[Frontend] Update OpenAI error response to upstream format (#22099)

Signed-off-by: Moritz Sanft <58110325+msanft@users.noreply.github.com>

tests/entrypoints/openai/test_classification.py

@@ -121,8 +121,7 @@ def test_invalid_truncate_prompt_tokens_error(server: RemoteOpenAIServer,
 
     error = classification_response.json()
     assert classification_response.status_code == 400
-    assert error["object"] == "error"
-    assert "truncate_prompt_tokens" in error["message"]
+    assert "truncate_prompt_tokens" in error["error"]["message"]
 
 
 @pytest.mark.parametrize("model_name", [MODEL_NAME])
@@ -137,7 +136,7 @@ def test_empty_input_error(server: RemoteOpenAIServer, model_name: str):
 
     error = classification_response.json()
     assert classification_response.status_code == 400
-    assert error["object"] == "error"
+    assert "error" in error
 
 
 @pytest.mark.parametrize("model_name", [MODEL_NAME])

tests/entrypoints/openai/test_lora_resolvers.py

@@ -160,8 +160,8 @@ async def test_serving_completion_resolver_not_found(mock_serving_setup,
     mock_engine.generate.assert_not_called()
 
     assert isinstance(response, ErrorResponse)
-    assert response.code == HTTPStatus.NOT_FOUND.value
-    assert non_existent_model in response.message
+    assert response.error.code == HTTPStatus.NOT_FOUND.value
+    assert non_existent_model in response.error.message
 
 
 @pytest.mark.asyncio
@@ -190,8 +190,8 @@ async def test_serving_completion_resolver_add_lora_fails(
 
     # Assert the correct error response
     assert isinstance(response, ErrorResponse)
-    assert response.code == HTTPStatus.BAD_REQUEST.value
-    assert invalid_model in response.message
+    assert response.error.code == HTTPStatus.BAD_REQUEST.value
+    assert invalid_model in response.error.message
 
 
 @pytest.mark.asyncio

tests/entrypoints/openai/test_serving_models.py

@@ -66,8 +66,8 @@ async def test_load_lora_adapter_missing_fields():
     request = LoadLoRAAdapterRequest(lora_name="", lora_path="")
     response = await serving_models.load_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
-    assert response.type == "InvalidUserInput"
-    assert response.code == HTTPStatus.BAD_REQUEST
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
 
 
 @pytest.mark.asyncio
@@ -84,8 +84,8 @@ async def test_load_lora_adapter_duplicate():
                                      lora_path="/path/to/adapter1")
     response = await serving_models.load_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
-    assert response.type == "InvalidUserInput"
-    assert response.code == HTTPStatus.BAD_REQUEST
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
     assert len(serving_models.lora_requests) == 1
 
 
@@ -110,8 +110,8 @@ async def test_unload_lora_adapter_missing_fields():
     request = UnloadLoRAAdapterRequest(lora_name="", lora_int_id=None)
     response = await serving_models.unload_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
-    assert response.type == "InvalidUserInput"
-    assert response.code == HTTPStatus.BAD_REQUEST
+    assert response.error.type == "InvalidUserInput"
+    assert response.error.code == HTTPStatus.BAD_REQUEST
 
 
 @pytest.mark.asyncio
@@ -120,5 +120,5 @@ async def test_unload_lora_adapter_not_found():
     request = UnloadLoRAAdapterRequest(lora_name="nonexistent_adapter")
     response = await serving_models.unload_lora_adapter(request)
     assert isinstance(response, ErrorResponse)
-    assert response.type == "NotFoundError"
-    assert response.code == HTTPStatus.NOT_FOUND
+    assert response.error.type == "NotFoundError"
+    assert response.error.code == HTTPStatus.NOT_FOUND

tests/entrypoints/openai/test_transcription_validation.py

@@ -116,8 +116,10 @@ async def test_non_asr_model(winning_call):
                                                        file=winning_call,
                                                        language="en",
                                                        temperature=0.0)
-        assert res.code == 400 and not res.text
-        assert res.message == "The model does not support Transcriptions API"
+        err = res.error
+        assert err["code"] == 400 and not res.text
+        assert err[
+            "message"] == "The model does not support Transcriptions API"
 
