[openapi server] log exception in exception handler(2/N)

tests/entrypoints/openai/test_lora_adapters.py

@@ -196,7 +196,7 @@ async def test_dynamic_lora_invalid_files(client: openai.AsyncOpenAI, tmp_path):
     invalid_files.mkdir()
     (invalid_files / "adapter_config.json").write_text("this is not json")
 
-    with pytest.raises(openai.BadRequestError):
+    with pytest.raises(openai.InternalServerError):
         await client.post(
             "load_lora_adapter",
             cast_to=str,
@@ -232,7 +232,7 @@ async def test_dynamic_lora_badrequests(
         json.dump(adapter_config, f)
 
     # Test loading the adapter
-    with pytest.raises(openai.BadRequestError, match=expected_error):
+    with pytest.raises(openai.InternalServerError, match=expected_error):
         await client.post(
             "load_lora_adapter",
             cast_to=str,
@@ -312,7 +312,7 @@ async def run_good_requests(client):
                 body={"lora_name": "notfound", "lora_path": "/not/an/adapter"},
             )
     for _ in range(25):
-        with suppress(openai.BadRequestError):
+        with suppress(openai.InternalServerError):
             await client.post(
                 "load_lora_adapter",
                 cast_to=str,

tests/entrypoints/sagemaker/test_sagemaker_lora_adapters.py

@@ -88,7 +88,7 @@ async def test_sagemaker_load_adapter_invalid_files(
         basic_server_with_lora.url_for("adapters"),
         json={"name": "invalid-adapter", "src": str(invalid_files)},
     )
-    assert load_response.status_code == 400
+    assert load_response.status_code == 500
 
 
 @pytest.mark.asyncio

vllm/entrypoints/anthropic/api_router.py

@@ -62,7 +62,7 @@ async def create_messages(request: AnthropicMessagesRequest, raw_request: Reques
     if handler is None:
         base_server = raw_request.app.state.openai_serving_tokenization
         error = base_server.create_error_response(
-            message="The model does not support Messages API"
+            NotImplementedError("The model does not support Messages API")
         )
         return translate_error_response(error)
 
@@ -108,7 +108,7 @@ async def count_tokens(request: AnthropicCountTokensRequest, raw_request: Reques
     if handler is None:
         base_server = raw_request.app.state.openai_serving_tokenization
         error = base_server.create_error_response(
-            message="The model does not support Messages API"
+            NotImplementedError("The model does not support Messages API")
         )
         return translate_error_response(error)
 

vllm/entrypoints/openai/chat_completion/api_router.py

@@ -50,10 +50,7 @@ async def create_chat_completion(request: ChatCompletionRequest, raw_request: Re
     )
     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"
-        )
+        raise NotImplementedError("The model does not support Chat Completions API")
 
     generator = await handler.create_chat_completion(request, raw_request)
 

vllm/entrypoints/openai/completion/api_router.py

@@ -49,10 +49,7 @@ async def create_completion(request: CompletionRequest, raw_request: Request):
     )
     handler = completion(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 Completions API"
-        )
+        raise NotImplementedError("The model does not support Completions API")
 
     generator = await handler.create_completion(request, raw_request)
 

vllm/entrypoints/openai/models/serving.py

@@ -7,7 +7,6 @@
 
 from vllm.engine.protocol import EngineClient
 from vllm.entrypoints.openai.engine.protocol import (
-    ErrorInfo,
     ErrorResponse,
     ModelCard,
     ModelList,
@@ -18,7 +17,8 @@
     LoadLoRAAdapterRequest,
     UnloadLoRAAdapterRequest,
 )
-from vllm.entrypoints.utils import sanitize_message
+from vllm.entrypoints.utils import create_error_response
+from vllm.exceptions import LoRAAdapterNotFoundError
 from vllm.logger import init_logger
 from vllm.lora.request import LoRARequest
 from vllm.lora.resolver import LoRAResolver, LoRAResolverRegistry
@@ -152,15 +152,15 @@ async def load_lora_adapter(
             try:
                 await self.engine_client.add_lora(lora_request)
             except Exception as e:
-                error_type = "BadRequestError"
-                status_code = HTTPStatus.BAD_REQUEST
-                if "No adapter found" in str(e):
-                    error_type = "NotFoundError"
-                    status_code = HTTPStatus.NOT_FOUND
-
-                return create_error_response(
-                    message=str(e), err_type=error_type, status_code=status_code
-                )
+                if str(
+                    LoRAAdapterNotFoundError(
+                        lora_request.lora_name, lora_request.lora_path
+                    )
+                ) in str(e):
+                    raise LoRAAdapterNotFoundError(
+                        lora_request.lora_name, lora_request.lora_path
+                    ) from e
+                raise
 
