[format] Valid para format error info (#4035)

* feat(log):add_request_and_response_log

* 报错信息与OpenAI对齐

fastdeploy/entrypoints/engine_client.py

@@ -31,7 +31,12 @@ from fastdeploy.inter_communicator import IPCSignal, ZmqClient
 from fastdeploy.metrics.work_metrics import work_process_metrics
 from fastdeploy.multimodal.registry import MultimodalRegistry
 from fastdeploy.platforms import current_platform
-from fastdeploy.utils import EngineError, StatefulSemaphore, api_server_logger
+from fastdeploy.utils import (
+    EngineError,
+    ParameterError,
+    StatefulSemaphore,
+    api_server_logger,
+)
 
 
 class EngineClient:
@@ -218,42 +223,21 @@ class EngineClient:
     def valid_parameters(self, data):
         """
         Validate stream options
+        超参数（top_p、seed、frequency_penalty、temperature、presence_penalty）的校验逻辑
+        前置到了ChatCompletionRequest/CompletionRequest中
         """
 
         if data.get("n") is not None:
             if data["n"] != 1:
-                raise ValueError("n only support 1.")
+                raise ParameterError("n", "n only support 1.")
 
         if data.get("max_tokens") is not None:
             if data["max_tokens"] < 1 or data["max_tokens"] >= self.max_model_len:
-                raise ValueError(f"max_tokens can be defined [1, {self.max_model_len}).")
+                raise ParameterError("max_tokens", f"max_tokens can be defined [1, {self.max_model_len}).")
 
         if data.get("reasoning_max_tokens") is not None:
             if data["reasoning_max_tokens"] > data["max_tokens"] or data["reasoning_max_tokens"] < 1:
-                raise ValueError("reasoning_max_tokens must be between max_tokens and 1")
-
-        if data.get("top_p") is not None:
-            if data["top_p"] > 1 or data["top_p"] < 0:
-                raise ValueError("top_p value can only be defined [0, 1].")
-
-        if data.get("frequency_penalty") is not None:
-            if not -2.0 <= data["frequency_penalty"] <= 2.0:
-                raise ValueError("frequency_penalty must be in [-2, 2]")
-
-        if data.get("temperature") is not None:
-            if data["temperature"] < 0:
-                raise ValueError("temperature must be non-negative")
-
-        if data.get("presence_penalty") is not None:
-            if not -2.0 <= data["presence_penalty"] <= 2.0:
-                raise ValueError("presence_penalty must be in [-2, 2]")
-
-        if data.get("seed") is not None:
-            if not 0 <= data["seed"] <= 922337203685477580:
-                raise ValueError("seed must be in [0, 922337203685477580]")
-
-        if data.get("stream_options") and not data.get("stream"):
-            raise ValueError("Stream options can only be defined when `stream=True`.")
+                raise ParameterError("reasoning_max_tokens", "reasoning_max_tokens must be between max_tokens and 1")
 
         # logprobs
         logprobs = data.get("logprobs")
@@ -263,35 +247,35 @@ class EngineClient:
             if not self.enable_logprob:
                 err_msg = "Logprobs is disabled, please enable it in startup config."
                 api_server_logger.error(err_msg)
-                raise ValueError(err_msg)
+                raise ParameterError("logprobs", err_msg)
             top_logprobs = data.get("top_logprobs")
         elif isinstance(logprobs, int):
             top_logprobs = logprobs
         elif logprobs:
-            raise ValueError("Invalid type for 'logprobs'")
+            raise ParameterError("logprobs", "Invalid type for 'logprobs'")
 
         # enable_logprob
         if top_logprobs:
             if not self.enable_logprob:
                 err_msg = "Logprobs is disabled, please enable it in startup config."
                 api_server_logger.error(err_msg)
-                raise ValueError(err_msg)
+                raise ParameterError("logprobs", err_msg)
 
             if not isinstance(top_logprobs, int):
                 err_type = type(top_logprobs).__name__
                 err_msg = f"Invalid type for 'top_logprobs': expected int but got {err_type}."
                 api_server_logger.error(err_msg)
-                raise ValueError(err_msg)
+                raise ParameterError("top_logprobs", err_msg)
 
             if top_logprobs < 0:
                 err_msg = f"Invalid 'top_logprobs': must be >= 0, got {top_logprobs}."
                 api_server_logger.error(err_msg)
-                raise ValueError(err_msg)
+                raise ParameterError("top_logprobs", err_msg)
 
             if top_logprobs > 20:
                 err_msg = "Invalid value for 'top_logprobs': must be <= 20."
                 api_server_logger.error(err_msg)
-                raise ValueError(err_msg)
+                raise ParameterError("top_logprobs", err_msg)
 
     def check_health(self, time_interval_threashold=30):
         """

fastdeploy/entrypoints/openai/api_server.py

@@ -26,6 +26,7 @@ from multiprocessing import current_process
 import uvicorn
 import zmq
 from fastapi import FastAPI, HTTPException, Request
+from fastapi.exceptions import RequestValidationError
 from fastapi.responses import JSONResponse, Response, StreamingResponse
 from prometheus_client import CONTENT_TYPE_LATEST
 