 
 @pytest.mark.asyncio
@@ -133,12 +135,15 @@ async def test_completion_endpoints():
                 "role": "system",
                 "content": "You are a helpful assistant."
             }])
-        assert res.code == 400
-        assert res.message == "The model does not support Chat Completions API"
+        err = res.error
+        assert err["code"] == 400
+        assert err[
+            "message"] == "The model does not support Chat Completions API"
 
         res = await client.completions.create(model=model_name, prompt="Hello")
-        assert res.code == 400
-        assert res.message == "The model does not support Completions API"
+        err = res.error
+        assert err["code"] == 400
+        assert err["message"] == "The model does not support Completions API"
 
 
 @pytest.mark.asyncio

tests/entrypoints/openai/test_translation_validation.py

@@ -73,8 +73,9 @@ async def test_non_asr_model(foscolo):
         res = await client.audio.translations.create(model=model_name,
                                                      file=foscolo,
                                                      temperature=0.0)
-        assert res.code == 400 and not res.text
-        assert res.message == "The model does not support Translations API"
+        err = res.error
+        assert err["code"] == 400 and not res.text
+        assert err["message"] == "The model does not support Translations API"
 
 
 @pytest.mark.asyncio

vllm/entrypoints/openai/api_server.py

@@ -62,7 +62,8 @@ from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
                                               DetokenizeRequest,
                                               DetokenizeResponse,
                                               EmbeddingRequest,
-                                              EmbeddingResponse, ErrorResponse,
+                                              EmbeddingResponse, ErrorInfo,
+                                              ErrorResponse,
                                               LoadLoRAAdapterRequest,
                                               PoolingRequest, PoolingResponse,
                                               RerankRequest, RerankResponse,
@@ -506,7 +507,7 @@ async def tokenize(request: TokenizeRequest, raw_request: Request):
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, TokenizeResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -540,7 +541,7 @@ async def detokenize(request: DetokenizeRequest, raw_request: Request):
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, DetokenizeResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -556,7 +557,7 @@ def maybe_register_tokenizer_info_endpoint(args):
             """Get comprehensive tokenizer information."""
             result = await tokenization(raw_request).get_tokenizer_info()
             return JSONResponse(content=result.model_dump(),
-                                status_code=result.code if isinstance(
+                                status_code=result.error.code if isinstance(
                                     result, ErrorResponse) else 200)
 
 
@@ -603,7 +604,7 @@ async def create_responses(request: ResponsesRequest, raw_request: Request):
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, ResponsesResponse):
         return JSONResponse(content=generator.model_dump())
     return StreamingResponse(content=generator, media_type="text/event-stream")
@@ -620,7 +621,7 @@ async def retrieve_responses(response_id: str, raw_request: Request):
 
     if isinstance(response, ErrorResponse):
         return JSONResponse(content=response.model_dump(),
-                            status_code=response.code)
+                            status_code=response.error.code)
     return JSONResponse(content=response.model_dump())
 
 
@@ -635,7 +636,7 @@ async def cancel_responses(response_id: str, raw_request: Request):
 
     if isinstance(response, ErrorResponse):
         return JSONResponse(content=response.model_dump(),
-                            status_code=response.code)
+                            status_code=response.error.code)
     return JSONResponse(content=response.model_dump())
 
 
@@ -670,7 +671,7 @@ async def create_chat_completion(request: ChatCompletionRequest,
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
 
     elif isinstance(generator, ChatCompletionResponse):
         return JSONResponse(content=generator.model_dump())
@@ -715,7 +716,7 @@ async def create_completion(request: CompletionRequest, raw_request: Request):
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, CompletionResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -744,7 +745,7 @@ async def create_embedding(request: EmbeddingRequest, raw_request: Request):
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, EmbeddingResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -772,7 +773,7 @@ async def create_pooling(request: PoolingRequest, raw_request: Request):
     generator = await handler.create_pooling(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, PoolingResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -792,7 +793,7 @@ async def create_classify(request: ClassificationRequest,
     generator = await handler.create_classify(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
 
