delivery": "A String", # Optional. Delivery mode for the generated content.
- "imageSize": "A String", # Optional. The size of the image output.
- "mimeType": "A String", # Optional. The MIME type of the image output.
- },
- "text": { # Configuration for text-specific output formatting. # Text output format.
- "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
- "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
- },
- "video": { # Configuration for video-specific output formatting. # Video output format.
- "aspectRatio": "A String", # The aspect ratio for the video output.
- "delivery": "A String", # Optional. Delivery mode for the generated content.
- "duration": "A String", # Optional. The duration for the video output.
- "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
- },
- },
- ],
- "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
- "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
- "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
- "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
- "A String",
- ],
- "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
- "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
- "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
- # Object with schema name: GoogleCloudAiplatformV1Schema
- ],
- "default": "", # Optional. Default value to use if the field is not specified.
- "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
- "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
- },
- "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
- "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
- "A String",
- ],
- "example": "", # Optional. Example of an instance of this schema.
- "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
- "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
- "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
- "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
- "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
- "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
- "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
- "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
- "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
- "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
- "nullable": True or False, # Optional. Indicates if the value of this field can be null.
- "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
- "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
- "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
- },
- "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
- "A String",
- ],
- "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
- "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "agents": { # Optional. Contains the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
"A String",
],
- "title": "A String", # Optional. Title for the schema.
- "type": "A String", # Optional. Data type of the schema field.
- },
- "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
- "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
- "modelRoutingPreference": "A String", # The model routing preference.
- },
- "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
- "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
- },
- },
- "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
- "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
- "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
- "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
- "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
- { # Configuration for a single speaker in a multi-speaker setup.
- "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
- "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
- "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
- "voiceName": "A String", # The name of the prebuilt voice to use.
- },
- "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
- "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
- "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
- },
- },
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Generation config.
+ "audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
+ "candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
+ "enableAffectiveDialog": True or False, # Optional. If enabled, the model will detect emotions and adapt its responses accordingly. For example, if the model detects that the user is frustrated, it may provide a more empathetic response.
+ "frequencyPenalty": 3.14, # Optional. Penalizes tokens based on their frequency in the generated text. A positive value helps to reduce the repetition of words and phrases. Valid values can range from [-2.0, 2.0].
+ "imageConfig": { # Configuration for image generation. This message allows you to control various aspects of image generation, such as the output format, aspect ratio, and whether the model can generate images of people. # Optional. Config for image generation features. Deprecated: Use `response_format.image` instead.
+ "aspectRatio": "A String", # Optional. The desired aspect ratio for the generated images. The following aspect ratios are supported: "1:1" "2:3", "3:2" "3:4", "4:3" "4:5", "5:4" "9:16", "16:9" "21:9"
+ "imageOutputOptions": { # The image output format for generated images. # Optional. The image output format for generated images.
+ "compressionQuality": 42, # Optional. The compression quality of the output image.
+ "mimeType": "A String", # Optional. The image format that the output should be saved as.
+ },
+ "imageSize": "A String", # Optional. Specifies the size of generated images. Supported values are `1K`, `2K`, `4K`. If not specified, the model will use default value `1K`.
+ "personGeneration": "A String", # Optional. Controls whether the model can generate people.
+ "prominentPeople": "A String", # Optional. Controls whether prominent people (celebrities) generation is allowed. If used with personGeneration, personGeneration enum would take precedence. For instance, if ALLOW_NONE is set, all person generation would be blocked. If this field is unspecified, the default behavior is to allow prominent people.
+ },
+ "logprobs": 42, # Optional. The number of top log probabilities to return for each token. This can be used to see which other tokens were considered likely candidates for a given position. A higher value will return more options, but it will also increase the size of the response.
+ "maxOutputTokens": 42, # Optional. The maximum number of tokens to generate in the response. A token is approximately four characters. The default value varies by model. This parameter can be used to control the length of the generated text and prevent overly long responses.
+ "mediaResolution": "A String", # Optional. The token resolution at which input media content is sampled. This is used to control the trade-off between the quality of the response and the number of tokens used to represent the media. A higher resolution allows the model to perceive more detail, which can lead to a more nuanced response, but it will also use more tokens. This does not affect the image dimensions sent to the model.
+ "presencePenalty": 3.14, # Optional. Penalizes tokens that have already appeared in the generated text. A positive value encourages the model to generate more diverse and less repetitive text. Valid values can range from [-2.0, 2.0].
+ "responseFormat": [ # Optional. New response format field for the model to configure output formatting and delivery.
+ { # Configuration for the model to configure output formatting and delivery.
+ "audio": { # Configuration for audio-specific output formatting. # Audio output format.
+ "bitRate": 42, # Optional. Bit rate in bits per second (bps). Only applicable for compressed formats (MP3, Opus).
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "mimeType": "A String", # Optional. The MIME type of the audio output.
+ "sampleRate": 42, # Optional. Sample rate for the generated audio in Hertz.
+ },
+ "image": { # Configuration for image-specific output formatting. # Image output format.
+ "aspectRatio": "A String", # Optional. The aspect ratio for the image output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "imageSize": "A String", # Optional. The size of the image output.
+ "mimeType": "A String", # Optional. The MIME type of the image output.
+ },
+ "text": { # Configuration for text-specific output formatting. # Text output format.
+ "mimeType": "A String", # Optional. The IANA standard MIME type of the response.
+ "schema": "", # Optional. The JSON schema that the output should conform to. Only applicable when mime_type is APPLICATION_JSON.
+ },
+ "video": { # Configuration for video-specific output formatting. # Video output format.
+ "aspectRatio": "A String", # The aspect ratio for the video output.
+ "delivery": "A String", # Optional. Delivery mode for the generated content.
+ "duration": "A String", # Optional. The duration for the video output.
+ "gcsUri": "A String", # Optional. The Google Cloud Storage URI to store the video output. Required for Vertex if delivery is URI.
+ },
+ },
+ ],
+ "responseJsonSchema": "", # Optional. When this field is set, response_schema must be omitted and response_mime_type must be set to `application/json`. Deprecated: Use `response_format` instead.
+ "responseLogprobs": True or False, # Optional. If set to true, the log probabilities of the output tokens are returned. Log probabilities are the logarithm of the probability of a token appearing in the output. A higher log probability means the token is more likely to be generated. This can be useful for analyzing the model's confidence in its own output and for debugging.
+ "responseMimeType": "A String", # Optional. The IANA standard MIME type of the response. The model will generate output that conforms to this MIME type. Supported values include 'text/plain' (default) and 'application/json'. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. Deprecated: Use `response_format` instead.
+ "responseModalities": [ # Optional. The modalities of the response. The model will generate a response that includes all the specified modalities. For example, if this is set to `[TEXT, IMAGE]`, the response will include both text and an image.
+ "A String",
+ ],
+ "responseSchema": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Lets you to specify a schema for the model's response, ensuring that the output conforms to a particular structure. This is useful for generating structured data such as JSON. The schema is a subset of the [OpenAPI 3.0 schema object](https://spec.openapis.org/oas/v3.0.3#schema) object. When this field is set, you must also set the `response_mime_type` to `application/json`. Deprecated: Use `response_format` instead.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "routingConfig": { # The configuration for routing the request to a specific model. This can be used to control which model is used for the generation, either automatically or by specifying a model name. # Optional. Routing configuration.
+ "autoMode": { # The configuration for automated routing. When automated routing is specified, the routing will be determined by the pretrained routing model and customer provided model routing preference. # In this mode, the model is selected automatically based on the content of the request.
+ "modelRoutingPreference": "A String", # The model routing preference.
+ },
+ "manualMode": { # The configuration for manual routing. When manual routing is specified, the model will be selected based on the model name provided. # In this mode, the model is specified manually.
+ "modelName": "A String", # The name of the model to use. Only public LLM models are accepted.
+ },
+ },
+ "seed": 42, # Optional. A seed for the random number generator. By setting a seed, you can make the model's output mostly deterministic. For a given prompt and parameters (like temperature, top_p, etc.), the model will produce the same response every time. However, it's not a guaranteed absolute deterministic behavior. This is different from parameters like `temperature`, which control the *level* of randomness. `seed` ensures that the "random" choices the model makes are the same on every run, making it essential for testing and ensuring reproducible results.
+ "speechConfig": { # Configuration for speech generation. # Optional. The speech generation config.
+ "languageCode": "A String", # Optional. The language code (ISO 639-1) for the speech synthesis.
+ "multiSpeakerVoiceConfig": { # Configuration for a multi-speaker text-to-speech request. # The configuration for a multi-speaker text-to-speech request. This field is mutually exclusive with `voice_config`.
+ "speakerVoiceConfigs": [ # Required. A list of configurations for the voices of the speakers. Exactly two speaker voice configurations must be provided.
+ { # Configuration for a single speaker in a multi-speaker setup.
+ "speaker": "A String", # Required. The name of the speaker. This should be the same as the speaker name used in the prompt.
+ "voiceConfig": { # Configuration for a voice. # Required. The configuration for the voice of this speaker.
+ "prebuiltVoiceConfig": { # Configuration for a prebuilt voice. # The configuration for a prebuilt voice.
+ "voiceName": "A String", # The name of the prebuilt voice to use.