@@ -40,6 +41,7 @@ from fastdeploy.entrypoints.openai.protocol import (
     CompletionRequest,
     CompletionResponse,
     ControlSchedulerRequest,
+    ErrorInfo,
     ErrorResponse,
     ModelList,
 )
@@ -56,6 +58,7 @@ from fastdeploy.metrics.metrics import (
 )
 from fastdeploy.metrics.trace_util import fd_start_span, inject_to_metadata, instrument
 from fastdeploy.utils import (
+    ExceptionHandler,
     FlexibleArgumentParser,
     StatefulSemaphore,
     api_server_logger,
@@ -232,6 +235,8 @@ async def lifespan(app: FastAPI):
 
 
 app = FastAPI(lifespan=lifespan)
+app.add_exception_handler(RequestValidationError, ExceptionHandler.handle_request_validation_exception)
+app.add_exception_handler(Exception, ExceptionHandler.handle_exception)
 instrument(app)
 
 
@@ -336,7 +341,7 @@ async def create_chat_completion(request: ChatCompletionRequest):
             if isinstance(generator, ErrorResponse):
                 api_server_logger.debug(f"release: {connection_semaphore.status()}")
                 connection_semaphore.release()
-                return JSONResponse(content={"detail": generator.model_dump()}, status_code=generator.code)
+                return JSONResponse(content=generator.model_dump(), status_code=500)
             elif isinstance(generator, ChatCompletionResponse):
                 api_server_logger.debug(f"release: {connection_semaphore.status()}")
                 connection_semaphore.release()
@@ -365,7 +370,7 @@ async def create_completion(request: CompletionRequest):
             generator = await app.state.completion_handler.create_completion(request)
             if isinstance(generator, ErrorResponse):
                 connection_semaphore.release()
-                return JSONResponse(content=generator.model_dump(), status_code=generator.code)
+                return JSONResponse(content=generator.model_dump(), status_code=500)
             elif isinstance(generator, CompletionResponse):
                 connection_semaphore.release()
                 return JSONResponse(content=generator.model_dump())
@@ -388,7 +393,7 @@ async def list_models() -> Response:
 
     models = await app.state.model_handler.list_models()
     if isinstance(models, ErrorResponse):
-        return JSONResponse(content=models.model_dump(), status_code=models.code)
+        return JSONResponse(content=models.model_dump())
     elif isinstance(models, ModelList):
         return JSONResponse(content=models.model_dump())
 
@@ -502,7 +507,8 @@ def control_scheduler(request: ControlSchedulerRequest):
     """
     Control the scheduler behavior with the given parameters.
     """
-    content = ErrorResponse(object="", message="Scheduler updated successfully", code=0)
+
+    content = ErrorResponse(error=ErrorInfo(message="Scheduler updated successfully", code=0))
 
     global llm_engine
     if llm_engine is None:

fastdeploy/entrypoints/openai/protocol.py

@@ -32,9 +32,14 @@ class ErrorResponse(BaseModel):
     Error response from OpenAI API.
     """
 
-    object: str = "error"
+    error: ErrorInfo
+
+
+class ErrorInfo(BaseModel):
     message: str
-    code: int
+    type: Optional[str] = None
+    param: Optional[str] = None
+    code: Optional[str] = None
 
 
 class PromptTokenUsageInfo(BaseModel):
@@ -403,21 +408,21 @@ class CompletionRequest(BaseModel):
     prompt: Union[List[int], List[List[int]], str, List[str]]
     best_of: Optional[int] = None
     echo: Optional[bool] = False
-    frequency_penalty: Optional[float] = None
+    frequency_penalty: Optional[float] = Field(default=None, ge=-2, le=2)
     logprobs: Optional[int] = None
     # For logits and logprobs post processing
     temp_scaled_logprobs: bool = False
     top_p_normalized_logprobs: bool = False
     max_tokens: Optional[int] = None
-    n: int = 1
-    presence_penalty: Optional[float] = None
-    seed: Optional[int] = None
+    n: Optional[int] = 1
+    presence_penalty: Optional[float] = Field(default=None, ge=-2, le=2)
+    seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
     stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
     stream: Optional[bool] = False
     stream_options: Optional[StreamOptions] = None
     suffix: Optional[dict] = None
-    temperature: Optional[float] = None
-    top_p: Optional[float] = None
+    temperature: Optional[float] = Field(default=None, ge=0)
+    top_p: Optional[float] = Field(default=None, ge=0, le=1)
     user: Optional[str] = None
 
     # doc: begin-completion-sampling-params
@@ -537,7 +542,7 @@ class ChatCompletionRequest(BaseModel):
     messages: Union[List[Any], List[int]]
     tools: Optional[List[ChatCompletionToolsParam]] = None
     model: Optional[str] = "default"
-    frequency_penalty: Optional[float] = None
+    frequency_penalty: Optional[float] = Field(None, le=2, ge=-2)
     logprobs: Optional[bool] = False
     top_logprobs: Optional[int] = 0
 