     elif isinstance(generator, ClassificationResponse):
         return JSONResponse(content=generator.model_dump())
@@ -821,7 +822,7 @@ async def create_score(request: ScoreRequest, raw_request: Request):
     generator = await handler.create_score(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, ScoreResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -881,7 +882,7 @@ async def create_transcriptions(raw_request: Request,
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
 
     elif isinstance(generator, TranscriptionResponse):
         return JSONResponse(content=generator.model_dump())
@@ -922,7 +923,7 @@ async def create_translations(request: Annotated[TranslationRequest,
 
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
 
     elif isinstance(generator, TranslationResponse):
         return JSONResponse(content=generator.model_dump())
@@ -950,7 +951,7 @@ async def do_rerank(request: RerankRequest, raw_request: Request):
     generator = await handler.do_rerank(request, raw_request)
     if isinstance(generator, ErrorResponse):
         return JSONResponse(content=generator.model_dump(),
-                            status_code=generator.code)
+                            status_code=generator.error.code)
     elif isinstance(generator, RerankResponse):
         return JSONResponse(content=generator.model_dump())
 
@@ -1175,7 +1176,7 @@ async def invocations(raw_request: Request):
     msg = ("Cannot find suitable handler for request. "
            f"Expected one of: {type_names}")
     res = base(raw_request).create_error_response(message=msg)
-    return JSONResponse(content=res.model_dump(), status_code=res.code)
+    return JSONResponse(content=res.model_dump(), status_code=res.error.code)
 
 
 if envs.VLLM_TORCH_PROFILER_DIR:
@@ -1211,7 +1212,7 @@ if envs.VLLM_ALLOW_RUNTIME_LORA_UPDATING:
         response = await handler.load_lora_adapter(request)
         if isinstance(response, ErrorResponse):
             return JSONResponse(content=response.model_dump(),
-                                status_code=response.code)
+                                status_code=response.error.code)
 
         return Response(status_code=200, content=response)
 
@@ -1223,7 +1224,7 @@ if envs.VLLM_ALLOW_RUNTIME_LORA_UPDATING:
         response = await handler.unload_lora_adapter(request)
         if isinstance(response, ErrorResponse):
             return JSONResponse(content=response.model_dump(),
-                                status_code=response.code)
+                                status_code=response.error.code)
 
         return Response(status_code=200, content=response)
 
@@ -1502,9 +1503,10 @@ def build_app(args: Namespace) -> FastAPI:
 
     @app.exception_handler(HTTPException)
     async def http_exception_handler(_: Request, exc: HTTPException):
-        err = ErrorResponse(message=exc.detail,
+        err = ErrorResponse(
+            error=ErrorInfo(message=exc.detail,
                             type=HTTPStatus(exc.status_code).phrase,
-                            code=exc.status_code)
+                            code=exc.status_code))
         return JSONResponse(err.model_dump(), status_code=exc.status_code)
 
     @app.exception_handler(RequestValidationError)
@@ -1518,9 +1520,9 @@ def build_app(args: Namespace) -> FastAPI:
         else:
             message = exc_str
 
-        err = ErrorResponse(message=message,
-                            type=HTTPStatus.BAD_REQUEST.phrase,
-                            code=HTTPStatus.BAD_REQUEST)
+        err = ErrorResponse(error=ErrorInfo(message=message,
+                                            type=HTTPStatus.BAD_REQUEST.phrase,
+                                            code=HTTPStatus.BAD_REQUEST))
         return JSONResponse(err.model_dump(),
                             status_code=HTTPStatus.BAD_REQUEST)
 

vllm/entrypoints/openai/protocol.py

@@ -78,14 +78,17 @@ class OpenAIBaseModel(BaseModel):
         return result
 
 
-class ErrorResponse(OpenAIBaseModel):
-    object: str = "error"
+class ErrorInfo(OpenAIBaseModel):
     message: str
     type: str
     param: Optional[str] = None
     code: int
 