+ },
+ "replicatedVoiceConfig": { # The configuration for the replicated voice to use. # Optional. The configuration for a replicated voice. This enables users to replicate a voice from an audio sample.
+ "mimeType": "A String", # Optional. The mimetype of the voice sample. The only currently supported value is `audio/wav`. This represents 16-bit signed little-endian wav data, with a 24kHz sampling rate. `mime_type` will default to `audio/wav` if not set.
+ "voiceSampleAudio": "A String", # Optional. The sample of the custom voice.
+ },
+ },
},
],
},
@@ -3498,6 +4012,10 @@ Method Details
},
"model": "A String", # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model formats: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` or `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
"parallelism": 42, # Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.
+ "promptTemplate": { # Prompt template used for inference. # Optional. The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. If not specified, the prompt template in the EvaluationConfig will be used.
+ "gcsUri": "A String", # Prompt template stored in Cloud Storage. Format: "gs://my-bucket/file-name.txt".
+ "promptTemplate": "A String", # Inline prompt template. Template variables should be in the format "{var_name}". Example: "Translate the following from {source_lang} to {target_lang}: {text}"
+ },
},
},
"labels": { # Optional. Labels for the evaluation run.
@@ -3731,12 +4249,30 @@ Method Details
},
"sampleCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
},
+ "cloudLoggingConfig": { # Specifies configuration for exporting evaluation results to Cloud Logging. # Optional. Configuration for exporting evaluation results to Cloud Logging.
+ "project": "A String", # Optional. Google Cloud project to write logs to. Defaults to the request project.
+ "resourceLabels": { # Optional. MonitoredResource labels to associate the log with. The backend will automatically inject project and location.
+ "a_key": "A String",
+ },
+ "resourceType": "A String", # Optional. MonitoredResource type. Defaults to "global" if unspecified.
+ "tracingContext": { # Tracing context for Observability correlation. # Optional. Tracing context for the evaluation run.
+ "conversationId": "A String", # Optional. Unique identifier for a conversation (session thread), used to store and correlate messages within a conversation. The value corresponds to the `gen_ai.conversation.id` field in the the OpenTelemetry GenAI attributes.
+ "spanId": "A String", # Optional. ID of the Cloud Trace span associated with the current operation in which the log is being written. e.g., `7a2190356c3fc94b`. If a span is being evaluated, this field should be populated.
+ "traceId": "A String", # Optional. Trace ID being written to Cloud Trace in association with this log entry. e.g., `12345`, the numeric ID from the resource name. If a trace or span is being evaluated, this field should be populated.
+ },
+ },
"datasetCustomMetrics": [ # Optional. Specifications for custom dataset-level aggregations.
{ # Defines a custom dataset-level aggregation.
"aggregationFunction": "A String", # Required. The Python code string containing the aggregation function. Expected function signature: `def aggregate(instances: list[dict[str, Any]]) -> dict[str, float]:` The `instances` argument is a list of dictionaries, where each dictionary represents a single evaluation result item. The structure of each dictionary corresponds to the fields in the `EvaluationResult` message. This includes: - `"request"`: Contains the original input data and model inputs (from `EvaluationResult.EvaluationRequest`). - `"candidate_results"`: Contains the results of any instance-level metrics (from `EvaluationResult.CandidateResults`). Example of a single item in the `instances` list: { "request": { "prompt": {"text": "What is the capital of France?"}, "golden_response": {"text": "Paris"}, "candidate_responses": [{"candidate": "model-v1", "text": "Paris"}] }, "candidate_results": [ {"metric": "exact_match", "score": 1.0}, {"metric": "bleu", "score": 0.9} ] }
"displayName": "A String", # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like "dataset_custom_metric_1", "dataset_custom_metric_2", etc., will be generated based on the order in the repeated field.
},
],
+ "lossAnalysisConfig": [ # Optional. Specifications for loss analysis. Each config can be specified for one metric.
+ { # Configuration for the loss analysis job.
+ "candidate": "A String", # Required. The candidate model/agent to analyze (e.g., "gemini-3.0-pro"). This targets the specific CandidateResult within the EvaluationResult.
+ "metric": "A String", # Required. The metric to analyze (e.g., "tool_use_quality"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.
+ },
+ ],
"metrics": [ # Optional. The metrics to be calculated in the evaluation run. Required when analysis_configs is not set.
{ # The metric used for evaluation runs.
"computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -5090,6 +5626,243 @@ Method Details
"modelName": "A String", # The model name to use for multi-turn agent scraping to get next user message, e.g. "gemini-3-flash-preview".
},
},
+ "agents": { # Optional. Contains the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
"generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Generation config.
"audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
"candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
@@ -5231,6 +6004,10 @@ Method Details
},
"model": "A String", # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model formats: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` or `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
"parallelism": 42, # Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.
+ "promptTemplate": { # Prompt template used for inference. # Optional. The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. If not specified, the prompt template in the EvaluationConfig will be used.
+ "gcsUri": "A String", # Prompt template stored in Cloud Storage. Format: "gs://my-bucket/file-name.txt".
+ "promptTemplate": "A String", # Inline prompt template. Template variables should be in the format "{var_name}". Example: "Translate the following from {source_lang} to {target_lang}: {text}"
+ },
},
},
"labels": { # Optional. Labels for the evaluation run.
@@ -5435,12 +6212,30 @@ Method Details
},
"sampleCount": 42, # Optional. Number of samples for each instance in the dataset. If not specified, the default is 4. Minimum value is 1, maximum value is 32.
},
+ "cloudLoggingConfig": { # Specifies configuration for exporting evaluation results to Cloud Logging. # Optional. Configuration for exporting evaluation results to Cloud Logging.
+ "project": "A String", # Optional. Google Cloud project to write logs to. Defaults to the request project.
+ "resourceLabels": { # Optional. MonitoredResource labels to associate the log with. The backend will automatically inject project and location.
+ "a_key": "A String",
+ },
+ "resourceType": "A String", # Optional. MonitoredResource type. Defaults to "global" if unspecified.
+ "tracingContext": { # Tracing context for Observability correlation. # Optional. Tracing context for the evaluation run.
+ "conversationId": "A String", # Optional. Unique identifier for a conversation (session thread), used to store and correlate messages within a conversation. The value corresponds to the `gen_ai.conversation.id` field in the the OpenTelemetry GenAI attributes.
+ "spanId": "A String", # Optional. ID of the Cloud Trace span associated with the current operation in which the log is being written. e.g., `7a2190356c3fc94b`. If a span is being evaluated, this field should be populated.
+ "traceId": "A String", # Optional. Trace ID being written to Cloud Trace in association with this log entry. e.g., `12345`, the numeric ID from the resource name. If a trace or span is being evaluated, this field should be populated.
+ },
+ },
"datasetCustomMetrics": [ # Optional. Specifications for custom dataset-level aggregations.
{ # Defines a custom dataset-level aggregation.
"aggregationFunction": "A String", # Required. The Python code string containing the aggregation function. Expected function signature: `def aggregate(instances: list[dict[str, Any]]) -> dict[str, float]:` The `instances` argument is a list of dictionaries, where each dictionary represents a single evaluation result item. The structure of each dictionary corresponds to the fields in the `EvaluationResult` message. This includes: - `"request"`: Contains the original input data and model inputs (from `EvaluationResult.EvaluationRequest`). - `"candidate_results"`: Contains the results of any instance-level metrics (from `EvaluationResult.CandidateResults`). Example of a single item in the `instances` list: { "request": { "prompt": {"text": "What is the capital of France?"}, "golden_response": {"text": "Paris"}, "candidate_responses": [{"candidate": "model-v1", "text": "Paris"}] }, "candidate_results": [ {"metric": "exact_match", "score": 1.0}, {"metric": "bleu", "score": 0.9} ] }
"displayName": "A String", # Optional. A display name for this custom summary metric. Used to prefix keys in the output summaryMetrics map. If not provided, a default name like "dataset_custom_metric_1", "dataset_custom_metric_2", etc., will be generated based on the order in the repeated field.
},
],
+ "lossAnalysisConfig": [ # Optional. Specifications for loss analysis. Each config can be specified for one metric.
+ { # Configuration for the loss analysis job.
+ "candidate": "A String", # Required. The candidate model/agent to analyze (e.g., "gemini-3.0-pro"). This targets the specific CandidateResult within the EvaluationResult.
+ "metric": "A String", # Required. The metric to analyze (e.g., "tool_use_quality"). This filters the EvaluationItems in the EvalSet to only those where EvaluationResult.metric matches this value.
+ },
+ ],
"metrics": [ # Optional. The metrics to be calculated in the evaluation run. Required when analysis_configs is not set.
{ # The metric used for evaluation runs.
"computationBasedMetricSpec": { # Specification for a computation based metric. # Spec for a computation based metric.
@@ -6794,6 +7589,243 @@ Method Details
"modelName": "A String", # The model name to use for multi-turn agent scraping to get next user message, e.g. "gemini-3-flash-preview".
},
},
+ "agents": { # Optional. Contains the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
"generationConfig": { # Configuration for content generation. This message contains all the parameters that control how the model generates content. It allows you to influence the randomness, length, and structure of the output. # Optional. Generation config.