@@ -552,13 +557,13 @@ class ChatCompletionRequest(BaseModel):
     )
     max_completion_tokens: Optional[int] = None
     n: Optional[int] = 1
-    presence_penalty: Optional[float] = None
-    seed: Optional[int] = None
+    presence_penalty: Optional[float] = Field(None, le=2, ge=-2)
+    seed: Optional[int] = Field(default=None, ge=0, le=922337203685477580)
     stop: Optional[Union[str, List[str]]] = Field(default_factory=list)
     stream: Optional[bool] = False
     stream_options: Optional[StreamOptions] = None
-    temperature: Optional[float] = None
-    top_p: Optional[float] = None
+    temperature: Optional[float] = Field(None, ge=0)
+    top_p: Optional[float] = Field(None, le=1, ge=0)
     user: Optional[str] = None
     metadata: Optional[dict] = None
     response_format: Optional[AnyResponseFormat] = None

fastdeploy/entrypoints/openai/serving_chat.py

@@ -30,6 +30,7 @@ from fastdeploy.entrypoints.openai.protocol import (
     ChatCompletionStreamResponse,
     ChatMessage,
     DeltaMessage,
+    ErrorInfo,
     ErrorResponse,
     LogProbEntry,
     LogProbs,
@@ -38,7 +39,7 @@ from fastdeploy.entrypoints.openai.protocol import (
 )
 from fastdeploy.entrypoints.openai.response_processors import ChatResponseProcessor
 from fastdeploy.metrics.work_metrics import work_process_metrics
-from fastdeploy.utils import api_server_logger
+from fastdeploy.utils import ErrorCode, ErrorType, ParameterError, api_server_logger
 from fastdeploy.worker.output import LogprobsLists
 
 
@@ -86,14 +87,16 @@ class OpenAIServingChat:
                 f"Only master node can accept completion request, please send request to master node: {self.master_ip}"
             )
             api_server_logger.error(err_msg)
-            return ErrorResponse(message=err_msg, code=400)
+            return ErrorResponse(error=ErrorInfo(message=err_msg, type=ErrorType.SERVER_ERROR))
 
         if self.models:
             is_supported, request.model = self.models.is_supported_model(request.model)
             if not is_supported:
                 err_msg = f"Unsupported model: [{request.model}], support [{', '.join([x.name for x in self.models.model_paths])}] or default"
                 api_server_logger.error(err_msg)
-                return ErrorResponse(message=err_msg, code=400)
+                return ErrorResponse(
+                    error=ErrorInfo(message=err_msg, type=ErrorType.SERVER_ERROR, code=ErrorCode.MODEL_NOT_SUPPORT)
+                )
 
         try:
             if self.max_waiting_time < 0:
@@ -117,11 +120,17 @@ class OpenAIServingChat:
                 text_after_process = current_req_dict.get("text_after_process")
                 if isinstance(prompt_token_ids, np.ndarray):
                     prompt_token_ids = prompt_token_ids.tolist()
+            except ParameterError as e:
+                api_server_logger.error(e.message)
+                self.engine_client.semaphore.release()
+                return ErrorResponse(
+                    error=ErrorInfo(message=str(e.message), type=ErrorType.INVALID_REQUEST_ERROR, param=e.param)
+                )
             except Exception as e:
                 error_msg = f"request[{request_id}] generator error: {str(e)}, {str(traceback.format_exc())}"
                 api_server_logger.error(error_msg)
                 self.engine_client.semaphore.release()
-                return ErrorResponse(code=400, message=error_msg)
+                return ErrorResponse(error=ErrorInfo(message=error_msg, type=ErrorType.INVALID_REQUEST_ERROR))
             del current_req_dict
 
             if request.stream:
@@ -136,21 +145,20 @@ class OpenAIServingChat:
                 except Exception as e:
                     error_msg = f"request[{request_id}]full generator error: {str(e)}, {str(traceback.format_exc())}"
                     api_server_logger.error(error_msg)
-                    return ErrorResponse(code=408, message=error_msg)
+                    return ErrorResponse(error=ErrorInfo(message=error_msg, type=ErrorType.SERVER_ERROR))
         except Exception as e:
             error_msg = (
                 f"request[{request_id}] waiting error: {str(e)}, {str(traceback.format_exc())}, "
                 f"max waiting time: {self.max_waiting_time}"
             )
             api_server_logger.error(error_msg)
-            return ErrorResponse(code=408, message=error_msg)
+            return ErrorResponse(
+                error=ErrorInfo(message=error_msg, type=ErrorType.TIMEOUT_ERROR, code=ErrorCode.TIMEOUT)
+            )
 
