Add minimal vLLM 0.16.1 build repo for BI-V150

vllm/entrypoints/openai/chat_completion/api_router.py

@@ -0,0 +1,108 @@
+# SPDX-License-Identifier: Apache-2.0
+# SPDX-FileCopyrightText: Copyright contributors to the vLLM project
+
+
+from http import HTTPStatus
+
+from fastapi import APIRouter, Depends, FastAPI, Request
+from fastapi.responses import JSONResponse, StreamingResponse
+
+from vllm.entrypoints.openai.chat_completion.protocol import (
+    ChatCompletionRequest,
+    ChatCompletionResponse,
+)
+from vllm.entrypoints.openai.chat_completion.serving import OpenAIServingChat
+from vllm.entrypoints.openai.engine.protocol import ErrorResponse
+from vllm.entrypoints.openai.orca_metrics import metrics_header
+from vllm.entrypoints.openai.utils import validate_json_request
+from vllm.entrypoints.utils import (
+    load_aware_call,
+    with_cancellation,
+)
+from vllm.logger import init_logger
+
+logger = init_logger(__name__)
+
+router = APIRouter()
+ENDPOINT_LOAD_METRICS_FORMAT_HEADER_LABEL = "endpoint-load-metrics-format"
+
+
+def chat(request: Request) -> OpenAIServingChat | None:
+    return request.app.state.openai_serving_chat
+
+
+@router.post(
+    "/v1/chat/completions",
+    dependencies=[Depends(validate_json_request)],
+    responses={
+        HTTPStatus.OK.value: {"content": {"text/event-stream": {}}},
+        HTTPStatus.BAD_REQUEST.value: {"model": ErrorResponse},
+        HTTPStatus.NOT_FOUND.value: {"model": ErrorResponse},
+        HTTPStatus.INTERNAL_SERVER_ERROR.value: {"model": ErrorResponse},
+    },
+)
+@with_cancellation
+@load_aware_call
+async def create_chat_completion(request: ChatCompletionRequest, raw_request: Request):
+    metrics_header_format = raw_request.headers.get(
+        ENDPOINT_LOAD_METRICS_FORMAT_HEADER_LABEL, ""
+    )
+    handler = chat(raw_request)
+    if handler is None:
+        base_server = raw_request.app.state.openai_serving_tokenization
+        return base_server.create_error_response(
+            message="The model does not support Chat Completions API"
+        )
+
+    try:
+        generator = await handler.create_chat_completion(request, raw_request)
+    except Exception as e:
+        generator = handler.create_error_response(e)
+
+    if isinstance(generator, ErrorResponse):
+        return JSONResponse(
+            content=generator.model_dump(), status_code=generator.error.code
+        )
+
+    elif isinstance(generator, ChatCompletionResponse):
+        return JSONResponse(
+            content=generator.model_dump(),
+            headers=metrics_header(metrics_header_format),
+        )
+
+    return StreamingResponse(content=generator, media_type="text/event-stream")
+
+
+@router.post(
+    "/v1/chat/completions/render",
+    dependencies=[Depends(validate_json_request)],
+    response_model=list,
+    responses={
+        HTTPStatus.BAD_REQUEST.value: {"model": ErrorResponse},
+        HTTPStatus.NOT_FOUND.value: {"model": ErrorResponse},
+        HTTPStatus.INTERNAL_SERVER_ERROR.value: {"model": ErrorResponse},
+    },
+)
+async def render_chat_completion(request: ChatCompletionRequest, raw_request: Request):
+    """Render chat completion request and return conversation and engine
+    prompts without generating."""
+    handler = chat(raw_request)
+    if handler is None:
+        base_server = raw_request.app.state.openai_serving_tokenization
+        return base_server.create_error_response(
+            message="The model does not support Chat Completions API"
+        )
+
+    try:
+        result = await handler.render_chat_request(request)
+    except Exception as e:
+        result = handler.create_error_response(e)
+
+    if isinstance(result, ErrorResponse):
+        return JSONResponse(content=result.model_dump(), status_code=result.error.code)
+
+    return JSONResponse(content=result)
+
+
+def attach_router(app: FastAPI):
+    app.include_router(router)