[Frontend] Use request id from header (#10968)

Signed-off-by: Joe Runde <Joseph.Runde@ibm.com>

docs/requirements-docs.txt

@@ -16,5 +16,6 @@ mistral_common >= 1.5.0
 aiohttp
 starlette
 openai # Required by docs/source/serving/openai_compatible_server.md's vllm.entrypoints.openai.cli_args
+fastapi # Required by docs/source/serving/openai_compatible_server.md's vllm.entrypoints.openai.cli_args
 partial-json-parser # Required by docs/source/serving/openai_compatible_server.md's vllm.entrypoints.openai.cli_args
 requests

vllm/entrypoints/openai/api_server.py

@@ -305,7 +305,7 @@ async def health(raw_request: Request) -> Response:
 async def tokenize(request: TokenizeRequest, raw_request: Request):
     handler = tokenization(raw_request)
 
-    generator = await handler.create_tokenize(request)
+    generator = await handler.create_tokenize(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
                             status_code=generator.code)
@@ -319,7 +319,7 @@ async def tokenize(request: TokenizeRequest, raw_request: Request):
 async def detokenize(request: DetokenizeRequest, raw_request: Request):
     handler = tokenization(raw_request)
 
-    generator = await handler.create_detokenize(request)
+    generator = await handler.create_detokenize(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
                             status_code=generator.code)

vllm/entrypoints/openai/serving_chat.py

@@ -176,7 +176,8 @@ class OpenAIServingChat(OpenAIServing):
             logger.exception("Error in preprocessing prompt inputs")
             return self.create_error_response(str(e))
 
-        request_id = f"chatcmpl-{request.request_id}"
+        request_id = "chatcmpl-" \
+                     f"{self._base_request_id(raw_request, request.request_id)}"
 
         request_metadata = RequestResponseMetadata(request_id=request_id)
         if raw_request:

vllm/entrypoints/openai/serving_completion.py

@@ -30,7 +30,7 @@ from vllm.outputs import RequestOutput
 from vllm.sampling_params import BeamSearchParams, SamplingParams
 from vllm.sequence import Logprob
 from vllm.transformers_utils.tokenizer import AnyTokenizer
-from vllm.utils import merge_async_iterators, random_uuid
+from vllm.utils import merge_async_iterators
 
 logger = init_logger(__name__)
 
@@ -86,7 +86,7 @@ class OpenAIServingCompletion(OpenAIServing):
                 "suffix is not currently supported")
 
         model_name = self.base_model_paths[0].name
-        request_id = f"cmpl-{random_uuid()}"
+        request_id = f"cmpl-{self._base_request_id(raw_request)}"
         created_time = int(time.time())
 
         request_metadata = RequestResponseMetadata(request_id=request_id)

vllm/entrypoints/openai/serving_embedding.py

@@ -19,7 +19,7 @@ from vllm.entrypoints.openai.protocol import (EmbeddingChatRequest,
 from vllm.entrypoints.openai.serving_engine import BaseModelPath, OpenAIServing
 from vllm.logger import init_logger
 from vllm.outputs import PoolingOutput, PoolingRequestOutput
-from vllm.utils import merge_async_iterators, random_uuid
+from vllm.utils import merge_async_iterators
 
 logger = init_logger(__name__)
 
@@ -110,7 +110,7 @@ class OpenAIServingEmbedding(OpenAIServing):
                 "dimensions is currently not supported")
 
         model_name = request.model
-        request_id = f"embd-{random_uuid()}"
+        request_id = f"embd-{self._base_request_id(raw_request)}"
         created_time = int(time.monotonic())
 
         truncate_prompt_tokens = None

vllm/entrypoints/openai/serving_engine.py

@@ -6,6 +6,7 @@ from http import HTTPStatus
 from typing import (Any, Callable, Dict, Iterable, Iterator, List, Mapping,
                     Optional, Sequence, Tuple, TypedDict, Union)
 
+from fastapi import Request
 from pydantic import Field
 from starlette.datastructures import Headers
 from typing_extensions import Annotated
@@ -47,7 +48,7 @@ from vllm.sequence import Logprob
 from vllm.tracing import (contains_trace_headers, extract_trace_headers,
                           log_tracing_disabled_warning)
 from vllm.transformers_utils.tokenizer import AnyTokenizer, MistralTokenizer
-from vllm.utils import AtomicCounter, is_list_of, make_async
+from vllm.utils import AtomicCounter, is_list_of, make_async, random_uuid
 
 logger = init_logger(__name__)
 
@@ -565,6 +566,14 @@ class OpenAIServing:
 
         return None
 
+    @staticmethod
+    def _base_request_id(raw_request: Request,
+                         default: Optional[str] = None) -> Optional[str]:
+        """Pulls the request id to use from a header, if provided"""
+        default = default or random_uuid()
+        return raw_request.headers.get(
+            "X-Request-Id", default) if raw_request is not None else default
+
     @staticmethod
     def _get_decoded_token(logprob: Logprob,
                            token_id: int,

vllm/entrypoints/openai/serving_score.py

@@ -15,7 +15,7 @@ from vllm.inputs.data import TokensPrompt
 from vllm.logger import init_logger
 from vllm.outputs import PoolingRequestOutput
 from vllm.transformers_utils.tokenizers.mistral import MistralTokenizer
-from vllm.utils import make_async, merge_async_iterators, random_uuid
+from vllm.utils import make_async, merge_async_iterators
 
 logger = init_logger(__name__)
 
@@ -102,7 +102,7 @@ class OpenAIServingScores(OpenAIServing):
             return error_check_ret
 
         model_name = request.model
-        request_id = f"score-{random_uuid()}"
+        request_id = f"score-{self._base_request_id(raw_request)}"
         created_time = int(time.monotonic())
         truncate_prompt_tokens = request.truncate_prompt_tokens
 

vllm/entrypoints/openai/serving_tokenization.py

@@ -1,5 +1,7 @@
 from typing import Final, List, Optional, Union
 
+from fastapi import Request
+
 from vllm.config import ModelConfig
 from vllm.engine.protocol import EngineClient
 from vllm.entrypoints.chat_utils import ChatTemplateContentFormatOption
@@ -17,7 +19,6 @@ from vllm.entrypoints.openai.serving_engine import (BaseModelPath,
                                                     LoRAModulePath,
                                                     OpenAIServing)
 from vllm.logger import init_logger
-from vllm.utils import random_uuid
 
 logger = init_logger(__name__)
 
@@ -48,12 +49,13 @@ class OpenAIServingTokenization(OpenAIServing):
     async def create_tokenize(
         self,
         request: TokenizeRequest,
+        raw_request: Request,
     ) -> Union[TokenizeResponse, ErrorResponse]:
         error_check_ret = await self._check_model(request)
         if error_check_ret is not None:
             return error_check_ret
 
-        request_id = f"tokn-{random_uuid()}"
+        request_id = f"tokn-{self._base_request_id(raw_request)}"
 
         try:
             (
@@ -112,12 +114,13 @@ class OpenAIServingTokenization(OpenAIServing):
     async def create_detokenize(
         self,
         request: DetokenizeRequest,
+        raw_request: Request,
     ) -> Union[DetokenizeResponse, ErrorResponse]:
         error_check_ret = await self._check_model(request)
         if error_check_ret is not None:
             return error_check_ret
 
-        request_id = f"tokn-{random_uuid()}"
+        request_id = f"tokn-{self._base_request_id(raw_request)}"
 
         (
             lora_request,