     def _create_streaming_error_response(self, message: str) -> str:
         api_server_logger.error(message)
-        error_response = ErrorResponse(
-            code=400,
-            message=message,
-        )
+        error_response = ErrorResponse(error=ErrorInfo(message=message, type=ErrorType.SERVER_ERROR))
         return error_response.model_dump_json()
 
     async def chat_completion_stream_generator(

fastdeploy/entrypoints/openai/serving_completion.py

@@ -30,10 +30,11 @@ from fastdeploy.entrypoints.openai.protocol import (
     CompletionResponseChoice,
     CompletionResponseStreamChoice,
     CompletionStreamResponse,
+    ErrorInfo,
     ErrorResponse,
     UsageInfo,
 )
-from fastdeploy.utils import api_server_logger
+from fastdeploy.utils import ErrorCode, ErrorType, ParameterError, api_server_logger
 from fastdeploy.worker.output import LogprobsLists
 
 
@@ -63,13 +64,15 @@ class OpenAIServingCompletion:
                 f"Only master node can accept completion request, please send request to master node: {self.master_ip}"
             )
             api_server_logger.error(err_msg)
-            return ErrorResponse(message=err_msg, code=400)
+            return ErrorResponse(error=ErrorInfo(message=err_msg, type=ErrorType.SERVER_ERROR))
         if self.models:
             is_supported, request.model = self.models.is_supported_model(request.model)
             if not is_supported:
                 err_msg = f"Unsupported model: [{request.model}], support [{', '.join([x.name for x in self.models.model_paths])}] or default"
                 api_server_logger.error(err_msg)
-                return ErrorResponse(message=err_msg, code=400)
+                return ErrorResponse(
+                    error=ErrorInfo(message=err_msg, type=ErrorType.SERVER_ERROR, code=ErrorCode.MODEL_NOT_SUPPORT)
+                )
         created_time = int(time.time())
         if request.user is not None:
             request_id = f"cmpl-{request.user}-{uuid.uuid4()}"
@@ -112,7 +115,7 @@ class OpenAIServingCompletion:
         except Exception as e:
             error_msg = f"OpenAIServingCompletion create_completion: {e}, {str(traceback.format_exc())}"
             api_server_logger.error(error_msg)
-            return ErrorResponse(message=error_msg, code=400)
+            return ErrorResponse(error=ErrorInfo(message=error_msg, type=ErrorType.SERVER_ERROR))
 
         if request_prompt_ids is not None:
             request_prompts = request_prompt_ids
@@ -132,7 +135,9 @@ class OpenAIServingCompletion:
                 f"max waiting time: {self.max_waiting_time}"
             )
             api_server_logger.error(error_msg)
-            return ErrorResponse(code=408, message=error_msg)
+            return ErrorResponse(
+                error=ErrorInfo(message=error_msg, code=ErrorCode.TIMEOUT, type=ErrorType.TIMEOUT_ERROR)
+            )
 
         try:
             try:
@@ -146,11 +151,17 @@ class OpenAIServingCompletion:
                     text_after_process_list.append(current_req_dict.get("text_after_process"))
                     prompt_batched_token_ids.append(prompt_token_ids)
                     del current_req_dict
+            except ParameterError as e:
+                api_server_logger.error(e.message)
+                self.engine_client.semaphore.release()
+                return ErrorResponse(code=400, message=str(e.message), type="invalid_request", param=e.param)
             except Exception as e:
                 error_msg = f"OpenAIServingCompletion format error: {e}, {str(traceback.format_exc())}"
                 api_server_logger.error(error_msg)
                 self.engine_client.semaphore.release()
-                return ErrorResponse(message=str(e), code=400)
+                return ErrorResponse(
+                    error=ErrorInfo(message=str(e), code=ErrorCode.INVALID_VALUE, type=ErrorType.INVALID_REQUEST_ERROR)
+                )
 
             if request.stream:
                 return self.completion_stream_generator(
@@ -178,12 +189,12 @@ class OpenAIServingCompletion:
                         f"OpenAIServingCompletion completion_full_generator error: {e}, {str(traceback.format_exc())}"
                     )
                     api_server_logger.error(error_msg)
-                    return ErrorResponse(code=400, message=error_msg)
+                    return ErrorResponse(error=ErrorInfo(message=error_msg, type=ErrorType.SERVER_ERROR))
 
         except Exception as e:
             error_msg = f"OpenAIServingCompletion create_completion error: {e}, {str(traceback.format_exc())}"
             api_server_logger.error(error_msg)
-            return ErrorResponse(message=error_msg, code=400)
+            return ErrorResponse(error=ErrorInfo(message=error_msg, type=ErrorType.SERVER_ERROR))
 
     async def completion_full_generator(
         self,

fastdeploy/entrypoints/openai/serving_models.py

@@ -18,12 +18,13 @@ from dataclasses import dataclass
 from typing import List, Union
 
 from fastdeploy.entrypoints.openai.protocol import (
+    ErrorInfo,
     ErrorResponse,
     ModelInfo,
     ModelList,
     ModelPermission,
 )
-from fastdeploy.utils import api_server_logger, get_host_ip
+from fastdeploy.utils import ErrorType, api_server_logger, get_host_ip
 
