[Frontend] Standardize use of create_error_response (#32319)

Signed-off-by: DarkLight1337 <tlleungac@connect.ust.hk>

vllm/entrypoints/openai/api_server.py

@@ -368,14 +368,8 @@ async def create_completion(request: CompletionRequest, raw_request: Request):
 
     try:
         generator = await handler.create_completion(request, raw_request)
-    except OverflowError as e:
-        raise HTTPException(
-            status_code=HTTPStatus.BAD_REQUEST.value, detail=str(e)
-        ) from e
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(

vllm/entrypoints/openai/chat_completion/api_router.py

@@ -4,7 +4,7 @@
 
 from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, FastAPI, HTTPException, Request
+from fastapi import APIRouter, Depends, FastAPI, Request
 from fastapi.responses import JSONResponse, StreamingResponse
 
 from vllm.entrypoints.openai.chat_completion.protocol import (
@@ -53,12 +53,12 @@ async def create_chat_completion(request: ChatCompletionRequest, raw_request: Re
         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:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code

vllm/entrypoints/openai/engine/serving.py

@@ -94,7 +94,7 @@ from vllm.entrypoints.serve.tokenize.protocol import (
     TokenizeCompletionRequest,
     TokenizeResponse,
 )
-from vllm.entrypoints.utils import _validate_truncation_size
+from vllm.entrypoints.utils import _validate_truncation_size, sanitize_message
 from vllm.inputs.data import PromptType, TokensPrompt
 from vllm.inputs.parse import (
     PromptComponents,
@@ -768,11 +768,15 @@ class OpenAIServing:
                 err_type = "BadRequestError"
                 status_code = HTTPStatus.BAD_REQUEST
                 param = exc.parameter
-            elif isinstance(exc, (ValueError, TypeError, RuntimeError)):
+            elif isinstance(exc, (ValueError, TypeError, RuntimeError, OverflowError)):
                 # Common validation errors from user input
                 err_type = "BadRequestError"
                 status_code = HTTPStatus.BAD_REQUEST
                 param = None
+            elif isinstance(exc, NotImplementedError):
+                err_type = "NotImplementedError"
+                status_code = HTTPStatus.NOT_IMPLEMENTED
+                param = None
             elif exc.__class__.__name__ == "TemplateError":
                 # jinja2.TemplateError (avoid importing jinja2)
                 err_type = "BadRequestError"
@@ -791,9 +795,10 @@ class OpenAIServing:
                 traceback.print_exc()
             else:
                 traceback.print_stack()
+
         return ErrorResponse(
             error=ErrorInfo(
-                message=message,
+                message=sanitize_message(message),
                 type=err_type,
                 code=status_code.value,
                 param=param,

vllm/entrypoints/openai/responses/api_router.py

@@ -5,7 +5,7 @@
 from collections.abc import AsyncGenerator
 from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, FastAPI, HTTPException, Request
+from fastapi import APIRouter, Depends, FastAPI, Request
 from fastapi.responses import JSONResponse, StreamingResponse
 
 from vllm.entrypoints.openai.engine.protocol import ErrorResponse
@@ -64,9 +64,7 @@ async def create_responses(request: ResponsesRequest, raw_request: Request):
     try:
         generator = await handler.create_responses(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
@@ -101,9 +99,7 @@ async def retrieve_responses(
             stream=stream,
         )
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(response, ErrorResponse):
         return JSONResponse(
@@ -128,9 +124,7 @@ async def cancel_responses(response_id: str, raw_request: Request):
     try:
         response = await handler.cancel_responses(response_id)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(response, ErrorResponse):
         return JSONResponse(

vllm/entrypoints/openai/serving_models.py

@@ -18,6 +18,7 @@ from vllm.entrypoints.serve.lora.protocol import (
     LoadLoRAAdapterRequest,
     UnloadLoRAAdapterRequest,
 )
+from vllm.entrypoints.utils import sanitize_message
 from vllm.logger import init_logger
 from vllm.lora.request import LoRARequest
 from vllm.lora.resolver import LoRAResolver, LoRAResolverRegistry
@@ -302,5 +303,9 @@ def create_error_response(
     status_code: HTTPStatus = HTTPStatus.BAD_REQUEST,
 ) -> ErrorResponse:
     return ErrorResponse(
-        error=ErrorInfo(message=message, type=err_type, code=status_code.value)
+        error=ErrorInfo(
+            message=sanitize_message(message),
+            type=err_type,
+            code=status_code.value,
+        )
     )

vllm/entrypoints/pooling/classify/api_router.py

@@ -1,8 +1,7 @@
 # SPDX-License-Identifier: Apache-2.0
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
-from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, Request
 from starlette.responses import JSONResponse
 from typing_extensions import assert_never
 
@@ -36,9 +35,8 @@ async def create_classify(request: ClassificationRequest, raw_request: Request):
     try:
         generator = await handler.create_classify(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code

vllm/entrypoints/pooling/embed/api_router.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, Request
 from fastapi.responses import JSONResponse, StreamingResponse
 from typing_extensions import assert_never
 
