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Register an ASR multimodal processor on GraniteSwitchForCausalLM: audio is transcribed and a <|audio|> marker is replaced with the transcript tokens (PromptReplacement), so the scheduler sizes KV for the real length. The model's embed_multimodal supplies those positions' embeddings via the token table (the seam a future trained audio encoder will reuse), and embed_input_ids scatters them. Audio capability is gated per-checkpoint by config.asr_enabled. Alpha scope: audio runs on the base model (no adapter control-token handling). Signed-off-by: aviv ron <rona@il.ibm.com>
Signed-off-by: aviv ron <rona@il.ibm.com>
New --enable-audio / --asr-model / --asr-device flags. When audio is enabled the composer adds the <|audio|> marker token (before the embedding resize) and writes asr_enabled / asr_model_id / asr_device into the checkpoint config, so the vLLM backend's gated audio processor activates for that checkpoint. Signed-off-by: aviv ron <rona@il.ibm.com>
Signed-off-by: aviv ron <rona@il.ibm.com>
tests/unit/test_asr.py: CPU-tier unit coverage for the ASR backend (audio coercion, mono/resample, lazy-load, transcribe with mocked pipeline); loads the leaf module by path so it runs without the vLLM extra. docs/AUDIO.md: how to compose --enable-audio, call it (Python + OpenAI server), the cascade design and the future-encoder seam, and alpha limitations. Signed-off-by: aviv ron <rona@il.ibm.com>
…ate work) Signed-off-by: aviv ron <rona@il.ibm.com>
The Granite content-part loop only handled type=='text' and dropped audio parts, so chat/OpenAI-server requests rendered without the <|audio|> marker and prompt replacement failed. Add configure_audio_chat_template(): injects an elif that appends the marker for any part whose type contains 'audio' (covers audio / input_audio / audio_url). Called during compose when audio is enabled. Signed-off-by: aviv ron <rona@il.ibm.com>
Signed-off-by: aviv ron <rona@il.ibm.com>
Set requires_raw_input_tokens=True so vLLM passes raw input_ids to forward on the multimodal path, letting the switch detect adapter control tokens for audio requests. embed_input_ids now applies the switch's token-exchange rewrite (control -> substitute id) via a new SingleSwitch.apply_token_exchange helper, so control tokens get in-distribution embeddings exactly as on the text path. Signed-off-by: aviv ron <rona@il.ibm.com>
Signed-off-by: aviv ron <rona@il.ibm.com>
…errides in config Signed-off-by: aviv ron <rona@il.ibm.com>
Remove the two hard caps in the audio cascade and add an encoder-agnostic long-audio chunker: 1. Multiple clips per request. get_supported_mm_limits is now a configurable ceiling (asr_max_audio_clips, default 32) instead of a hardcoded 1; each clip's transcript is spliced at its own <|audio|> marker (the splice loop already supported N). For the cascade the clips cost no extra KV (transcripts are ordinary text tokens bounded by the context); the ceiling exists to bound the per-request synchronous-ASR work and the startup profiling pass. 2. Context-derived transcript budget. The fixed 2048-token cap is replaced by audio_token_budget() = (context - generation_reserve - prompt) / clips, floored at 1. get_mm_max_tokens_per_item derives from the seq_len vLLM passes; _call_hf_processor reads the served max_model_len and subtracts the actual prompt. New asr_generation_reserve_tokens (default 8192). 3. Encoder-agnostic chunker (chunking.py): split_waveform + merge_transcripts (word-level overlap de-dup). ASRTranscriber.transcribe gains a self_chunks flag: Whisper (self_chunks=True) keeps its internal timestamp stitching; backends with a fixed input window route through our split/transcribe/merge. New config: asr_self_chunks, asr_chunk_length_s, asr_chunk_overlap_s. Compose CLI flags and docs/AUDIO.md updated. Tests: new test_chunking.py; budget and chunked-path tests in test_asr.py; config round-trip/validation in test_config.py; multi-clip, budget, and flag-forwarding in test_audio_processor.py. Already-composed checkpoints inherit the new behavior via getattr defaults; no re-compose required (only self_chunks=False needs a config change). Signed-off-by: aviv ron <rona@il.ibm.com>
Add support for adapter switching and configurable encoders Signed-off-by: Aviv Ron <rona@il.ibm.com>
# Conflicts: # src/granite_switch/config.py # src/granite_switch/vllm/granite_switch_model.py # src/granite_switch/vllm/switch/single.py # tutorials/notebooks/granite_speech_demo.ipynb Signed-off-by: aviv ron <rona@il.ibm.com>
GraniteSwitchForCausalLM.embed_input_ids annotated is_multimodal as Optional[torch.Tensor], but the module never imports Optional. The NameError fires at class-definition time, so `import granite_switch.vllm` raises and vLLM's plugin loader silently skips the entry point. The architecture is then never registered with transformers, and any attempt to serve a granite_switch checkpoint fails with "Transformers does not recognize this architecture". Use the module's prevailing PEP 604 style (torch.Tensor | None) instead of adding a typing import. Signed-off-by: aviv ron <rona@il.ibm.com>