 
 @dataclass
@@ -86,7 +87,7 @@ class OpenAIServingModels:
                 f"Only master node can accept models request, please send request to master node: {self.master_ip}"
             )
             api_server_logger.error(err_msg)
-            return ErrorResponse(message=err_msg, code=400)
+            return ErrorResponse(error=ErrorInfo(message=err_msg, type=ErrorType.SERVER_ERROR))
         model_infos = [
             ModelInfo(
                 id=model.name, max_model_len=self.max_model_len, root=model.model_path, permission=[ModelPermission()]

fastdeploy/utils.py

@@ -28,6 +28,8 @@ import sys
 import tarfile
 import time
 from datetime import datetime
+from enum import Enum
+from http import HTTPStatus
 from importlib.metadata import PackageNotFoundError, distribution
 from logging.handlers import BaseRotatingHandler
 from pathlib import Path
@@ -38,10 +40,14 @@ import paddle
 import requests
 import yaml
 from aistudio_sdk.snapshot_download import snapshot_download as aistudio_download
+from fastapi import Request
+from fastapi.exceptions import RequestValidationError
+from fastapi.responses import JSONResponse
 from tqdm import tqdm
 from typing_extensions import TypeIs, assert_never
 
 from fastdeploy import envs
+from fastdeploy.entrypoints.openai.protocol import ErrorInfo, ErrorResponse
 from fastdeploy.logger.logger import FastDeployLogger
 
 T = TypeVar("T")
@@ -59,6 +65,61 @@ class EngineError(Exception):
         self.error_code = error_code
 
 
+class ParameterError(Exception):
+    def __init__(self, param: str, message: str):
+        self.param = param
+        self.message = message
+        super().__init__(message)
+
+
+class ExceptionHandler:
+
+    # 全局异常兜底处理
+    @staticmethod
+    async def handle_exception(request: Request, exc: Exception) -> JSONResponse:
+        error = ErrorResponse(error=ErrorInfo(message=str(exc), type=ErrorType.INTERNAL_ERROR))
+        return JSONResponse(content=error.model_dump(), status_code=HTTPStatus.INTERNAL_SERVER_ERROR)
+
+    # 处理请求参数验证异常
+    @staticmethod
+    async def handle_request_validation_exception(_: Request, exc: RequestValidationError) -> JSONResponse:
+        errors = exc.errors()
+        if not errors:
+            message = str(exc)
+            param = None
+        else:
+            first_error = errors[0]
+            loc = first_error.get("loc", [])
+            param = loc[-1] if loc else None
+            message = first_error.get("msg", str(exc))
+        err = ErrorResponse(
+            error=ErrorInfo(
+                message=message,
+                type=ErrorType.INVALID_REQUEST_ERROR,
+                code=ErrorCode.MISSING_REQUIRED_PARAMETER if param == "messages" else ErrorCode.INVALID_VALUE,
+                param=param,
+            )
+        )
+        return JSONResponse(content=err.model_dump(), status_code=HTTPStatus.BAD_REQUEST)
+
+
+class ErrorType(str, Enum):
+    INVALID_REQUEST_ERROR = "invalid_request_error"
+    TIMEOUT_ERROR = "timeout_error"
+    SERVER_ERROR = "server_error"
+    INTERNAL_ERROR = "internal_error"
+    API_CONNECTION_ERROR = "api_connection_error"
+
+
+class ErrorCode(str, Enum):
+    INVALID_VALUE = "invalid_value"
+    CONTEXT_LENGTH_EXCEEDED = "context_length_exceeded"
+    MODEL_NOT_SUPPORT = "model_not_support"
+    TIMEOUT = "timeout"
+    CONNECTION_ERROR = "connection_error"
+    MISSING_REQUIRED_PARAMETER = "missing_required_parameter"
+
+
 class ColoredFormatter(logging.Formatter):
     """自定义日志格式器，用于控制台输出带颜色"""
 

tests/ce/server/test_evil_cases.py

@@ -20,9 +20,14 @@ def test_missing_messages_field():
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
 
-    assert "detail" in resp, "返回中未包含 detail 错误信息字段"
-    assert any("messages" in err.get("loc", []) for err in resp["detail"]), "未检测到 messages 字段缺失的报错"
-    assert any("Field required" in err.get("msg", "") for err in resp["detail"]), "未检测到 'Field required' 错误提示"
+    assert "error" in resp, "返回中未包含 error 错误信息字段"
+    error = resp["error"]
+    assert "Field required" in error.get("message", ""), "未检测到 messages 字段缺失的报错"
+    assert error.get("code") == "missing_required_parameter", "code 字段不正确"
+
+    # assert "detail" in resp, "返回中未包含 detail 错误信息字段"
+    # assert any("messages" in err.get("loc", []) for err in resp["detail"]), "未检测到 messages 字段缺失的报错"
+    # assert any("Field required" in err.get("msg", "") for err in resp["detail"]), "未检测到 'Field required' 错误提示"
 