 
+class ErrorResponse(OpenAIBaseModel):
+    error: ErrorInfo
+
+
 class ModelPermission(OpenAIBaseModel):
     id: str = Field(default_factory=lambda: f"modelperm-{random_uuid()}")
     object: str = "model_permission"

vllm/entrypoints/openai/run_batch.py

@@ -302,7 +302,7 @@ async def run_request(serving_engine_func: Callable,
             id=f"vllm-{random_uuid()}",
             custom_id=request.custom_id,
             response=BatchResponseData(
-                status_code=response.code,
+                status_code=response.error.code,
                 request_id=f"vllm-batch-{random_uuid()}"),
             error=response,
         )

vllm/entrypoints/openai/serving_engine.py

@@ -47,10 +47,10 @@ from vllm.entrypoints.openai.protocol import (ChatCompletionRequest,
                                               EmbeddingChatRequest,
                                               EmbeddingCompletionRequest,
                                               EmbeddingRequest,
-                                              EmbeddingResponse, ErrorResponse,
-                                              PoolingResponse, RerankRequest,
-                                              ResponsesRequest, ScoreRequest,
-                                              ScoreResponse,
+                                              EmbeddingResponse, ErrorInfo,
+                                              ErrorResponse, PoolingResponse,
+                                              RerankRequest, ResponsesRequest,
+                                              ScoreRequest, ScoreResponse,
                                               TokenizeChatRequest,
                                               TokenizeCompletionRequest,
                                               TokenizeResponse,
@@ -412,21 +412,18 @@ class OpenAIServing:
             message: str,
             err_type: str = "BadRequestError",
             status_code: HTTPStatus = HTTPStatus.BAD_REQUEST) -> ErrorResponse:
-        return ErrorResponse(message=message,
-                             type=err_type,
-                             code=status_code.value)
+        return ErrorResponse(error=ErrorInfo(
+            message=message, type=err_type, code=status_code.value))
 
     def create_streaming_error_response(
             self,
             message: str,
             err_type: str = "BadRequestError",
             status_code: HTTPStatus = HTTPStatus.BAD_REQUEST) -> str:
-        json_str = json.dumps({
-            "error":
+        json_str = json.dumps(
             self.create_error_response(message=message,
                                        err_type=err_type,
-                                       status_code=status_code).model_dump()
-        })
+                                       status_code=status_code).model_dump())
         return json_str
 
     async def _check_model(
@@ -445,7 +442,7 @@ class OpenAIServing:
             if isinstance(load_result, LoRARequest):
                 return None
             if isinstance(load_result, ErrorResponse) and \
-                load_result.code == HTTPStatus.BAD_REQUEST.value:
+                load_result.error.code == HTTPStatus.BAD_REQUEST.value:
                 error_response = load_result
 
         return error_response or self.create_error_response(

vllm/entrypoints/openai/serving_models.py

@@ -9,7 +9,7 @@ from typing import Optional, Union
 
 from vllm.config import ModelConfig
 from vllm.engine.protocol import EngineClient
-from vllm.entrypoints.openai.protocol import (ErrorResponse,
+from vllm.entrypoints.openai.protocol import (ErrorInfo, ErrorResponse,
                                               LoadLoRAAdapterRequest,
                                               ModelCard, ModelList,
                                               ModelPermission,
@@ -82,7 +82,7 @@ class OpenAIServingModels:
             load_result = await self.load_lora_adapter(
                 request=load_request, base_model_name=lora.base_model_name)
             if isinstance(load_result, ErrorResponse):
-                raise ValueError(load_result.message)
+                raise ValueError(load_result.error.message)
 
     def is_base_model(self, model_name) -> bool:
         return any(model.name == model_name for model in self.base_model_paths)
@@ -284,6 +284,5 @@ def create_error_response(
         message: str,
         err_type: str = "BadRequestError",
         status_code: HTTPStatus = HTTPStatus.BAD_REQUEST) -> ErrorResponse:
-    return ErrorResponse(message=message,
-                         type=err_type,
-                         code=status_code.value)
+    return ErrorResponse(error=ErrorInfo(
+        message=message, type=err_type, code=status_code.value))