             self.lora_requests[lora_name] = lora_request
             logger.info(
@@ -292,17 +292,3 @@ async def resolve_lora(self, lora_name: str) -> LoRARequest | ErrorResponse:
                     err_type="NotFoundError",
                     status_code=HTTPStatus.NOT_FOUND,
                 )
-
-
-def create_error_response(
-    message: str,
-    err_type: str = "BadRequestError",
-    status_code: HTTPStatus = HTTPStatus.BAD_REQUEST,
-) -> ErrorResponse:
-    return ErrorResponse(
-        error=ErrorInfo(
-            message=sanitize_message(message),
-            type=err_type,
-            code=status_code.value,
-        )
-    )

vllm/entrypoints/openai/responses/api_router.py

@@ -59,10 +59,7 @@ async def _convert_stream_to_sse_events(
 async def create_responses(request: ResponsesRequest, raw_request: Request):
     handler = responses(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 Responses API"
-        )
+        raise NotImplementedError("The model does not support Responses API")
 
     generator = await handler.create_responses(request, raw_request)
 
@@ -88,10 +85,7 @@ async def retrieve_responses(
 ):
     handler = responses(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 Responses API"
-        )
+        raise NotImplementedError("The model does not support Responses API")
 
     response = await handler.retrieve_responses(
         response_id,
@@ -115,10 +109,7 @@ async def retrieve_responses(
 async def cancel_responses(response_id: str, raw_request: Request):
     handler = responses(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 Responses API"
-        )
+        raise NotImplementedError("The model does not support Responses API")
 
     response = await handler.cancel_responses(response_id)
 

vllm/entrypoints/openai/speech_to_text/api_router.py

@@ -65,10 +65,7 @@ async def create_transcriptions(
 ):
     handler = transcription(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 Transcriptions API"
-        )
+        raise NotImplementedError("The model does not support Transcriptions API")
 
     audio_data = await request.file.read()
 
@@ -101,10 +98,7 @@ async def create_translations(
 ):
     handler = translation(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 Translations API"
-        )
+        raise NotImplementedError("The model does not support Translations API")
 
     audio_data = await request.file.read()
 

vllm/entrypoints/pooling/classify/api_router.py

@@ -2,13 +2,12 @@
 # SPDX-FileCopyrightText: Copyright contributors to the vLLM project
 
 from fastapi import APIRouter, Depends, Request
-from fastapi.responses import JSONResponse, Response
+from fastapi.responses import Response
 
 from vllm.entrypoints.openai.utils import validate_json_request
 from vllm.entrypoints.pooling.classify.protocol import ClassificationRequest
 from vllm.entrypoints.pooling.classify.serving import ServingClassification
 from vllm.entrypoints.utils import (
-    create_error_response,
     load_aware_call,
     with_cancellation,
 )
@@ -28,12 +27,6 @@ async def create_classify(
 ) -> Response:
     handler = classify(raw_request)
     if handler is None:
-        error_response = create_error_response(
-            message="The model does not support Classification API"
-        )
-        return JSONResponse(
-            content=error_response.model_dump(),
-            status_code=error_response.error.code,
-        )
+        raise NotImplementedError("The model does not support Classification API")
 
     return await handler(request, raw_request)

vllm/entrypoints/pooling/embed/api_router.py

@@ -4,14 +4,12 @@
 from http import HTTPStatus
 
 from fastapi import APIRouter, Depends, Request
-from fastapi.responses import JSONResponse
 
 from vllm.entrypoints.openai.engine.protocol import ErrorResponse
 from vllm.entrypoints.openai.utils import validate_json_request
 from vllm.entrypoints.pooling.embed.protocol import EmbeddingRequest
 from vllm.entrypoints.pooling.embed.serving import ServingEmbedding
 from vllm.entrypoints.utils import (
-    create_error_response,
     load_aware_call,
     with_cancellation,
 )
@@ -39,11 +37,6 @@ async def create_embedding(
 ):
     handler = embedding(raw_request)
     if handler is None:
-        error_response = create_error_response(
-            message="The model does not support Embeddings API"
-        )
-        return JSONResponse(
-            content=error_response.model_dump(),
-            status_code=error_response.error.code,
-        )
+        raise NotImplementedError("The model does not support Embeddings API")
+
     return await handler(request, raw_request)

vllm/entrypoints/pooling/pooling/api_router.py

@@ -37,10 +37,7 @@ def pooling(request: Request) -> OpenAIServingPooling | None:
 async def create_pooling(request: PoolingRequest, raw_request: Request):
     handler = pooling(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 Pooling API"
-        )
+        raise NotImplementedError("The model does not support Pooling API")
 
     generator = await handler.create_pooling(request, raw_request)
 

vllm/entrypoints/pooling/score/api_router.py

@@ -44,10 +44,7 @@ def rerank(request: Request) -> ServingScores | None:
 async def create_score(request: ScoreRequest, raw_request: Request):
     handler = score(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 Score API"
-        )
+        raise NotImplementedError("The model does not support Score API")
 
     generator = await handler.create_score(request, raw_request)
 