 
 def test_malformed_messages_format():
@@ -34,11 +39,15 @@ def test_malformed_messages_format():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert "detail" in resp, "非法结构未被识别"
-    assert any("messages" in err.get("loc", []) for err in resp["detail"]), "未检测到 messages 字段结构错误"
-    assert any(
-        "Input should be a valid list" in err.get("msg", "") for err in resp["detail"]
-    ), "未检测到 'Input should be a valid list' 错误提示"
+    assert "error" in resp, "非法结构未被识别"
+    err = resp["error"]
+    assert err.get("param") == "list[any]", f"param 字段错误: {err.get('param')}"
+    assert err.get("message") == "Input should be a valid list", "错误提示不符合预期"
+    # assert "detail" in resp, "非法结构未被识别"
+    # assert any("messages" in err.get("loc", []) for err in resp["detail"]), "未检测到 messages 字段结构错误"
+    # assert any(
+    #     "Input should be a valid list" in err.get("msg", "") for err in resp["detail"]
+    # ), "未检测到 'Input should be a valid list' 错误提示"
 
 
 def test_extremely_large_max_tokens():
@@ -79,8 +88,13 @@ def test_top_p_exceed_1():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp.get("detail").get("object") == "error", "top_p > 1 应触发校验异常"
-    assert "top_p value can only be defined" in resp.get("detail").get("message", ""), "未返回预期的 top_p 错误信息"
+    assert "error" in resp, "未返回 error 字段"
+
+    err = resp["error"]
+    assert err.get("param") == "top_p", f"param 字段错误: {err.get('param')}"
+    assert err.get("message") == "Input should be less than or equal to 1", "错误提示不符合预期"
+    # assert resp.get("detail").get("object") == "error", "top_p > 1 应触发校验异常"
+    # assert "top_p value can only be defined" in resp.get("detail").get("message", ""), "未返回预期的 top_p 错误信息"
 
 
 def test_mixed_valid_invalid_fields():
@@ -106,8 +120,8 @@ def test_stop_seq_exceed_num():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp.get("detail").get("object") == "error", "stop 超出个数应触发异常"
-    assert "exceeds the limit max_stop_seqs_num" in resp.get("detail").get("message", ""), "未返回预期的报错信息"
+    assert resp.get("error").get("type") == "invalid_request_error", "stop 超出个数应触发异常"
+    assert "exceeds the limit max_stop_seqs_num" in resp.get("error").get("message", ""), "未返回预期的报错信息"
 
 
 def test_stop_seq_exceed_length():
@@ -120,8 +134,8 @@ def test_stop_seq_exceed_length():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp.get("detail").get("object") == "error", "stop 超出长度应触发异常"
-    assert "exceeds the limit stop_seqs_max_len" in resp.get("detail").get("message", ""), "未返回预期的报错信息"
+    assert resp.get("error").get("type") == "invalid_request_error", "stop 超出长度应触发异常"
+    assert "exceeds the limit stop_seqs_max_len" in resp.get("error").get("message", ""), "未返回预期的报错信息"
 
 
 def test_multilingual_input():
@@ -154,8 +168,8 @@ def test_too_long_input():
     data = {"messages": [{"role": "user", "content": "a，" * 200000}], "stream": False}  # 超过最大输入长度
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp["detail"].get("object") == "error", "超长输入未被识别为错误"
-    assert "Input text is too long" in resp["detail"].get("message", ""), "未检测到最大长度限制错误"
+    # assert resp["detail"].get("object") == "error", "超长输入未被识别为错误"
+    assert "Input text is too long" in resp["error"].get("message", ""), "未检测到最大长度限制错误"
 
 
 def test_empty_input():
@@ -361,8 +375,8 @@ def test_max_tokens_negative():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp.get("detail").get("object") == "error", "max_tokens < 0 未触发校验异常"
-    assert "max_tokens can be defined [1," in resp.get("detail").get("message"), "未返回预期的 max_tokens 错误信息"
+    # assert resp.get("detail").get("object") == "error", "max_tokens < 0 未触发校验异常"
+    assert "max_tokens can be defined [1," in resp.get("error").get("message"), "未返回预期的 max_tokens 错误信息"
 
 
 def test_max_tokens_min():
@@ -379,7 +393,10 @@ def test_max_tokens_min():
     }
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
-    assert resp.get("detail").get("object") == "error", "max_tokens未0时API未拦截住"
+    # assert resp.get("detail").get("object") == "error", "max_tokens未0时API未拦截住"
+    assert "max_tokens can be defined [1," in resp.get("error").get(
+        "message"
+    ), "max_tokens未0时API未拦截住,未返回预期的 max_tokens 错误信息"
 