"audioTimestamp": True or False, # Optional. If enabled, audio timestamps will be included in the request to the model. This can be useful for synchronizing audio with other modalities in the response.
"candidateCount": 42, # Optional. The number of candidate responses to generate. A higher `candidate_count` can provide more options to choose from, but it also consumes more resources. This can be useful for generating a variety of responses and selecting the best one.
@@ -6935,6 +7967,10 @@ Method Details
},
"model": "A String", # Optional. The fully qualified name of the publisher model or endpoint to use. Anthropic and Llama third-party models are also supported through Model Garden. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Third-party model formats: `projects/{project}/locations/{location}/publishers/anthropic/models/{model}` or `projects/{project}/locations/{location}/publishers/llama/models/{model}` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
"parallelism": 42, # Optional. The parallelism of the evaluation run for the inference step. If not specified, the default parallelism will be used.
+ "promptTemplate": { # Prompt template used for inference. # Optional. The prompt template used for inference. The values for variables in the prompt template are defined in EvaluationItem.EvaluationPrompt.PromptTemplateData.values. If not specified, the prompt template in the EvaluationConfig will be used.
+ "gcsUri": "A String", # Prompt template stored in Cloud Storage. Format: "gs://my-bucket/file-name.txt".
+ "promptTemplate": "A String", # Inline prompt template. Template variables should be in the format "{var_name}". Example: "Translate the following from {source_lang} to {target_lang}: {text}"
+ },
},
},
"labels": { # Optional. Labels for the evaluation run.
diff --git a/docs/dyn/aiplatform_v1.projects.locations.evaluationSets.html b/docs/dyn/aiplatform_v1.projects.locations.evaluationSets.html
index a87310d996..9df98be642 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.evaluationSets.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.evaluationSets.html
@@ -259,7 +259,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -514,7 +515,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -811,7 +813,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1099,7 +1102,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1413,7 +1417,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1687,7 +1692,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1943,7 +1949,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
diff --git a/docs/dyn/aiplatform_v1.projects.locations.html b/docs/dyn/aiplatform_v1.projects.locations.html
index 3323ba7d7d..f410629cb6 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.html
@@ -119,6 +119,11 @@ Instance Methods
Returns the evaluationItems Resource.
+
+Returns the evaluationMetrics Resource.
+
@@ -159,6 +164,11 @@ Instance Methods
Returns the indexes Resource.
+
+ memoryBanks()
+
+Returns the memoryBanks Resource.
+
@@ -510,7 +520,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -796,7 +807,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -2532,7 +2544,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -2850,7 +2863,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -3239,7 +3253,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -3470,7 +3485,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -5740,7 +5756,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -6117,6 +6134,15 @@ Method Details
{ # Result for a single candidate.
"additionalResults": "", # Optional. Additional results for the metric.
"candidate": "A String", # Required. The candidate that is being evaluated. The value is the same as the candidate name in the EvaluationRequest.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while evaluating the candidate for the metric.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
"explanation": "A String", # Optional. The explanation for the metric.
"metric": "A String", # Required. The metric that was evaluated.
"rubricVerdicts": [ # Optional. The rubric verdicts for the metric.
@@ -6145,6 +6171,560 @@ Method Details
"request": { # A single evaluation request supporting input for both single-turn model generation and multi-turn agent execution traces. Valid input modes: 1. Inference Mode: `prompt` is set (containing text or AgentData context). 2. Offline Eval Mode: `prompt` is unset, and `candidate_responses` contains `agent_data` (the completed execution trace). Validation Rule: Either `prompt` must be set, OR at least one of the `candidate_responses` must contain `agent_data`. # Required. The request that was evaluated.
"candidateResponses": [ # Optional. Responses from model under test and other baseline models for comparison.
{ # Responses from model or agent.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -6160,6 +6740,560 @@ Method Details
},
],
"goldenResponse": { # Responses from model or agent. # Optional. The Ideal response or ground truth.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This field is used to provide the full output of an agent's run, including all turns and events, for direct evaluation.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"candidate": "A String", # Required. The name of the candidate that produced the response.
"error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # Output only. Error while scraping model or agent.
"code": 42, # The status code, which should be an enum value of google.rpc.Code.
@@ -6174,6 +7308,560 @@ Method Details
"value": "", # Fields and values that can be used to populate the response template.
},
"prompt": { # Prompt to be evaluated. This can represent a single-turn prompt or a multi-turn conversation for agent evaluations. # Optional. The request/prompt to evaluate.
+ "agentData": { # Represents data specific to multi-turn agent evaluations. # Optional. Represents the complete execution trace of a multi-turn conversation, which can involve single or multiple agents. This serves as the input context for agent scraping.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "a_key": { # Represents configuration for an Agent.
+ "agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
+ "agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
+ "description": "A String", # Optional. A high-level description of the agent's role and responsibilities. Critical for evaluating if the agent is routing tasks correctly.
+ "instruction": "A String", # Optional. Provides instructions for the LLM model, guiding the agent's behavior. Can be static or dynamic. Dynamic instructions can contain placeholders like {variable_name} that will be resolved at runtime using the `AgentEvent.state_delta` field.
+ "subAgents": [ # Optional. The list of valid agent IDs that this agent can delegate to. This defines the directed edges in the multi-agent system graph topology.
+ "A String",
+ ],
+ "tools": [ # Optional. The list of tools available to this agent.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ },
+ },
+ "turns": [ # Optional. A chronological list of conversation turns. Each turn represents a logical execution cycle (e.g., User Input -> Agent Response).
+ { # Represents a single turn/invocation in the conversation.
+ "events": [ # Optional. The list of events that occurred during this turn.
+ { # Represents a single event in the execution trace.
+ "activeTools": [ # Optional. The list of tools that were active/available to the agent at the time of this event. This overrides the `AgentConfig.tools` if set.
+ { # Tool details that the model may use to generate response. A `Tool` is a piece of code that enables the system to interact with external systems to perform an action, or set of actions, outside of knowledge and scope of the model. A Tool object should contain exactly one type of Tool (e.g FunctionDeclaration, Retrieval or GoogleSearchRetrieval).
+ "codeExecution": { # Tool that executes code generated by the model, and automatically returns the result to the model. See also ExecutableCode and CodeExecutionResult, which are input and output to this tool. # Optional. CodeExecution tool type. Enables the model to execute code as part of generation.
+ },
+ "computerUse": { # Tool to support computer use. # Optional. Tool to support the model interacting directly with the computer. If enabled, it automatically populates computer-use specific Function Declarations.
+ "enablePromptInjectionDetection": True or False, # Optional. Enables the prompt injection detection check on computer-use request.
+ "environment": "A String", # Required. The environment being operated.
+ "excludedPredefinedFunctions": [ # Optional. By default, [predefined functions](https://cloud.google.com/vertex-ai/generative-ai/docs/computer-use#supported-actions) are included in the final model call. Some of them can be explicitly excluded from being automatically included. This can serve two purposes: 1. Using a more restricted / different action space. 2. Improving the definitions / instructions of predefined functions.
+ "A String",
+ ],
+ },
+ "enterpriseWebSearch": { # Tool to search public web data, powered by Vertex AI Search and Sec4 compliance. # Optional. Tool to support searching public web data, powered by Vertex AI Search and Sec4 compliance.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains.
+ "A String",
+ ],
+ },
+ "exaAiSearch": { # ExaAiSearch tool type. A tool that uses the Exa.ai search engine for grounding. # Optional. Uses Exa.ai to search for information to answer user queries. The search results will be grounded on Exa.ai and presented to the model for response generation
+ "apiKey": "A String", # Required. The API key for ExaAiSearch.
+ "customConfigs": { # Optional. This field can be used to pass any parameter from the Exa.ai Search API.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ "functionDeclarations": [ # Optional. Function tool type. One or more function declarations to be passed to the model along with the current user query. Model may decide to call a subset of these functions by populating FunctionCall in the response. User should provide a FunctionResponse for each function call in the next turn. Based on the function responses, Model will generate the final response back to the user. Maximum 512 function declarations can be provided.
+ { # Structured representation of a function declaration as defined by the [OpenAPI 3.0 specification](https://spec.openapis.org/oas/v3.0.3). Included in this declaration are the function name, description, parameters and response type. This FunctionDeclaration is a representation of a block of code that can be used as a `Tool` by the model and executed by the client.
+ "behavior": "A String", # Optional. Specifies the function Behavior. If not specified, the system keeps the current function call behavior. This field is currently only supported by the BidiGenerateContent method.
+ "description": "A String", # Optional. Description and purpose of the function. Model uses it to decide how and whether to call the function.
+ "name": "A String", # Required. The name of the function to call. Must start with a letter or an underscore. Must be a-z, A-Z, 0-9, or contain underscores, dots, colons and dashes, with a maximum length of 128.