@@ -47,9 +47,7 @@ async def create_embedding(
     try:
         generator = await handler.create_embedding(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(

vllm/entrypoints/pooling/pooling/api_router.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, Request
 from fastapi.responses import JSONResponse, StreamingResponse
 from typing_extensions import assert_never
 
@@ -44,9 +44,8 @@ async def create_pooling(request: PoolingRequest, raw_request: Request):
     try:
         generator = await handler.create_pooling(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code

vllm/entrypoints/pooling/score/api_router.py

@@ -2,7 +2,7 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 from http import HTTPStatus
 
-from fastapi import APIRouter, Depends, HTTPException, Request
+from fastapi import APIRouter, Depends, Request
 from fastapi.responses import JSONResponse
 from typing_extensions import assert_never
 
@@ -52,9 +52,8 @@ async def create_score(request: ScoreRequest, raw_request: Request):
     try:
         generator = await handler.create_score(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code
@@ -104,9 +103,8 @@ async def do_rerank(request: RerankRequest, raw_request: Request):
     try:
         generator = await handler.do_rerank(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code

vllm/entrypoints/serve/disagg/api_router.py

@@ -67,9 +67,8 @@ async def generate(request: GenerateRequest, raw_request: Request):
     try:
         generator = await handler.serve_tokens(request, raw_request)
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
+
     if isinstance(generator, ErrorResponse):
         return JSONResponse(
             content=generator.model_dump(), status_code=generator.error.code

vllm/entrypoints/serve/tokenize/api_router.py

@@ -51,14 +51,8 @@ async def tokenize(request: TokenizeRequest, raw_request: Request):
 
     try:
         generator = await handler.create_tokenize(request, raw_request)
-    except NotImplementedError as e:
-        raise HTTPException(
-            status_code=HTTPStatus.NOT_IMPLEMENTED.value, detail=str(e)
-        ) from e
     except Exception as e:
-        raise HTTPException(
-            status_code=HTTPStatus.INTERNAL_SERVER_ERROR.value, detail=str(e)
-        ) from e
+        return handler.create_error_response(e)
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(

vllm/entrypoints/utils.py

@@ -7,7 +7,7 @@ import functools
 import os
 from argparse import Namespace
 from pathlib import Path
-from typing import Any
+from typing import TYPE_CHECKING, Any
 
 import regex as re
 from fastapi import Request
@@ -22,20 +22,27 @@ from vllm.entrypoints.chat_utils import (
     resolve_hf_chat_template,
     resolve_mistral_chat_template,
 )
-from vllm.entrypoints.openai.chat_completion.protocol import (
-    ChatCompletionRequest,
-)
-from vllm.entrypoints.openai.cli_args import make_arg_parser
-from vllm.entrypoints.openai.engine.protocol import (
-    CompletionRequest,
-    StreamOptions,
-)
-from vllm.entrypoints.openai.serving_models import LoRAModulePath
 from vllm.logger import init_logger
 from vllm.platforms import current_platform
 from vllm.tokenizers.mistral import MistralTokenizer
 from vllm.utils.argparse_utils import FlexibleArgumentParser
 
+if TYPE_CHECKING:
+    from vllm.entrypoints.openai.chat_completion.protocol import (
+        ChatCompletionRequest,
+    )
+    from vllm.entrypoints.openai.engine.protocol import (
+        CompletionRequest,
+        StreamOptions,
+    )
+    from vllm.entrypoints.openai.serving_models import LoRAModulePath
+else:
+    ChatCompletionRequest = object
+    CompletionRequest = object
+    StreamOptions = object
+    LoRAModulePath = object
+
+
 logger = init_logger(__name__)
 
 VLLM_SUBCMD_PARSER_EPILOG = (
@@ -208,7 +215,7 @@ def _validate_truncation_size(
 
 def get_max_tokens(
     max_model_len: int,
-    request: ChatCompletionRequest | CompletionRequest,
+    request: "ChatCompletionRequest | CompletionRequest",
     input_length: int,
     default_sampling_params: dict,
 ) -> int:
@@ -229,6 +236,8 @@ def get_max_tokens(
 
 
 def log_non_default_args(args: Namespace | EngineArgs):
+    from vllm.entrypoints.openai.cli_args import make_arg_parser
+
     non_default_args = {}
 
     # Handle Namespace
@@ -257,7 +266,7 @@ def log_non_default_args(args: Namespace | EngineArgs):
 
 
 def should_include_usage(
-    stream_options: StreamOptions | None, enable_force_include_usage: bool
+    stream_options: "StreamOptions | None", enable_force_include_usage: bool
 ) -> tuple[bool, bool]:
     if stream_options:
         include_usage = stream_options.include_usage or enable_force_include_usage
@@ -272,6 +281,8 @@ def should_include_usage(
 def process_lora_modules(
     args_lora_modules: list[LoRAModulePath], default_mm_loras: dict[str, str] | None
 ) -> list[LoRAModulePath]:
+    from vllm.entrypoints.openai.serving_models import LoRAModulePath
+
     lora_modules = args_lora_modules
     if default_mm_loras:
         default_mm_lora_paths = [