 
 def test_max_tokens_non_integer():
@@ -397,5 +414,5 @@ def test_max_tokens_non_integer():
     payload = build_request_payload(TEMPLATE, data)
     resp = send_request(URL, payload).json()
     assert (
-        resp.get("detail")[0].get("msg") == "Input should be a valid integer, got a number with a fractional part"
+        resp.get("error").get("message") == "Input should be a valid integer, got a number with a fractional part"
     ), "未返回预期的 max_tokens 为非整数的错误信息"

tests/entrypoints/openai/test_chatcompletion_request.py

@@ -0,0 +1,168 @@
+"""
+# Copyright (c) 2025  PaddlePaddle Authors. All Rights Reserved.
+#
+# Licensed under the Apache License, Version 2.0 (the "License"
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#
+#     http://www.apache.org/licenses/LICENSE-2.0
+#
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+"""
+
+import unittest
+
+from pydantic import ValidationError
+
+from fastdeploy.entrypoints.openai.protocol import (
+    ChatCompletionRequest,
+    CompletionRequest,
+)
+
+
+class TestChatCompletionRequest(unittest.TestCase):
+
+    def test_required_messages(self):
+        with self.assertRaises(ValidationError):
+            ChatCompletionRequest()
+
+    def test_messages_accepts_list_of_any_and_int(self):
+        req = ChatCompletionRequest(messages=[{"role": "user", "content": "hi"}])
+        self.assertEqual(req.messages[0]["role"], "user")
+
+        req = ChatCompletionRequest(messages=[1, 2, 3])
+        self.assertEqual(req.messages, [1, 2, 3])
+
+    def test_default_values(self):
+        req = ChatCompletionRequest(messages=[1])
+        self.assertEqual(req.model, "default")
+        self.assertFalse(req.logprobs)
+        self.assertEqual(req.top_logprobs, 0)
+        self.assertEqual(req.n, 1)
+        self.assertEqual(req.stop, [])
+
+    def test_boundary_values(self):
+        valid_cases = [
+            ("frequency_penalty", -2),
+            ("frequency_penalty", 2),
+            ("presence_penalty", -2),
+            ("presence_penalty", 2),
+            ("temperature", 0),
+            ("top_p", 1),
+            ("seed", 0),
+            ("seed", 922337203685477580),
+        ]
+        for field, value in valid_cases:
+            with self.subTest(field=field, value=value):
+                req = ChatCompletionRequest(messages=[1], **{field: value})
+                self.assertEqual(getattr(req, field), value)
+
+    def test_invalid_boundary_values(self):
+        invalid_cases = [
+            ("frequency_penalty", -3),
+            ("frequency_penalty", 3),
+            ("presence_penalty", -3),
+            ("presence_penalty", 3),
+            ("temperature", -1),
+            ("top_p", 1.1),
+            ("seed", -1),
+            ("seed", 922337203685477581),
+        ]
+        for field, value in invalid_cases:
+            with self.subTest(field=field, value=value):
+                with self.assertRaises(ValidationError):
+                    ChatCompletionRequest(messages=[1], **{field: value})
+
+    def test_stop_field_accepts_str_or_list(self):
+        req1 = ChatCompletionRequest(messages=[1], stop="end")
+        self.assertEqual(req1.stop, "end")
+
+        req2 = ChatCompletionRequest(messages=[1], stop=["a", "b"])
+        self.assertEqual(req2.stop, ["a", "b"])
+
+        with self.assertRaises(ValidationError):
+            ChatCompletionRequest(messages=[1], stop=123)
+
+    def test_deprecated_max_tokens_field(self):
+        req = ChatCompletionRequest(messages=[1], max_tokens=10)
+        self.assertEqual(req.max_tokens, 10)
+
+    def test_field_names_snapshot(self):
+        expected_fields = set(ChatCompletionRequest.__fields__.keys())
+        self.assertEqual(set(ChatCompletionRequest.__fields__.keys()), expected_fields)
+
+
+class TestCompletionRequest(unittest.TestCase):
+
+    def test_required_prompt(self):
+        with self.assertRaises(ValidationError):
+            CompletionRequest()
+
+    def test_prompt_accepts_various_types(self):
+        # str
+        req = CompletionRequest(prompt="hello")
+        self.assertEqual(req.prompt, "hello")
+
+        # list of str
+        req = CompletionRequest(prompt=["hello", "world"])
+        self.assertEqual(req.prompt, ["hello", "world"])
+
+        # list of int
+        req = CompletionRequest(prompt=[1, 2, 3])
+        self.assertEqual(req.prompt, [1, 2, 3])
+
+        # list of list of int
+        req = CompletionRequest(prompt=[[1, 2], [3, 4]])
+        self.assertEqual(req.prompt, [[1, 2], [3, 4]])
+
+    def test_default_values(self):
+        req = CompletionRequest(prompt="test")
+        self.assertEqual(req.model, "default")
+        self.assertEqual(req.echo, False)
+        self.assertEqual(req.temp_scaled_logprobs, False)
+        self.assertEqual(req.top_p_normalized_logprobs, False)
+        self.assertEqual(req.n, 1)
+        self.assertEqual(req.stop, [])
+        self.assertEqual(req.stream, False)
+
+    def test_boundary_values(self):
+        valid_cases = [
+            ("frequency_penalty", -2),
+            ("frequency_penalty", 2),
+            ("presence_penalty", -2),
+            ("presence_penalty", 2),
+            ("temperature", 0),
+            ("top_p", 0),
+            ("top_p", 1),
+            ("seed", 0),
+            ("seed", 922337203685477580),
+        ]
+        for field, value in valid_cases:
+            with self.subTest(field=field, value=value):
+                req = CompletionRequest(prompt="hi", **{field: value})
+                self.assertEqual(getattr(req, field), value)
+
+    def test_invalid_boundary_values(self):
+        invalid_cases = [
+            ("frequency_penalty", -3),
+            ("frequency_penalty", 3),
+            ("presence_penalty", -3),
+            ("presence_penalty", 3),
+            ("temperature", -0.1),
+            ("top_p", -0.1),
+            ("top_p", 1.1),
+            ("seed", -1),
+            ("seed", 922337203685477581),
+        ]
+        for field, value in invalid_cases:
+            with self.subTest(field=field, value=value):
+                with self.assertRaises(ValidationError):
+                    CompletionRequest(prompt="hi", **{field: value})
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/entrypoints/openai/test_error_response.py