+ "parameters": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the parameters to this function in JSON Schema Object format. Reflects the Open API 3.03 Parameter Object. string Key: the name of the parameter. Parameter names are case sensitive. Schema Value: the Schema defining the type used for the parameter. For function with no parameters, this can be left unset. Parameter names must start with a letter or an underscore and must only contain chars a-z, A-Z, 0-9, or underscores with a maximum length of 64. Example with 1 required and 1 optional parameter: type: OBJECT properties: param1: type: STRING param2: type: INTEGER required: - param1
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "parametersJsonSchema": "", # Optional. Describes the parameters to the function in JSON Schema format. The schema must describe an object where the properties are the parameters to the function. For example: ``` { "type": "object", "properties": { "name": { "type": "string" }, "age": { "type": "integer" } }, "additionalProperties": false, "required": ["name", "age"], "propertyOrdering": ["name", "age"] } ``` This field is mutually exclusive with `parameters`.
+ "response": { # Defines the schema of input and output data. This is a subset of the [OpenAPI 3.0 Schema Object](https://spec.openapis.org/oas/v3.0.3#schema-object). # Optional. Describes the output from this function in JSON Schema format. Reflects the Open API 3.03 Response Object. The Schema defines the type used for the response value of the function.
+ "additionalProperties": "", # Optional. If `type` is `OBJECT`, specifies how to handle properties not defined in `properties`. If it is a boolean `false`, no additional properties are allowed. If it is a schema, additional properties are allowed if they conform to the schema.
+ "anyOf": [ # Optional. The instance must be valid against any (one or more) of the subschemas listed in `any_of`.
+ # Object with schema name: GoogleCloudAiplatformV1Schema
+ ],
+ "default": "", # Optional. Default value to use if the field is not specified.
+ "defs": { # Optional. `defs` provides a map of schema definitions that can be reused by `ref` elsewhere in the schema. Only allowed at root level of the schema.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "description": "A String", # Optional. Describes the data. The model uses this field to understand the purpose of the schema and how to use it. It is a best practice to provide a clear and descriptive explanation for the schema and its properties here, rather than in the prompt.
+ "enum": [ # Optional. Possible values of the field. This field can be used to restrict a value to a fixed set of values. To mark a field as an enum, set `format` to `enum` and provide the list of possible values in `enum`. For example: 1. To define directions: `{type:STRING, format:enum, enum:["EAST", "NORTH", "SOUTH", "WEST"]}` 2. To define apartment numbers: `{type:INTEGER, format:enum, enum:["101", "201", "301"]}`
+ "A String",
+ ],
+ "example": "", # Optional. Example of an instance of this schema.
+ "format": "A String", # Optional. The format of the data. For `NUMBER` type, format can be `float` or `double`. For `INTEGER` type, format can be `int32` or `int64`. For `STRING` type, format can be `email`, `byte`, `date`, `date-time`, `password`, and other formats to further refine the data type.
+ "items": # Object with schema name: GoogleCloudAiplatformV1Schema # Optional. If type is `ARRAY`, `items` specifies the schema of elements in the array.
+ "maxItems": "A String", # Optional. If type is `ARRAY`, `max_items` specifies the maximum number of items in an array.
+ "maxLength": "A String", # Optional. If type is `STRING`, `max_length` specifies the maximum length of the string.
+ "maxProperties": "A String", # Optional. If type is `OBJECT`, `max_properties` specifies the maximum number of properties that can be provided.
+ "maximum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `maximum` specifies the maximum allowed value.
+ "minItems": "A String", # Optional. If type is `ARRAY`, `min_items` specifies the minimum number of items in an array.
+ "minLength": "A String", # Optional. If type is `STRING`, `min_length` specifies the minimum length of the string.
+ "minProperties": "A String", # Optional. If type is `OBJECT`, `min_properties` specifies the minimum number of properties that can be provided.
+ "minimum": 3.14, # Optional. If type is `INTEGER` or `NUMBER`, `minimum` specifies the minimum allowed value.
+ "nullable": True or False, # Optional. Indicates if the value of this field can be null.
+ "pattern": "A String", # Optional. If type is `STRING`, `pattern` specifies a regular expression that the string must match.
+ "properties": { # Optional. If type is `OBJECT`, `properties` is a map of property names to schema definitions for each property of the object.
+ "a_key": # Object with schema name: GoogleCloudAiplatformV1Schema
+ },
+ "propertyOrdering": [ # Optional. Order of properties displayed or used where order matters. This is not a standard field in OpenAPI specification, but can be used to control the order of properties.
+ "A String",
+ ],
+ "ref": "A String", # Optional. Allows referencing another schema definition to use in place of this schema. The value must be a valid reference to a schema in `defs`. For example, the following schema defines a reference to a schema node named "Pet": type: object properties: pet: ref: #/defs/Pet defs: Pet: type: object properties: name: type: string The value of the "pet" property is a reference to the schema node named "Pet". See details in https://json-schema.org/understanding-json-schema/structuring
+ "required": [ # Optional. If type is `OBJECT`, `required` lists the names of properties that must be present.
+ "A String",
+ ],
+ "title": "A String", # Optional. Title for the schema.
+ "type": "A String", # Optional. Data type of the schema field.
+ },
+ "responseJsonSchema": "", # Optional. Describes the output from this function in JSON Schema format. The value specified by the schema is the response value of the function. This field is mutually exclusive with `response`.
+ },
+ ],
+ "googleMaps": { # Tool to retrieve public maps data for grounding, powered by Google. # Optional. GoogleMaps tool type. Tool to support Google Maps in Model.
+ "enableWidget": True or False, # Optional. Deprecated: The Google Maps contextual widget behavior in Grounding with Google Maps is being deprecated; this field is planned for removal and no longer has any effect once removed. If true, include the widget context token in the response.
+ },
+ "googleSearch": { # GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google. # Optional. GoogleSearch tool type. Tool to support Google Search in Model. Powered by Google.
+ "blockingConfidence": "A String", # Optional. Sites with confidence level chosen & above this value will be blocked from the search results.
+ "excludeDomains": [ # Optional. List of domains to be excluded from the search results. The default limit is 2000 domains. Example: ["amazon.com", "facebook.com"].
+ "A String",
+ ],
+ "searchTypes": { # Different types of search that can be enabled on the GoogleSearch tool. # Optional. The set of search types to enable. If not set, web search is enabled by default.
+ "imageSearch": { # Image search for grounding and related configurations. # Optional. Setting this field enables image search. Image bytes are returned.
+ },
+ "webSearch": { # Standard web search for grounding and related configurations. Only text results are returned. # Optional. Setting this field enables web search. Only text results are returned.
+ },
+ },
+ },
+ "googleSearchRetrieval": { # Tool to retrieve public web data for grounding, powered by Google. # Optional. Specialized retrieval tool that is powered by Google Search.
+ "dynamicRetrievalConfig": { # Describes the options to customize dynamic retrieval. # Specifies the dynamic retrieval configuration for the given source.
+ "dynamicThreshold": 3.14, # Optional. The threshold to be used in dynamic retrieval. If not set, a system default value is used.
+ "mode": "A String", # The mode of the predictor to be used in dynamic retrieval.
+ },
+ },
+ "parallelAiSearch": { # ParallelAiSearch tool type. A tool that uses the Parallel.ai search engine for grounding. # Optional. If specified, Vertex AI will use Parallel.ai to search for information to answer user queries. The search results will be grounded on Parallel.ai and presented to the model for response generation
+ "apiKey": "A String", # Optional. The API key for ParallelAiSearch. If an API key is not provided, the system will attempt to verify access by checking for an active Parallel.ai subscription through the Google Cloud Marketplace. See https://docs.parallel.ai/search/search-quickstart for more details.
+ "customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
+ "a_key": "", # Properties of the object.
+ },
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ },
+ "retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
+ "disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
+ "externalApi": { # Retrieve from data source powered by external API for grounding. The external API is not owned by Google, but need to follow the pre-defined API spec. # Use data source powered by external API for grounding.
+ "apiAuth": { # The generic reusable api auth config. Deprecated. Please use AuthConfig (google/cloud/aiplatform/master/auth.proto) instead. # The authentication config to access the API. Deprecated. Please use auth_config instead.
+ "apiKeyConfig": { # The API secret. # The API secret.
+ "apiKeySecretVersion": "A String", # Required. The SecretManager secret version resource name storing API key. e.g. projects/{project}/secrets/{secret}/versions/{version}
+ "apiKeyString": "A String", # The API key string. Either this or `api_key_secret_version` must be set.
+ },
+ },
+ "apiSpec": "A String", # The API spec that the external API implements.
+ "authConfig": { # Auth configuration to run the extension. # The authentication config to access the API.
+ "apiKeyConfig": { # Config for authentication with API key. # Config for API key auth.
+ "apiKeySecret": "A String", # Optional. The name of the SecretManager secret version resource storing the API key. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If both `api_key_secret` and `api_key_string` are specified, this field takes precedence over `api_key_string`. - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ "apiKeyString": "A String", # Optional. The API key to be used in the request directly.
+ "httpElementLocation": "A String", # Optional. The location of the API key.
+ "name": "A String", # Optional. The parameter name of the API key. E.g. If the API request is "https://example.com/act?api_key=", "api_key" would be the parameter name.
+ },
+ "authType": "A String", # Type of auth scheme.
+ "googleServiceAccountConfig": { # Config for Google Service Account Authentication. # Config for Google Service Account auth.
+ "serviceAccount": "A String", # Optional. The service account that the extension execution service runs as. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified service account. - If not specified, the Vertex AI Extension Service Agent will be used to execute the Extension.
