9 commits

Author	SHA1	Message	Date
Ashwin Bharambe	7519b73fcc	feat(distro): fork off a starter-gpu distribution (#3240) ... The starter distribution added post-training which added torch dependencies which pulls in all the nvidia CUDA libraries. This made our starter container very big. We have worked hard to keep the starter container small so it serves its purpose as a starter. This PR tries to get it back to its size by forking off duplicate "-gpu" providers for post-training. These forked providers are then used for a new `starter-gpu` distribution which can pull in all dependencies.	2025-08-22 15:47:15 -07:00
slekkala1	7519ab4024	feat: Code scanner Provider impl for moderations api (#3100) ... # What does this PR do? Add CodeScanner implementations ## Test Plan `SAFETY_MODEL=CodeScanner LLAMA_STACK_CONFIG=starter uv run pytest -v tests/integration/safety/test_safety.py --text-model=llama3.2:3b-instruct-fp16 --embedding-model=all-MiniLM-L6-v2 --safety-shield=ollama` This PR need to land after this https://github.com/meta-llama/llama-stack/pull/3098	2025-08-18 14:15:40 -07:00
Matthew Farrellee	914c7be288	feat: add batches API with OpenAI compatibility (with inference replay) (#3162) ... Add complete batches API implementation with protocol, providers, and tests: Core Infrastructure: - Add batches API protocol using OpenAI Batch types directly - Add Api.batches enum value and protocol mapping in resolver - Add OpenAI "batch" file purpose support - Include proper error handling (ConflictError, ResourceNotFoundError) Reference Provider: - Add ReferenceBatchesImpl with full CRUD operations (create, retrieve, cancel, list) - Implement background batch processing with configurable concurrency - Add SQLite KVStore backend for persistence - Support /v1/chat/completions endpoint with request validation Comprehensive Test Suite: - Add unit tests for provider implementation with validation - Add integration tests for end-to-end batch processing workflows - Add error handling tests for validation, malformed inputs, and edge cases Configuration: - Add max_concurrent_batches and max_concurrent_requests_per_batch options - Add provider documentation with sample configurations Test with - ``` $ uv run llama stack build --image-type venv --providers inference=YOU_PICK,files=inline::localfs,batches=inline::reference --run & $ LLAMA_STACK_CONFIG=http://localhost:8321 uv run pytest tests/unit/providers/batches tests/integration/batches --text-model YOU_PICK ``` addresses #3066 --------- Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>	2025-08-15 15:34:15 -07:00
Chacksu	fffdab4f5c	fix: Dell distribution missing kvstore (#3113) ... # What does this PR do? - Added kvstore config to ChromaDB provider config for Dell distribution similar to [starter config](https://github.com/meta-llama/llama-stack/blob/main/llama_stack/distributions/starter/run.yaml#L110-L112) - Fixed [error](https://github.com/huggingface/huggingface_hub/blob/main/src/huggingface_hub/inference/_generated/_async_client.py#L3424-L3425) getting endpoint information by adding `hf-inference` as the provider to the `AsyncInferenceClient` (TGI client). ## Test Plan ``` export INFERENCE_PORT=8181 export DEH_URL=http://0.0.0.0:$INFERENCE_PORT export INFERENCE_MODEL=meta-llama/Llama-3.2-3B-Instruct export CHROMADB_HOST=localhost export CHROMADB_PORT=8000 export CHROMA_URL=http://$CHROMADB_HOST:$CHROMADB_PORT export CUDA_VISIBLE_DEVICES=0 export LLAMA_STACK_PORT=8321 export HF_TOKEN=[redacted] # TGI Server docker run --rm -it \ --pull always \ --network host \ -v $HOME/.cache/huggingface:/data \ -e HF_TOKEN=$HF_TOKEN \ -e PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True \ -p $INFERENCE_PORT:$INFERENCE_PORT \ --gpus all \ ghcr.io/huggingface/text-generation-inference:latest \ --dtype float16 \ --usage-stats off \ --sharded false \ --cuda-memory-fraction 0.8 \ --model-id meta-llama/Llama-3.2-3B-Instruct \ --port $INFERENCE_PORT \ --hostname 0.0.0.0 # Chrome DB docker run --rm -it \ --name chromadb \ --net=host -p 8000:8000 \ -v ~/chroma:/chroma/chroma \ -e IS_PERSISTENT=TRUE \ -e ANONYMIZED_TELEMETRY=FALSE \ chromadb/chroma:latest # Llama Stack llama stack run dell \ --port $LLAMA_STACK_PORT \ --env INFERENCE_MODEL=$INFERENCE_MODEL \ --env DEH_URL=$DEH_URL \ --env CHROMA_URL=$CHROMA_URL ``` --------- Co-authored-by: Connor Hack <connorhack@fb.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>	2025-08-13 06:18:25 -07:00
Eran Cohen	a4bad6c0b4	feat: Add Google Vertex AI inference provider support (#2841) ... # What does this PR do? - Add new Vertex AI remote inference provider with litellm integration - Support for Gemini models through Google Cloud Vertex AI platform - Uses Google Cloud Application Default Credentials (ADC) for authentication - Added VertexAI models: gemini-2.5-flash, gemini-2.5-pro, gemini-2.0-flash. - Updated provider registry to include vertexai provider - Updated starter template to support Vertex AI configuration - Added comprehensive documentation and sample configuration <!-- If resolving an issue, uncomment and update the line below --> relates to https://github.com/meta-llama/llama-stack/issues/2747 ## Test Plan <!-- Describe the tests you ran to verify your changes with result summaries. *Provide clear instructions so the plan can be easily re-executed.* --> Signed-off-by: Eran Cohen <eranco@redhat.com> Co-authored-by: Francisco Arceo <arceofrancisco@gmail.com>	2025-08-11 08:22:04 -04:00
Jiayi Ni	9e78f2da96	docs: fix the docs for NVIDIA Inference Provider (#3055) ... # What does this PR do? Fix the NVIDIA inference docs by updating API methods, model IDs, and embedding example. ## Test Plan N/A	2025-08-08 11:27:55 +02:00
ehhuang	3e695cf320	chore: update postgres_demo with new config (#3045) ... # What does this PR do? closes https://github.com/meta-llama/llama-stack/issues/3044 ## Test Plan matches starter's template	2025-08-06 07:48:40 -07:00
Ashwin Bharambe	7f834339ba	chore(misc): make tests and starter faster (#3042) ... A bunch of miscellaneous cleanup focusing on tests, but ended up speeding up starter distro substantially. - Pulled llama stack client init for tests into `pytest_sessionstart` so it does not clobber output - Profiling of that told me where we were doing lots of heavy imports for starter, so lazied them - starter now starts 20seconds+ faster on my Mac - A few other smallish refactors for `compat_client`	2025-08-05 14:55:05 -07:00
Ashwin Bharambe	cc87995e2b	chore: rename templates to distributions (#3035) ... As the title says. Distributions is in, Templates is out. `llama stack build --template` --> `llama stack build --distro`. For backward compatibility, the previous option is kept but results in a warning. Updated `server.py` to remove the "config_or_template" backward compatibility since it has been a couple releases since that change.	2025-08-04 11:34:17 -07:00