@@ -93,10 +90,7 @@ async def create_score_v1(request: ScoreRequest, raw_request: Request):
 async def do_rerank(request: RerankRequest, raw_request: Request):
     handler = rerank(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 Rerank (Score) API"
-        )
+        raise NotImplementedError("The model does not support Rerank (Score) API")
 
     generator = await handler.do_rerank(request, raw_request)
 

vllm/entrypoints/serve/disagg/api_router.py

@@ -61,9 +61,7 @@ def engine_client(request: Request) -> EngineClient:
 async def generate(request: GenerateRequest, raw_request: Request):
     handler = generate_tokens(raw_request)
     if handler is None:
-        return tokenization(raw_request).create_error_response(
-            message="The model does not support generate tokens API"
-        )
+        raise NotImplementedError("The model does not support generate tokens API")
 
     generator = await handler.serve_tokens(request, raw_request)
 

vllm/entrypoints/serve/render/api_router.py

@@ -10,7 +10,6 @@
 from vllm.entrypoints.openai.engine.protocol import ErrorResponse
 from vllm.entrypoints.openai.utils import validate_json_request
 from vllm.entrypoints.serve.render.serving import OpenAIServingRender
-from vllm.entrypoints.utils import create_error_response
 from vllm.logger import init_logger
 
 logger = init_logger(__name__)
@@ -36,13 +35,8 @@ def render(request: Request) -> OpenAIServingRender | None:
 async def render_chat_completion(request: ChatCompletionRequest, raw_request: Request):
     handler = render(raw_request)
     if handler is None:
-        error = create_error_response(
-            message="The model does not support Chat Completions Render API",
-            err_type="NotFoundError",
-            status_code=HTTPStatus.NOT_FOUND,
-        )
-        return JSONResponse(
-            status_code=HTTPStatus.NOT_FOUND, content=error.model_dump()
+        raise NotImplementedError(
+            "The model does not support Chat Completions Render API"
         )
 
     result = await handler.render_chat_request(request)
@@ -66,14 +60,7 @@ async def render_chat_completion(request: ChatCompletionRequest, raw_request: Re
 async def render_completion(request: CompletionRequest, raw_request: Request):
     handler = render(raw_request)
     if handler is None:
-        error = create_error_response(
-            message="The model does not support Completions Render API",
-            err_type="NotFoundError",
-            status_code=HTTPStatus.NOT_FOUND,
-        )
-        return JSONResponse(
-            status_code=HTTPStatus.NOT_FOUND, content=error.model_dump()
-        )
+        raise NotImplementedError("The model does not support Completions Render API")
 
     result = await handler.render_completion_request(request)
 

vllm/exceptions.py

@@ -36,7 +36,31 @@ def __str__(self):
         return f"{base} ({', '.join(extras)})" if extras else base
 
 
-class VLLMNotFoundError(ValueError):
+class VLLMNotFoundError(Exception):
     """vLLM-specific NotFoundError"""
 
     pass
+
+
+class LoRAAdapterNotFoundError(VLLMNotFoundError):
+    """Exception raised when a LoRA adapter is not found.
+
+    This exception is thrown when a requested LoRA adapter does not exist
+    in the system.
+
+    Attributes:
+        message: The error message string describing the exception
+    """
+
+    message: str
+
+    def __init__(
+        self,
+        lora_name: str,
+        lora_path: str,
+    ) -> None:
+        message = f"Loading lora {lora_name} failed: No adapter found for {lora_path}"
+        self.message = message
+
+    def __str__(self):
+        return self.message

vllm/lora/worker_manager.py

@@ -7,6 +7,7 @@
 import torch
 
 from vllm.config import VllmConfig
+from vllm.exceptions import LoRAAdapterNotFoundError
 from vllm.logger import init_logger
 from vllm.lora.lora_model import LoRAModel
 from vllm.lora.model_manager import (
@@ -147,12 +148,10 @@ def _load_adapter(self, lora_request: LoRARequest) -> LoRAModel:
             #       offline mode)
             # - No local adapter files found at `lora_request.lora_path`
             # For NotFoundError
-            raise ValueError(
-                f"Loading lora {lora_request.lora_name} failed: No adapter "
-                f"found for {lora_request.lora_path}"
+            raise LoRAAdapterNotFoundError(
+                lora_request.lora_name, lora_request.lora_path
             ) from e
         except Exception as e:
-            # For BadRequestError
             raise e
 
         return lora