+ },
+ "httpBasicAuthConfig": { # Config for HTTP Basic Authentication. # Config for HTTP Basic auth.
+ "credentialSecret": "A String", # Required. The name of the SecretManager secret version resource storing the base64 encoded credentials. Format: `projects/{project}/secrets/{secrete}/versions/{version}` - If specified, the `secretmanager.versions.access` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the specified resource.
+ },
+ "oauthConfig": { # Config for user oauth. # Config for user oauth.
+ "accessToken": "A String", # Access token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate access tokens for executing the Extension. - If the service account is specified, the `iam.serviceAccounts.getAccessToken` permission should be granted to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents) on the provided service account.
+ },
+ "oidcConfig": { # Config for user OIDC auth. # Config for user OIDC auth.
+ "idToken": "A String", # OpenID Connect formatted ID token for extension endpoint. Only used to propagate token from [[ExecuteExtensionRequest.runtime_auth_config]] at request time.
+ "serviceAccount": "A String", # The service account used to generate an OpenID Connect (OIDC)-compatible JWT token signed by the Google OIDC Provider (accounts.google.com) for extension endpoint (https://cloud.google.com/iam/docs/create-short-lived-credentials-direct#sa-credentials-oidc). - The audience for the token will be set to the URL in the server url defined in the OpenApi spec. - If the service account is provided, the service account should grant `iam.serviceAccounts.getOpenIdToken` permission to Vertex AI Extension Service Agent (https://cloud.google.com/vertex-ai/docs/general/access-control#service-agents).
+ },
+ },
+ "elasticSearchParams": { # The search parameters to use for the ELASTIC_SEARCH spec. # Parameters for the elastic search API.
+ "index": "A String", # The ElasticSearch index to use.
+ "numHits": 42, # Optional. Number of hits (chunks) to request. When specified, it is passed to Elasticsearch as the `num_hits` param.
+ "searchTemplate": "A String", # The ElasticSearch search template to use.
+ },
+ "endpoint": "A String", # The endpoint of the external API. The system will call the API at this endpoint to retrieve the data for grounding. Example: https://acme.com:443/search
+ "simpleSearchParams": { # The search parameters to use for SIMPLE_SEARCH spec. # Parameters for the simple search API.
+ },
+ },
+ "vertexAiSearch": { # Retrieve from Vertex AI Search datastore or engine for grounding. datastore and engine are mutually exclusive. See https://cloud.google.com/products/agent-builder # Set to use data source powered by Vertex AI Search.
+ "dataStoreSpecs": [ # Specifications that define the specific DataStores to be searched, along with configurations for those data stores. This is only considered for Engines with multiple data stores. It should only be set if engine is used.
+ { # Define data stores within engine to filter on in a search call and configurations for those data stores. For more information, see https://cloud.google.com/generative-ai-app-builder/docs/reference/rpc/google.cloud.discoveryengine.v1#datastorespec
+ "dataStore": "A String", # Full resource name of DataStore, such as Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "filter": "A String", # Optional. Filter specification to filter documents in the data store specified by data_store field. For more information on filtering, see [Filtering](https://cloud.google.com/generative-ai-app-builder/docs/filter-search-metadata)
+ },
+ ],
+ "datastore": "A String", # Optional. Fully-qualified Vertex AI Search data store resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/dataStores/{dataStore}`
+ "engine": "A String", # Optional. Fully-qualified Vertex AI Search engine resource ID. Format: `projects/{project}/locations/{location}/collections/{collection}/engines/{engine}`
+ "filter": "A String", # Optional. Filter strings to be passed to the search API.
+ "maxResults": 42, # Optional. Number of search results to return per query. The default value is 10. The maximumm allowed value is 10.
+ },
+ "vertexRagStore": { # Retrieve from Vertex RAG Store for grounding. # Set to use data source powered by Vertex RAG store. User data is uploaded via the VertexRagDataService.
+ "ragResources": [ # Optional. The representation of the rag source. It can be used to specify corpus only or ragfiles. Currently only support one corpus or multiple files from one corpus. In the future we may open up multiple corpora support.
+ { # The definition of the Rag resource.
+ "ragCorpus": "A String", # Optional. RagCorpora resource name. Format: `projects/{project}/locations/{location}/ragCorpora/{rag_corpus}`
+ "ragFileIds": [ # Optional. rag_file_id. The files should be in the same rag_corpus set in rag_corpus field.
+ "A String",
+ ],
+ },
+ ],
+ "ragRetrievalConfig": { # Specifies the context retrieval config. # Optional. The retrieval config for the Rag query.
+ "filter": { # Config for filters. # Optional. Config for filters.
+ "metadataFilter": "A String", # Optional. String for metadata filtering.
+ "vectorDistanceThreshold": 3.14, # Optional. Only returns contexts with vector distance smaller than the threshold.
+ "vectorSimilarityThreshold": 3.14, # Optional. Only returns contexts with vector similarity larger than the threshold.
+ },
+ "ranking": { # Config for ranking and reranking. # Optional. Config for ranking and reranking.
+ "llmRanker": { # Config for LlmRanker. # Optional. Config for LlmRanker.
+ "modelName": "A String", # Optional. The model name used for ranking. See [Supported models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-reference/inference#supported-models).
+ },
+ "rankService": { # Config for Rank Service. # Optional. Config for Rank Service.
+ "modelName": "A String", # Optional. The model name of the rank service. Format: `semantic-ranker-512@latest`
+ },
+ },
+ "topK": 42, # Optional. The number of contexts to retrieve.
+ },
+ "similarityTopK": 42, # Optional. Number of top k results to return from the selected corpora.
+ "vectorDistanceThreshold": 3.14, # Optional. Only return results with vector distance smaller than the threshold.
+ },
+ },
+ "urlContext": { # Tool to support URL context. # Optional. Tool to support URL context retrieval.
+ },
+ },
+ ],
+ "author": "A String", # Required. The ID of the agent or entity that generated this event. Use "user" to denote events generated by the end-user.
+ "content": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message. # Required. The content of the event (e.g., text response, tool call, tool response).
+ "parts": [ # Required. A list of Part objects that make up a single message. Parts of a message can have different MIME types. A Content message must have at least one Part.
+ { # A datatype containing media that is part of a multi-part Content message. A `Part` consists of data which has an associated datatype. A `Part` can only contain one of the accepted types in `Part.data`. For media types that are not text, `Part` must have a fixed IANA MIME type identifying the type and subtype of the media if `inline_data` or `file_data` field is filled with raw bytes.
+ "codeExecutionResult": { # Result of executing the ExecutableCode. Generated only when the `CodeExecution` tool is used. # Optional. The result of executing the ExecutableCode.
+ "outcome": "A String", # Required. Outcome of the code execution.
+ "output": "A String", # Optional. Contains stdout when code execution is successful, stderr or other description otherwise.
+ },
+ "executableCode": { # Code generated by the model that is meant to be executed, and the result returned to the model. Generated when using the `CodeExecution` tool, in which the code will be automatically executed, and a corresponding CodeExecutionResult will also be generated. # Optional. Code generated by the model that is intended to be executed.
+ "code": "A String", # Required. The code to be executed.
+ "language": "A String", # Required. Programming language of the `code`.
+ },
+ "fileData": { # URI-based data. A FileData message contains a URI pointing to data of a specific media type. It is used to represent images, audio, and video stored in Google Cloud Storage. # Optional. The URI-based data of the part. This can be used to include files from Google Cloud Storage.
+ "displayName": "A String", # Optional. The display name of the file. Used to provide a label or filename to distinguish files. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "fileUri": "A String", # Required. The URI of the file in Google Cloud Storage.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "functionCall": { # A predicted FunctionCall returned from the model that contains a string representing the FunctionDeclaration.name and a structured JSON object containing the parameters and their values. # Optional. A predicted function call returned from the model. This contains the name of the function to call and the arguments to pass to the function.
+ "args": { # Optional. The function parameters and values in JSON object format. See FunctionDeclaration.parameters for parameter details.
+ "a_key": "", # Properties of the object.
+ },
+ "name": "A String", # Optional. The name of the function to call. Matches FunctionDeclaration.name.
+ "partialArgs": [ # Optional. The partial argument value of the function call. If provided, represents the arguments/fields that are streamed incrementally.
+ { # Partial argument value of the function call.
+ "boolValue": True or False, # Optional. Represents a boolean value.
+ "jsonPath": "A String", # Required. A JSON Path (RFC 9535) to the argument being streamed. https://datatracker.ietf.org/doc/html/rfc9535. e.g. "$.foo.bar[0].data".
+ "nullValue": "A String", # Optional. Represents a null value.
+ "numberValue": 3.14, # Optional. Represents a double value.
+ "stringValue": "A String", # Optional. Represents a string value.
+ "willContinue": True or False, # Optional. Whether this is not the last part of the same json_path. If true, another PartialArg message for the current json_path is expected to follow.
+ },
+ ],
+ "willContinue": True or False, # Optional. Whether this is the last part of the FunctionCall. If true, another partial message for the current FunctionCall is expected to follow.
+ },
+ "functionResponse": { # The result output from a FunctionCall that contains a string representing the FunctionDeclaration.name and a structured JSON object containing any output from the function is used as context to the model. This should contain the result of a `FunctionCall` made based on model prediction. # Optional. The result of a function call. This is used to provide the model with the result of a function call that it predicted.
