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# What does this PR do? This PR updates the inline vLLM inference provider in several significant ways: * Models are now attached at run time to instances of the provider via the `.../models` API instead of hard-coding the model's full name into the provider's YAML configuration. * The provider supports models that are not Meta Llama models. Any model that vLLM supports can be loaded by passing Huggingface coordinates in the "provider_model_id" field. Custom fine-tuned versions of Meta Llama models can be loaded by specifying a path on local disk in the "provider_model_id". * To implement full chat completions support, including tool calling and constrained decoding, the provider now routes the `chat_completions` API to a captive (i.e. called directly in-process, not via HTTPS) instance of vLLM's OpenAI-compatible server . * The `logprobs` parameter and completions API are also working. ## Test Plan Existing tests in `llama_stack/providers/tests/inference/test_text_inference.py` have good coverage of the new functionality. These tests can be invoked as follows: ``` cd llama-stack && pytest \ -vvv \ llama_stack/providers/tests/inference/test_text_inference.py \ --providers inference=vllm \ --inference-model meta-llama/Llama-3.2-3B-Instruct ====================================== test session starts ====================================== platform linux -- Python 3.12.8, pytest-8.3.4, pluggy-1.5.0 -- /mnt/datadisk1/freiss/llama/env/bin/python3.12 cachedir: .pytest_cache metadata: {'Python': '3.12.8', 'Platform': 'Linux-6.8.0-1016-ibm-x86_64-with-glibc2.39', 'Packages': {'pytest': '8.3.4', 'pluggy': '1.5.0'}, 'Plugins': {'anyio': '4.8.0', 'html': '4.1.1', 'metadata': '3.1.1', 'asyncio': '0.25.2'}, 'JAVA_HOME': '/usr/lib/jvm/java-8-openjdk-amd64'} rootdir: /mnt/datadisk1/freiss/llama/llama-stack configfile: pyproject.toml plugins: anyio-4.8.0, html-4.1.1, metadata-3.1.1, asyncio-0.25.2 asyncio: mode=Mode.STRICT, asyncio_default_fixture_loop_scope=None collected 9 items llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_model_list[-vllm] PASSED [ 11%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion[-vllm] PASSED [ 22%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_logprobs[-vllm] PASSED [ 33%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_completion_structured_output[-vllm] PASSED [ 44%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_non_streaming[-vllm] PASSED [ 55%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_structured_output[-vllm] PASSED [ 66%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_streaming[-vllm] PASSED [ 77%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling[-vllm] PASSED [ 88%] llama_stack/providers/tests/inference/test_text_inference.py::TestInference::test_chat_completion_with_tool_calling_streaming[-vllm] PASSED [100%] =========================== 9 passed, 13 warnings in 97.18s (0:01:37) =========================== ``` ## Sources ## Before submitting - [X] Ran pre-commit to handle lint / formatting issues. - [X] Read the [contributor guideline](https://github.com/meta-llama/llama-stack/blob/main/CONTRIBUTING.md), Pull Request section? - [ ] Updated relevant documentation. - [ ] Wrote necessary unit or integration tests. --------- Co-authored-by: Sébastien Han <seb@redhat.com> Co-authored-by: Ashwin Bharambe <ashwin.bharambe@gmail.com>
122 lines
3.2 KiB
YAML
122 lines
3.2 KiB
YAML
version: '2'
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image_name: vllm-gpu
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apis:
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- agents
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- datasetio
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- eval
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- inference
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- safety
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- scoring
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- telemetry
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- tool_runtime
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- vector_io
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providers:
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inference:
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- provider_id: vllm
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provider_type: inline::vllm
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config:
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tensor_parallel_size: ${env.TENSOR_PARALLEL_SIZE:1}
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max_tokens: ${env.MAX_TOKENS:4096}
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max_model_len: ${env.MAX_MODEL_LEN:4096}
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max_num_seqs: ${env.MAX_NUM_SEQS:4}
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enforce_eager: ${env.ENFORCE_EAGER:False}
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gpu_memory_utilization: ${env.GPU_MEMORY_UTILIZATION:0.3}
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- provider_id: sentence-transformers
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provider_type: inline::sentence-transformers
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config: {}
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vector_io:
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- provider_id: faiss
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provider_type: inline::faiss
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config:
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kvstore:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/vllm-gpu}/faiss_store.db
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safety:
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- provider_id: llama-guard
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provider_type: inline::llama-guard
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config: {}
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agents:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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persistence_store:
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type: sqlite
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namespace: null
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/vllm-gpu}/agents_store.db
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telemetry:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config:
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service_name: ${env.OTEL_SERVICE_NAME:llama-stack}
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sinks: ${env.TELEMETRY_SINKS:console,sqlite}
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sqlite_db_path: ${env.SQLITE_DB_PATH:~/.llama/distributions/vllm-gpu/trace_store.db}
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eval:
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- provider_id: meta-reference
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provider_type: inline::meta-reference
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config: {}
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datasetio:
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- provider_id: huggingface
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provider_type: remote::huggingface
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config: {}
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- provider_id: localfs
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provider_type: inline::localfs
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config: {}
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scoring:
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- provider_id: basic
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provider_type: inline::basic
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config: {}
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- provider_id: llm-as-judge
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provider_type: inline::llm-as-judge
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config: {}
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- provider_id: braintrust
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provider_type: inline::braintrust
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config:
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openai_api_key: ${env.OPENAI_API_KEY:}
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tool_runtime:
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- provider_id: brave-search
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provider_type: remote::brave-search
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config:
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api_key: ${env.BRAVE_SEARCH_API_KEY:}
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max_results: 3
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- provider_id: tavily-search
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provider_type: remote::tavily-search
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config:
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api_key: ${env.TAVILY_SEARCH_API_KEY:}
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max_results: 3
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- provider_id: code-interpreter
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provider_type: inline::code-interpreter
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config: {}
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- provider_id: rag-runtime
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provider_type: inline::rag-runtime
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config: {}
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- provider_id: model-context-protocol
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provider_type: remote::model-context-protocol
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config: {}
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metadata_store:
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type: sqlite
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db_path: ${env.SQLITE_STORE_DIR:~/.llama/distributions/vllm-gpu}/registry.db
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models:
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- metadata: {}
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model_id: ${env.INFERENCE_MODEL}
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provider_id: vllm
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model_type: llm
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- metadata:
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embedding_dimension: 384
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model_id: all-MiniLM-L6-v2
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provider_id: sentence-transformers
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model_type: embedding
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shields: []
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vector_dbs: []
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datasets: []
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scoring_fns: []
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benchmarks: []
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tool_groups:
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- toolgroup_id: builtin::websearch
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provider_id: tavily-search
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- toolgroup_id: builtin::rag
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provider_id: rag-runtime
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- toolgroup_id: builtin::code_interpreter
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provider_id: code-interpreter
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server:
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port: 8321
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