…check (#45) (#109) The audio cascade truncated the transcript to a context-derived per-clip budget (asr_generation_reserve_tokens held back for the answer). When that reserve met or exceeded the served max_model_len, the budget floored to 1 token: the model saw no question and refused, with no error (#45). Rather than patch the truncation math, remove it. The transcript is now spliced into the prompt in full, as ordinary text tokens. A request whose prompt + transcript(s) can't leave room for the answer within max_model_len is rejected by vLLM's standard prompt-length check (HTTP 400) — the same loud failure text-only requests already get, instead of a silent 1-token transcript. This also makes audio behave identically to long text. Details: - Remove asr_generation_reserve_tokens entirely (config field + validation, compose CLI flag, processor accessor). It only existed to size the old truncation budget. - Drop the budget param / ids[:budget] truncation in the processor; splice the full transcript. - get_mm_max_tokens_per_item now reports max(1, seq_len // count) — the honest worst-case transcript positions one clip can occupy. This still sizes vLLM's encoder cache correctly (embed_multimodal emits one row per transcript token); it is a profiling hint, not a request bound. - Remove the now-dead audio_token_budget helper and its tests. Tests updated; docs/AUDIO.md rewritten to describe reject-not-truncate. Co-authored-by: aviv ron <rona@il.ibm.com> Signed-off-by: Bar Haim <barha@il.ibm.com>
Signed-off-by: aviv ron <rona@il.ibm.com>
* tests: cover audio/adapter coexistence, chat-template marker, empty clips, clip ceiling Signed-off-by: BAR HAIM <barha@il.ibm.com> * tests: add e2e vLLM audio serving smoke (text + adapter + audio x1/x2/x3) CI-runnable serving smoke closing the #47 e2e box. Boots a real composed, audio-enabled GraniteSwitch checkpoint under vLLM and drives text-only, adapter-control-token, and audio x1/x2/x3 requests through one live engine. Markers slow+requires_model+gpu (opt-in via -m); model built through the compose CLI with --enable-audio; synthetic audio keeps it asset-free. Verified green on an A100 with ibm-granite/granite-4.1-3b + granitelib-core-r1.0: 5 passed. Signed-off-by: BAR HAIM <barha@il.ibm.com> * tests: e2e answerability adapter over an audio-delivered document (#47) Adds the first correctness test for the "adapters + audio together" #47 box: the RAG answerability adapter judging a query against a document supplied as speech rather than text. The document is delivered as audio by placing a single <|audio|> marker as the document text (documents=[{"text": "<|audio|>"}]); the Granite template renders each document via `doc | tojson`, so the marker lands in the <documents> block exactly where vLLM's ASR processor splices the transcript — the document the adapter reasons over is the transcribed speech. The <|answerability|> control token is inserted by the same template (aLoRA fallback path), so the switch fires the adapter at the generation prompt. Ground truth comes from one real clip (hf-internal-testing/ librispeech_asr_dummy row 0), driving both classes without shipping a fixture: an answerable question whose answer is spoken, and an unanswerable one about content the clip never mentions. Both are distinctive enough to survive ASR word-errors, so the assertion tests the answerability decision, not transcription accuracy (WER is a separate box). FLAC is decoded with soundfile from the raw bytes to avoid requiring torchcodec (datasets>=4). Where test_audio_serving_smoke.py only proves an adapter control token doesn't crash the audio path, this proves the switch produces the correct verdict end-to-end through a live vLLM engine. Verified on an A100 with granite-4.1-3b + granitelib-rag-r1.0: 2 passed. Markers slow+requires_model+gpu; opt-in via pytest -m "slow and requires_model and gpu" Signed-off-by: BAR HAIM <barha@il.ibm.com> * tests: use committed local speech clip for answerability-over-audio Replace the runtime hf-internal-testing/librispeech_asr_dummy download with a committed 3s 16 kHz WAV (SpeechT5, MIT-licensed) so the test runs offline and carries clean provenance for merge-to-main. The spoken sentence states a location that distil-whisper transcribes cleanly, so the questions key on the location rather than the proper noun. Verdicts verified: 2 passed on A100 (granite-4.1-3b + granitelib-rag-r1.0). Signed-off-by: BAR HAIM <barha@il.ibm.com> * tests: sweep all default adapters route correctly with audio enabled Adds the 'all default adapters route correctly with audio enabled' coverage for issue #47. Composes the full default set (RAG + Core + Guardian) with --enable-audio and asserts the switch maps each adapter_token_ids[i] to index i+1 (pre-control positions stay on base 0), observed via the HF backend's _last_adapter_indices. For granite-4.1-3b, 12 adapters resolve (context_relevance has no 4.1-3b flavor); verified 12/12 route correctly on A100. Loads with ignore_mismatched_sizes=True: the <|audio|> token bumps vocab_size one past the switch's control_to_substitute_lut buffer, which SingleSwitch rebuilds from config, so the freshly-built buffer is kept. Signed-off-by: BAR HAIM <barha@il.ibm.com> --------- Signed-off-by: BAR HAIM <barha@il.ibm.com>
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