+ "name": "A String", # Required. The name of the function to call. Matches FunctionDeclaration.name and FunctionCall.name.
+ "parts": [ # Optional. Ordered `Parts` that constitute a function response. Parts may have different IANA MIME types.
+ { # A datatype containing media that is part of a `FunctionResponse` message. A `FunctionResponsePart` consists of data which has an associated datatype. A `FunctionResponsePart` can only contain one of the accepted types in `FunctionResponsePart.data`. A `FunctionResponsePart` must have a fixed IANA MIME type identifying the type and subtype of the media if the `inline_data` field is filled with raw bytes.
+ "fileData": { # URI based data for function response. # URI based data.
+ "displayName": "A String", # Optional. Display name of the file data. Used to provide a label or filename to distinguish file datas. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "fileUri": "A String", # Required. URI.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "inlineData": { # Raw media bytes for function response. Text should not be sent as raw bytes, use the 'text' field. # Inline media bytes.
+ "data": "A String", # Required. Raw bytes.
+ "displayName": "A String", # Optional. Display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in PromptMessage for prompt management. It is currently used in the Gemini GenerateContent calls only when server side tools (code_execution, google_search, and url_context) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ },
+ ],
+ "response": { # Required. The function response in JSON object format. Use "output" key to specify function output and "error" key to specify error details (if any). If "output" and "error" keys are not specified, then whole "response" is treated as function output.
+ "a_key": "", # Properties of the object.
+ },
+ "scheduling": "A String", # Optional. Specifies how the response should be scheduled in the conversation. Only applicable to NON_BLOCKING function calls, is ignored otherwise. Defaults to WHEN_IDLE.
+ },
+ "inlineData": { # A content blob. A Blob contains data of a specific media type. It is used to represent images, audio, and video. # Optional. The inline data content of the part. This can be used to include images, audio, or video in a request.
+ "data": "A String", # Required. The raw bytes of the data.
+ "displayName": "A String", # Optional. The display name of the blob. Used to provide a label or filename to distinguish blobs. This field is only returned in `PromptMessage` for prompt management. It is used in the Gemini calls only when server-side tools (`code_execution`, `google_search`, and `url_context`) are enabled.
+ "mimeType": "A String", # Required. The IANA standard MIME type of the source data.
+ },
+ "mediaResolution": { # per part media resolution. Media resolution for the input media. # per part media resolution. Media resolution for the input media.
+ "level": "A String", # The tokenization quality used for given media.
+ },
+ "text": "A String", # Optional. The text content of the part. When sent from the VSCode Gemini Code Assist extension, references to @mentioned items will be converted to markdown boldface text. For example `@my-repo` will be converted to and sent as `**my-repo**` by the IDE agent.
+ "thought": True or False, # Optional. Indicates whether the `part` represents the model's thought process or reasoning.
+ "thoughtSignature": "A String", # Optional. An opaque signature for the thought so it can be reused in subsequent requests.
+ "videoMetadata": { # Provides metadata for a video, including the start and end offsets for clipping and the frame rate. # Optional. Video metadata. The metadata should only be specified while the video data is presented in inline_data or file_data.
+ "endOffset": "A String", # Optional. The end offset of the video.
+ "fps": 3.14, # Optional. The frame rate of the video sent to the model. If not specified, the default value is 1.0. The valid range is (0.0, 24.0].
+ "startOffset": "A String", # Optional. The start offset of the video.
+ },
+ },
+ ],
+ "role": "A String", # Optional. The producer of the content. Must be either 'user' or 'model'. If not set, the service will default to 'user'.
+ },
+ "eventTime": "A String", # Optional. The timestamp when the event occurred.
+ "stateDelta": { # Optional. The change in the session state caused by this event. This is a key-value map of fields that were modified or added by the event.
+ "a_key": "", # Properties of the object.
+ },
+ },
+ ],
+ "turnId": "A String", # Optional. A unique identifier for the turn. Useful for referencing specific turns across systems.
+ "turnIndex": 42, # Required. The 0-based index of the turn in the conversation sequence.
+ },
+ ],
+ },
"promptTemplateData": { # Message to hold a prompt template and the values to populate the template. # Prompt template data.
"values": { # The values for fields in the prompt template.
"a_key": { # The structured data content of a message. A Content message contains a `role` field, which indicates the producer of the content, and a `parts` field, which contains the multi-part data of the message.
@@ -6253,6 +7941,10 @@ Method Details
},
},
"text": "A String", # Text prompt.
+ "userScenario": { # User scenario to help simulate multi-turn agent running results. # Optional. The generated user scenario used to drive multi-turn agent running results.
+ "conversationPlan": "A String", # Required. The plan for the conversation, used to drive the multi-turn agent run and generate the simulated agent evaluation dataset.
+ "startingPrompt": "A String", # Required. The prompt that starts the conversation between the simulated user and the agent under test.
+ },
"value": "", # Fields and values that can be used to populate the prompt template.
},
"rubrics": { # Optional. Named groups of rubrics associated with this prompt. The key is a user-defined name for the rubric group.
@@ -6519,7 +8211,7 @@ Method Details
The object takes the form of:
{ # Request message for DataFoundryService.GenerateUserScenarios.
- "agents": { # Required. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent.
+ "agents": { # Optional. A map containing the static configurations for each agent in the system. Key: agent_id (matches the `author` field in events). Value: The static configuration of the agent. Required unless `gemini_agent_config` is set, in which case the agents map and `root_agent_id` are derived from the referenced Gemini Agent.
"a_key": { # Represents configuration for an Agent.
"agentId": "A String", # Required. Unique identifier of the agent. This ID is used to refer to this agent, e.g., in AgentEvent.author, or in the `sub_agents` field. It must be unique within the `agents` map.
"agentType": "A String", # Optional. The type or class of the agent (e.g., "LlmAgent", "RouterAgent", "ToolUseAgent"). Useful for the autorater to understand the expected behavior of the agent.
@@ -6664,7 +8356,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -6756,7 +8449,7 @@ Method Details
},
},
"allowCrossRegionModel": True or False, # Optional. Allows the scenario generation to use cross region models. When this flag is set, the service may route traffic to other regions if a model is unavailable in the current region (e.g., to a `global` endpoint). If a fully-qualified model endpoint resource name with a different region than the request location is provided elsewhere in the request, this flag must be set to true or the request will fail.
- "rootAgentId": "A String", # Required. The agent id to identify the root agent.
+ "rootAgentId": "A String", # Optional. The agent id to identify the root agent. Required unless `gemini_agent_config` is set, in which case it is derived from the referenced Gemini Agent.
"userScenarioGenerationConfig": { # User scenario generation configuration. # Required. Configuration for generating user scenarios.
"environmentData": "A String", # Optional. Environment data in string type.
"modelName": "A String", # Optional. The model name to use for generation. It can be model name, e.g. "gemini-3-pro-preview". or the fully qualified name of the publisher model or endpoint. Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*` Endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
diff --git a/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.html b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.html
new file mode 100644
index 0000000000..869428ee88
--- /dev/null
+++ b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.html
@@ -0,0 +1,96 @@
+
+
+
+Agent Platform API . projects . locations . memoryBanks
+Instance Methods
+
+ memories()
+
+Returns the memories Resource.
+
+
+ operations()
+
+Returns the operations Resource.
+
+
+ close()
+Close httplib2 connections.
+Method Details
+
+ close()
+ Close httplib2 connections.
+
+
+
\ No newline at end of file
diff --git a/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.html b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.html
new file mode 100644
index 0000000000..880a6ad4d4
--- /dev/null
+++ b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.html
@@ -0,0 +1,143 @@
+
+
+
+Agent Platform API . projects . locations . memoryBanks . memories
+Instance Methods
+
+ operations()
+
+Returns the operations Resource.
+
+
+ close()
+Close httplib2 connections.
+
+Get a Memory.
+Method Details
+
+ close()
+ Close httplib2 connections.
+
+
+
+ get(name, x__xgafv=None)
+ Get a Memory.
+
+Args:
+ name: string, Required. The resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}` (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A memory.
+ "createTime": "A String", # Output only. Represents the timestamp when this Memory was created.
+ "description": "A String", # Optional. Represents the description of the Memory.
+ "disableMemoryRevisions": True or False, # Optional. Input only. Indicates whether no revision will be created for this request.
+ "displayName": "A String", # Optional. Represents the display name of the Memory.
+ "expireTime": "A String", # Optional. Represents the timestamp of when this resource is considered expired. This is *always* provided on output when `expiration` is set on input, regardless of whether `expire_time` or `ttl` was provided.
+ "fact": "A String", # Optional. Represents semantic knowledge extracted from the source content.
+ "metadata": { # Optional. Represents user-provided metadata for the Memory. This information was provided when creating, updating, or generating the Memory. It was not generated by Memory Bank.
+ "a_key": { # Memory metadata.
+ "boolValue": True or False, # Represents a boolean value.
+ "doubleValue": 3.14, # Represents a double value.
+ "stringValue": "A String", # Represents a string value.
+ "timestampValue": "A String", # Represents a timestamp value. When filtering on timestamp values, only the seconds field will be compared.
