llama-stack-mirror/llama_stack/providers/remote/inference/vllm/vllm.py
Eric Huang 4a3d1e33f8 test
# What does this PR do?


## Test Plan
2025-10-09 20:53:21 -07:00

96 lines
3.3 KiB
Python

# Copyright (c) Meta Platforms, Inc. and affiliates.
# All rights reserved.
#
# This source code is licensed under the terms described in the LICENSE file in
# the root directory of this source tree.
from collections.abc import AsyncIterator
from urllib.parse import urljoin
import httpx
from openai.types.chat.chat_completion_chunk import (
ChatCompletionChunk as OpenAIChatCompletionChunk,
)
from pydantic import ConfigDict
from llama_stack.apis.inference import (
OpenAIChatCompletion,
OpenaiChatCompletionRequest,
ToolChoice,
)
from llama_stack.log import get_logger
from llama_stack.providers.datatypes import (
HealthResponse,
HealthStatus,
)
from llama_stack.providers.utils.inference.openai_mixin import OpenAIMixin
from .config import VLLMInferenceAdapterConfig
log = get_logger(name=__name__, category="inference::vllm")
class VLLMInferenceAdapter(OpenAIMixin):
config: VLLMInferenceAdapterConfig
model_config = ConfigDict(arbitrary_types_allowed=True)
provider_data_api_key_field: str = "vllm_api_token"
def get_api_key(self) -> str:
return self.config.api_token or ""
def get_base_url(self) -> str:
"""Get the base URL from config."""
if not self.config.url:
raise ValueError("No base URL configured")
return self.config.url
async def initialize(self) -> None:
if not self.config.url:
raise ValueError(
"You must provide a URL in run.yaml (or via the VLLM_URL environment variable) to use vLLM."
)
async def health(self) -> HealthResponse:
"""
Performs a health check by verifying connectivity to the remote vLLM server.
This method is used by the Provider API to verify
that the service is running correctly.
Uses the unauthenticated /health endpoint.
Returns:
HealthResponse: A dictionary containing the health status.
"""
try:
base_url = self.get_base_url()
health_url = urljoin(base_url, "health")
async with httpx.AsyncClient() as client:
response = await client.get(health_url)
response.raise_for_status()
return HealthResponse(status=HealthStatus.OK)
except Exception as e:
return HealthResponse(status=HealthStatus.ERROR, message=f"Health check failed: {str(e)}")
def get_extra_client_params(self):
return {"http_client": httpx.AsyncClient(verify=self.config.tls_verify)}
async def openai_chat_completion(
self,
params: "OpenaiChatCompletionRequest",
) -> OpenAIChatCompletion | AsyncIterator[OpenAIChatCompletionChunk]:
# Copy params to avoid mutating the original
params = params.model_copy()
# Apply vLLM-specific defaults
if params.max_tokens is None and self.config.max_tokens:
params.max_tokens = self.config.max_tokens
# This is to be consistent with OpenAI API and support vLLM <= v0.6.3
# References:
# * https://platform.openai.com/docs/api-reference/chat/create#chat-create-tool_choice
# * https://github.com/vllm-project/vllm/pull/10000
if not params.tools and params.tool_choice is not None:
params.tool_choice = ToolChoice.none.value
return await super().openai_chat_completion(params)