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# What does this PR do? Allows passing through extra_body parameters to inference providers. With this, we removed the 2 vllm-specific parameters from completions API into `extra_body`. Before/After <img width="1883" height="324" alt="image" src="https://github.com/user-attachments/assets/acb27c08-c748-46c9-b1da-0de64e9908a1" /> closes #2720 ## Test Plan CI and added new test ``` ❯ uv run pytest -s -v tests/integration/ --stack-config=server:starter --inference-mode=record -k 'not( builtin_tool or safety_with_image or code_interpreter or test_rag ) and test_openai_completion_guided_choice' --setup=vllm --suite=base --color=yes Uninstalled 3 packages in 125ms Installed 3 packages in 19ms INFO 2025-10-10 14:29:54,317 tests.integration.conftest:118 tests: Applying setup 'vllm' for suite base INFO 2025-10-10 14:29:54,331 tests.integration.conftest:47 tests: Test stack config type: server (stack_config=server:starter) ============================================================================================================== test session starts ============================================================================================================== platform darwin -- Python 3.12.11, pytest-8.4.2, pluggy-1.6.0 -- /Users/erichuang/projects/llama-stack-1/.venv/bin/python cachedir: .pytest_cache metadata: {'Python': '3.12.11', 'Platform': 'macOS-15.6.1-arm64-arm-64bit', 'Packages': {'pytest': '8.4.2', 'pluggy': '1.6.0'}, 'Plugins': {'anyio': '4.9.0', 'html': '4.1.1', 'socket': '0.7.0', 'asyncio': '1.1.0', 'json-report': '1.5.0', 'timeout': '2.4.0', 'metadata': '3.1.1', 'cov': '6.2.1', 'nbval': '0.11.0'}} rootdir: /Users/erichuang/projects/llama-stack-1 configfile: pyproject.toml plugins: anyio-4.9.0, html-4.1.1, socket-0.7.0, asyncio-1.1.0, json-report-1.5.0, timeout-2.4.0, metadata-3.1.1, cov-6.2.1, nbval-0.11.0 asyncio: mode=Mode.AUTO, asyncio_default_fixture_loop_scope=None, asyncio_default_test_loop_scope=function collected 285 items / 284 deselected / 1 selected tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B] instantiating llama_stack_client Starting llama stack server with config 'starter' on port 8321... Waiting for server at http://localhost:8321... (0.0s elapsed) Waiting for server at http://localhost:8321... (0.5s elapsed) Waiting for server at http://localhost:8321... (5.1s elapsed) Waiting for server at http://localhost:8321... (5.6s elapsed) Waiting for server at http://localhost:8321... (10.1s elapsed) Waiting for server at http://localhost:8321... (10.6s elapsed) Server is ready at http://localhost:8321 llama_stack_client instantiated in 11.773s PASSEDTerminating llama stack server process... Terminating process 98444 and its group... Server process and children terminated gracefully ============================================================================================================= slowest 10 durations ============================================================================================================== 11.88s setup tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B] 3.02s call tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B] 0.01s teardown tests/integration/inference/test_openai_completion.py::test_openai_completion_guided_choice[txt=vllm/Qwen/Qwen3-0.6B] ================================================================================================ 1 passed, 284 deselected, 3 warnings in 16.21s ================================================================================================= ```
145 lines
4.5 KiB
Python
145 lines
4.5 KiB
Python
# Copyright (c) Meta Platforms, Inc. and affiliates.
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# All rights reserved.
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#
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# This source code is licensed under the terms described in the LICENSE file in
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# the root directory of this source tree.
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import json
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from collections.abc import AsyncIterator
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from botocore.client import BaseClient
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from llama_stack.apis.inference import (
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ChatCompletionRequest,
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Inference,
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OpenAIChatCompletionRequestWithExtraBody,
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OpenAICompletionRequestWithExtraBody,
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OpenAIEmbeddingsResponse,
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)
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from llama_stack.apis.inference.inference import (
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OpenAIChatCompletion,
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OpenAIChatCompletionChunk,
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OpenAICompletion,
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)
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from llama_stack.providers.remote.inference.bedrock.config import BedrockConfig
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from llama_stack.providers.utils.bedrock.client import create_bedrock_client
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from llama_stack.providers.utils.inference.model_registry import (
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ModelRegistryHelper,
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)
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from llama_stack.providers.utils.inference.openai_compat import (
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get_sampling_strategy_options,
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)
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from llama_stack.providers.utils.inference.prompt_adapter import (
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chat_completion_request_to_prompt,
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)
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from .models import MODEL_ENTRIES
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REGION_PREFIX_MAP = {
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"us": "us.",
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"eu": "eu.",
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"ap": "ap.",
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}
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def _get_region_prefix(region: str | None) -> str:
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# AWS requires region prefixes for inference profiles
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if region is None:
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return "us." # default to US when we don't know
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# Handle case insensitive region matching
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region_lower = region.lower()
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for prefix in REGION_PREFIX_MAP:
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if region_lower.startswith(f"{prefix}-"):
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return REGION_PREFIX_MAP[prefix]
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# Fallback to US for anything we don't recognize
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return "us."
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def _to_inference_profile_id(model_id: str, region: str = None) -> str:
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# Return ARNs unchanged
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if model_id.startswith("arn:"):
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return model_id
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# Return inference profile IDs that already have regional prefixes
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if any(model_id.startswith(p) for p in REGION_PREFIX_MAP.values()):
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return model_id
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# Default to US East when no region is provided
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if region is None:
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region = "us-east-1"
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return _get_region_prefix(region) + model_id
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class BedrockInferenceAdapter(
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ModelRegistryHelper,
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Inference,
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):
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def __init__(self, config: BedrockConfig) -> None:
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ModelRegistryHelper.__init__(self, model_entries=MODEL_ENTRIES)
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self._config = config
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self._client = None
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@property
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def client(self) -> BaseClient:
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if self._client is None:
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self._client = create_bedrock_client(self._config)
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return self._client
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async def initialize(self) -> None:
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pass
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async def shutdown(self) -> None:
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if self._client is not None:
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self._client.close()
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async def _get_params_for_chat_completion(self, request: ChatCompletionRequest) -> dict:
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bedrock_model = request.model
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sampling_params = request.sampling_params
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options = get_sampling_strategy_options(sampling_params)
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if sampling_params.max_tokens:
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options["max_gen_len"] = sampling_params.max_tokens
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if sampling_params.repetition_penalty > 0:
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options["repetition_penalty"] = sampling_params.repetition_penalty
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prompt = await chat_completion_request_to_prompt(request, self.get_llama_model(request.model))
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# Convert foundation model ID to inference profile ID
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region_name = self.client.meta.region_name
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inference_profile_id = _to_inference_profile_id(bedrock_model, region_name)
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return {
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"modelId": inference_profile_id,
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"body": json.dumps(
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{
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"prompt": prompt,
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**options,
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}
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),
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}
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async def openai_embeddings(
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self,
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model: str,
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input: str | list[str],
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encoding_format: str | None = "float",
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dimensions: int | None = None,
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user: str | None = None,
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) -> OpenAIEmbeddingsResponse:
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raise NotImplementedError()
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async def openai_completion(
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self,
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params: OpenAICompletionRequestWithExtraBody,
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) -> OpenAICompletion:
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raise NotImplementedError("OpenAI completion not supported by the Bedrock provider")
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async def openai_chat_completion(
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self,
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params: OpenAIChatCompletionRequestWithExtraBody,
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) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
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raise NotImplementedError("OpenAI chat completion not supported by the Bedrock provider")
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