+ },
+ },
+ "name": "A String", # Identifier. Represents the resource name of the Memory. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}/memories/{memory}`
+ "revisionExpireTime": "A String", # Optional. Input only. Represents the timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.
+ "revisionLabels": { # Optional. Input only. Represents the labels to apply to the Memory Revision created as a result of this request.
+ "a_key": "A String",
+ },
+ "revisionTtl": "A String", # Optional. Input only. Represents the TTL for the revision. The expiration time is computed: now + TTL.
+ "scope": { # Required. Immutable. Represents the scope of the Memory. Memories are isolated within their scope. The scope is defined when creating or generating memories. Scope values cannot contain the wildcard character '*'.
+ "a_key": "A String",
+ },
+ "topics": [ # Optional. Represents the Topics of the Memory.
+ { # A memory topic identifier. This will be used to label a Memory and to restrict which topics are eligible for generation or retrieval.
+ "customMemoryTopicLabel": "A String", # Optional. Represents the custom memory topic label.
+ "managedMemoryTopic": "A String", # Optional. Represents the managed memory topic.
+ },
+ ],
+ "ttl": "A String", # Optional. Input only. Represents the TTL for this resource. The expiration time is computed: now + TTL.
+ "updateTime": "A String", # Output only. Represents the timestamp when this Memory was most recently updated.
+}
+
+
+
\ No newline at end of file
diff --git a/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.operations.html b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.operations.html
new file mode 100644
index 0000000000..f7830c0bf0
--- /dev/null
+++ b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.memories.operations.html
@@ -0,0 +1,272 @@
+
+
+
+Agent Platform API . projects . locations . memoryBanks . memories . operations
+Instance Methods
+
+Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+ close()
+Close httplib2 connections.
+
+Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Retrieves the next page of results.
+
+ wait(name, timeout=None, x__xgafv=None)
+Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+Method Details
+
+ cancel(name, x__xgafv=None)
+ Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+Args:
+ name: string, The name of the operation resource to be cancelled. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+
+
+
+ close()
+ Close httplib2 connections.
+
+
+
+ delete(name, x__xgafv=None)
+ Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation resource to be deleted. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+
+
+
+ get(name, x__xgafv=None)
+ Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+Args:
+ name: string, The name of the operation resource. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+ Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation's parent resource. (required)
+ filter: string, The standard list filter.
+ pageSize: integer, The standard list page size.
+ pageToken: string, The standard list page token.
+ returnPartialSuccess: boolean, When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `"projects/example/locations/-"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # The response message for Operations.ListOperations.
+ "nextPageToken": "A String", # The standard List next-page token.
+ "operations": [ # A list of operations that matches the specified filter in the request.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ },
+ ],
+ "unreachable": [ # Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.
+ "A String",
+ ],
+}
+
+
+
+ list_next()
+ Retrieves the next page of results.
+
+ Args:
+ previous_request: The request for the previous page. (required)
+ previous_response: The response from the request for the previous page. (required)
+
+ Returns:
+ A request object that you can call 'execute()' on to request the next
+ page. Returns None if there are no more items in the collection.
+
+
+
+
+ wait(name, timeout=None, x__xgafv=None)
+ Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+
+Args:
+ name: string, The name of the operation resource to wait on. (required)
+ timeout: string, The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+
+
\ No newline at end of file
diff --git a/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.operations.html b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.operations.html
new file mode 100644
index 0000000000..297420b2a1
--- /dev/null
+++ b/docs/dyn/aiplatform_v1.projects.locations.memoryBanks.operations.html
@@ -0,0 +1,272 @@
+
+
+
+Agent Platform API . projects . locations . memoryBanks . operations
+Instance Methods
+
+Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+ close()
+Close httplib2 connections.
+
+Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Retrieves the next page of results.
+
+ wait(name, timeout=None, x__xgafv=None)
+Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+Method Details
+
+ cancel(name, x__xgafv=None)
+ Starts asynchronous cancellation on a long-running operation. The server makes a best effort to cancel the operation, but success is not guaranteed. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Clients can use Operations.GetOperation or other methods to check whether the cancellation succeeded or whether the operation completed despite cancellation. On successful cancellation, the operation is not deleted; instead, it becomes an operation with an Operation.error value with a google.rpc.Status.code of `1`, corresponding to `Code.CANCELLED`.
+
+Args:
+ name: string, The name of the operation resource to be cancelled. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+
+
+
+ close()
+ Close httplib2 connections.
+
+
+
+ delete(name, x__xgafv=None)
+ Deletes a long-running operation. This method indicates that the client is no longer interested in the operation result. It does not cancel the operation. If the server doesn't support this method, it returns `google.rpc.Code.UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation resource to be deleted. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # A generic empty message that you can re-use to avoid defining duplicated empty messages in your APIs. A typical example is to use it as the request or the response type of an API method. For instance: service Foo { rpc Bar(google.protobuf.Empty) returns (google.protobuf.Empty); }
+}
+
+
+
+ get(name, x__xgafv=None)
+ Gets the latest state of a long-running operation. Clients can use this method to poll the operation result at intervals as recommended by the API service.
+
+Args:
+ name: string, The name of the operation resource. (required)
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+
+
+ list(name, filter=None, pageSize=None, pageToken=None, returnPartialSuccess=None, x__xgafv=None)
+ Lists operations that match the specified filter in the request. If the server doesn't support this method, it returns `UNIMPLEMENTED`.
+
+Args:
+ name: string, The name of the operation's parent resource. (required)
+ filter: string, The standard list filter.
+ pageSize: integer, The standard list page size.
+ pageToken: string, The standard list page token.
+ returnPartialSuccess: boolean, When set to `true`, operations that are reachable are returned as normal, and those that are unreachable are returned in the ListOperationsResponse.unreachable field. This can only be `true` when reading across collections. For example, when `parent` is set to `"projects/example/locations/-"`. This field is not supported by default and will result in an `UNIMPLEMENTED` error if set unless explicitly documented otherwise in service or product specific documentation.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # The response message for Operations.ListOperations.
+ "nextPageToken": "A String", # The standard List next-page token.
+ "operations": [ # A list of operations that matches the specified filter in the request.
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ },
+ ],
+ "unreachable": [ # Unordered list. Unreachable resources. Populated when the request sets `ListOperationsRequest.return_partial_success` and reads across collections. For example, when attempting to list all resources across all supported locations.
+ "A String",
+ ],
+}
+
+
+
+ list_next()
+ Retrieves the next page of results.
+
+ Args:
+ previous_request: The request for the previous page. (required)
+ previous_response: The response from the request for the previous page. (required)
+
+ Returns:
+ A request object that you can call 'execute()' on to request the next
+ page. Returns None if there are no more items in the collection.
+
+
+
+
+ wait(name, timeout=None, x__xgafv=None)
+ Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+
+Args:
+ name: string, The name of the operation resource to wait on. (required)
+ timeout: string, The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+
+
\ No newline at end of file
diff --git a/docs/dyn/aiplatform_v1.projects.locations.publishers.models.html b/docs/dyn/aiplatform_v1.projects.locations.publishers.models.html
index faf263ea05..1361cff7ef 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.publishers.models.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.publishers.models.html
@@ -675,7 +675,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -1443,7 +1444,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
@@ -2604,7 +2606,8 @@ Method Details
"customConfigs": { # Optional. Custom configs for ParallelAiSearch. This field can be used to pass any parameter from the Parallel.ai Search API. See the Parallel.ai documentation for the full list of available parameters and their usage: https://docs.parallel.ai/api-reference/search-beta/search Currently only `source_policy`, `excerpts`, `max_results`, `mode`, `fetch_policy` can be set via this field. For example: { "source_policy": { "include_domains": ["google.com", "wikipedia.org"], "exclude_domains": ["example.com"] }, "fetch_policy": { "max_age_seconds": 3600 } }
"a_key": "", # Properties of the object.
},
- "enableDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableDataRetention": True or False, # Optional. Deprecated: Use `enable_zero_data_retention` instead. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
+ "enableZeroDataRetention": True or False, # Optional. Instructs Vertex Grounding to use Parallel's Zero Data Retention Marketplace product. If this value is "false" or omitted, the Parallel Web Search for Grounding standard subscription will be used. If this value is "true", the Parallel Web Search for Grounding - ZDR subscription will be used.
},
"retrieval": { # Defines a retrieval tool that model can call to access external knowledge. # Optional. Retrieval tool type. System will always execute the provided retrieval tool(s) to get external knowledge to answer the prompt. Retrieval results are presented to the model for generation.
"disableAttribution": True or False, # Optional. Deprecated. This option is no longer supported.
diff --git a/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.html b/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.html
index 826016cca8..58f1da2464 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.html
@@ -365,6 +365,7 @@ Method Details
"eventCount": 42, # Optional. Specifies to trigger generation when the event count reaches this limit.
"fixedInterval": "A String", # Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.
"idleDuration": "A String", # Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity.
+ "overlapEventCount": 42, # Optional. Re-include the last N already-processed events in the next window.
},
},
"model": "A String", # Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.
@@ -396,6 +397,9 @@ Method Details
"name": "A String", # Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`
"spec": { # ReasoningEngine configurations # Optional. Configurations of the ReasoningEngine
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
+ "buildSpec": { # Specification for building container image. # Optional. Configuration for building container image.
+ "workerPool": "A String", # Optional. Identifier. The resource name of the Cloud Build WorkerPool to use for the build. Format: `projects/{project}/locations/{location}/workerPools/{worker_pool}`
+ },
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
@@ -751,6 +755,7 @@ Method Details
"eventCount": 42, # Optional. Specifies to trigger generation when the event count reaches this limit.
"fixedInterval": "A String", # Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.
"idleDuration": "A String", # Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity.
+ "overlapEventCount": 42, # Optional. Re-include the last N already-processed events in the next window.
},
},
"model": "A String", # Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.
@@ -782,6 +787,9 @@ Method Details
"name": "A String", # Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`
"spec": { # ReasoningEngine configurations # Optional. Configurations of the ReasoningEngine
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
+ "buildSpec": { # Specification for building container image. # Optional. Configuration for building container image.
+ "workerPool": "A String", # Optional. Identifier. The resource name of the Cloud Build WorkerPool to use for the build. Format: `projects/{project}/locations/{location}/workerPools/{worker_pool}`
+ },
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
@@ -1068,6 +1076,7 @@ Method Details
"eventCount": 42, # Optional. Specifies to trigger generation when the event count reaches this limit.
"fixedInterval": "A String", # Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.
"idleDuration": "A String", # Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity.
+ "overlapEventCount": 42, # Optional. Re-include the last N already-processed events in the next window.
},
},
"model": "A String", # Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.
@@ -1099,6 +1108,9 @@ Method Details
"name": "A String", # Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`
"spec": { # ReasoningEngine configurations # Optional. Configurations of the ReasoningEngine
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
+ "buildSpec": { # Specification for building container image. # Optional. Configuration for building container image.
+ "workerPool": "A String", # Optional. Identifier. The resource name of the Cloud Build WorkerPool to use for the build. Format: `projects/{project}/locations/{location}/workerPools/{worker_pool}`
+ },
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
@@ -1355,6 +1367,7 @@ Method Details
"eventCount": 42, # Optional. Specifies to trigger generation when the event count reaches this limit.
"fixedInterval": "A String", # Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.
"idleDuration": "A String", # Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity.
+ "overlapEventCount": 42, # Optional. Re-include the last N already-processed events in the next window.
},
},
"model": "A String", # Optional. The model used to generate memories. Format: `projects/{project}/locations/{location}/publishers/google/models/{model}`.
@@ -1386,6 +1399,9 @@ Method Details
"name": "A String", # Identifier. The resource name of the ReasoningEngine. Format: `projects/{project}/locations/{location}/reasoningEngines/{reasoning_engine}`
"spec": { # ReasoningEngine configurations # Optional. Configurations of the ReasoningEngine
"agentFramework": "A String", # Optional. The OSS agent framework used to develop the agent. Currently supported values: "google-adk", "langchain", "langgraph", "ag2", "llama-index", "custom".
+ "buildSpec": { # Specification for building container image. # Optional. Configuration for building container image.
+ "workerPool": "A String", # Optional. Identifier. The resource name of the Cloud Build WorkerPool to use for the build. Format: `projects/{project}/locations/{location}/workerPools/{worker_pool}`
+ },
"classMethods": [ # Optional. Declarations for object class methods in OpenAPI specification format.
{
"a_key": "", # Properties of the object.
diff --git a/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.memories.html b/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.memories.html
index 75509ee8de..13986f9825 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.memories.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.reasoningEngines.memories.html
@@ -539,14 +539,30 @@ Method Details
},
],
},
+ "disableMemoryRevisions": True or False, # Optional. If true, no revisions will be created for this request.
"forceFlush": True or False, # Optional. Forces a flush of all pending events in the stream and triggers memory generation immediately bypassing any conditions configured in the `generation_trigger_config`.
"generationTriggerConfig": { # Represents configuration for triggering generation. # Optional. Configuration for triggering memory generation from this ingestion. If not set, then the stream will be force flushed immediately.
"generationRule": { # Represents the active rule that determines when to flush the buffer. # Optional. Represents the active rule that determines when to flush the buffer. If not set, then the stream will be force flushed immediately.
"eventCount": 42, # Optional. Specifies to trigger generation when the event count reaches this limit.
"fixedInterval": "A String", # Optional. Specifies to trigger generation at a fixed interval. The duration must have a minute-level granularity.
"idleDuration": "A String", # Optional. Specifies to trigger generation if the stream is inactive for the specified duration after the most recent event. The duration must have a minute-level granularity.
+ "overlapEventCount": 42, # Optional. Re-include the last N already-processed events in the next window.
},
},
+ "metadata": { # Optional. User-provided metadata for the generated memories. This is not generated by Memory Bank.
+ "a_key": { # Memory metadata.
+ "boolValue": True or False, # Represents a boolean value.
+ "doubleValue": 3.14, # Represents a double value.
+ "stringValue": "A String", # Represents a string value.
+ "timestampValue": "A String", # Represents a timestamp value. When filtering on timestamp values, only the seconds field will be compared.
+ },
+ },
+ "metadataMergeStrategy": "A String", # Optional. The strategy to use when applying metadata to existing memories.
+ "revisionExpireTime": "A String", # Optional. Timestamp of when the revision is considered expired. If not set, the memory revision will be kept until manually deleted.
+ "revisionLabels": { # Optional. Labels to be applied to the generated memory revisions. For example, you can use this to label a revision with its data source.
+ "a_key": "A String",
+ },
+ "revisionTtl": "A String", # Optional. The TTL for the revision. The expiration time is computed: now + TTL.
"scope": { # Required. The scope of the memories that should be generated from the stream. Memories will be consolidated across memories with the same scope. Scope values cannot contain the wildcard character '*'.
"a_key": "A String",
},
diff --git a/docs/dyn/aiplatform_v1.projects.locations.tuningJobs.operations.html b/docs/dyn/aiplatform_v1.projects.locations.tuningJobs.operations.html
index b889e0b157..d87dbfa0a1 100644
--- a/docs/dyn/aiplatform_v1.projects.locations.tuningJobs.operations.html
+++ b/docs/dyn/aiplatform_v1.projects.locations.tuningJobs.operations.html
@@ -92,6 +92,9 @@ Instance Methods
Retrieves the next page of results.
+
+ wait(name, timeout=None, x__xgafv=None)
+Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
Method Details
cancel(name, x__xgafv=None)
@@ -230,4 +233,40 @@ Method Details
+
+ wait(name, timeout=None, x__xgafv=None)
+ Waits until the specified long-running operation is done or reaches at most a specified timeout, returning the latest state. If the operation is already done, the latest state is immediately returned. If the timeout specified is greater than the default HTTP/RPC timeout, the HTTP/RPC timeout is used. If the server does not support this method, it returns `google.rpc.Code.UNIMPLEMENTED`. Note that this method is on a best-effort basis. It may return the latest state before the specified timeout (including immediately), meaning even an immediate response is no guarantee that the operation is done.
+
+Args:
+ name: string, The name of the operation resource to wait on. (required)
+ timeout: string, The maximum duration to wait before timing out. If left blank, the wait will be at most the time permitted by the underlying HTTP/RPC protocol. If RPC context deadline is also specified, the shorter one will be used.
+ x__xgafv: string, V1 error format.
+ Allowed values
+ 1 - v1 error format
+ 2 - v2 error format
+
+Returns:
+ An object of the form:
+
+ { # This resource represents a long-running operation that is the result of a network API call.
+ "done": True or False, # If the value is `false`, it means the operation is still in progress. If `true`, the operation is completed, and either `error` or `response` is available.
+ "error": { # The `Status` type defines a logical error model that is suitable for different programming environments, including REST APIs and RPC APIs. It is used by [gRPC](https://github.com/grpc). Each `Status` message contains three pieces of data: error code, error message, and error details. You can find out more about this error model and how to work with it in the [API Design Guide](https://cloud.google.com/apis/design/errors). # The error result of the operation in case of failure or cancellation.
+ "code": 42, # The status code, which should be an enum value of google.rpc.Code.
+ "details": [ # A list of messages that carry the error details. There is a common set of message types for APIs to use.
+ {
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ ],
+ "message": "A String", # A developer-facing error message, which should be in English. Any user-facing error message should be localized and sent in the google.rpc.Status.details field, or localized by the client.
+ },
+ "metadata": { # Service-specific metadata associated with the operation. It typically contains progress information and common metadata such as create time. Some services might not provide such metadata. Any method that returns a long-running operation should document the metadata type, if any.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+ "name": "A String", # The server-assigned name, which is only unique within the same service that originally returns it. If you use the default HTTP mapping, the `name` should be a resource name ending with `operations/{unique_id}`.
+ "response": { # The normal, successful response of the operation. If the original method returns no data on success, such as `Delete`, the response is `google.protobuf.Empty`. If the original method is standard `Get`/`Create`/`Update`, the response should be the resource. For other methods, the response should have the type `XxxResponse`, where `Xxx` is the original method name. For example, if the original method name is `TakeSnapshot()`, the inferred response type is `TakeSnapshotResponse`.
+ "a_key": "", # Properties of the object. Contains field @type with type URL.
+ },
+}
+
+