@@ -0,0 +1,30 @@
+import unittest
+
+from pydantic import ValidationError
+
+from fastdeploy.entrypoints.openai.protocol import ErrorResponse
+
+
+class TestErrorResponse(unittest.TestCase):
+    def test_valid_error_response(self):
+        data = {
+            "error": {
+                "message": "Invalid top_p value",
+                "type": "invalid_request_error",
+                "param": "top_p",
+                "code": "invalid_value",
+            }
+        }
+        err_resp = ErrorResponse(**data)
+        self.assertEqual(err_resp.error.message, "Invalid top_p value")
+        self.assertEqual(err_resp.error.param, "top_p")
+        self.assertEqual(err_resp.error.code, "invalid_value")
+
+    def test_missing_message_field(self):
+        data = {"error": {"type": "invalid_request_error", "param": "messages", "code": "missing_required_parameter"}}
+        with self.assertRaises(ValidationError):
+            ErrorResponse(**data)
+
+
+if __name__ == "__main__":
+    unittest.main()

tests/utils/test_exception_handler.py

@@ -0,0 +1,54 @@
+import json
+import unittest
+from http import HTTPStatus
+
+from fastapi.exceptions import RequestValidationError
+from fastapi.responses import JSONResponse
+
+from fastdeploy.utils import ErrorCode, ExceptionHandler, ParameterError
+
+
+class TestParameterError(unittest.TestCase):
+    def test_parameter_error_init(self):
+        exc = ParameterError("param1", "error message")
+        self.assertEqual(exc.param, "param1")
+        self.assertEqual(exc.message, "error message")
+        self.assertEqual(str(exc), "error message")
+
+
+class TestExceptionHandler(unittest.IsolatedAsyncioTestCase):
+
+    async def test_handle_exception(self):
+        """普通异常应返回 500 + internal_error"""
+        exc = RuntimeError("Something went wrong")
+        resp: JSONResponse = await ExceptionHandler.handle_exception(None, exc)
+        body = json.loads(resp.body.decode())
+        self.assertEqual(resp.status_code, HTTPStatus.INTERNAL_SERVER_ERROR)
+        self.assertEqual(body["error"]["type"], "internal_error")
+        self.assertIn("Something went wrong", body["error"]["message"])
+
+    async def test_handle_request_validation_missing_messages(self):
+        """缺少 messages 参数时，应返回 missing_required_parameter"""
+        exc = RequestValidationError([{"loc": ("body", "messages"), "msg": "Field required", "type": "missing"}])
+        resp: JSONResponse = await ExceptionHandler.handle_request_validation_exception(None, exc)
+        data = json.loads(resp.body.decode())
+        self.assertEqual(resp.status_code, HTTPStatus.BAD_REQUEST)
+        self.assertEqual(data["error"]["param"], "messages")
+        self.assertEqual(data["error"]["code"], ErrorCode.MISSING_REQUIRED_PARAMETER)
+        self.assertIn("Field required", data["error"]["message"])
+
+    async def test_handle_request_validation_invalid_value(self):
+        """参数非法时，应返回 invalid_value"""
+        exc = RequestValidationError(
+            [{"loc": ("body", "top_p"), "msg": "Input should be less than or equal to 1", "type": "value_error"}]
+        )
+        resp: JSONResponse = await ExceptionHandler.handle_request_validation_exception(None, exc)
+        data = json.loads(resp.body.decode())
+        self.assertEqual(resp.status_code, HTTPStatus.BAD_REQUEST)
+        self.assertEqual(data["error"]["param"], "top_p")
+        self.assertEqual(data["error"]["code"], ErrorCode.INVALID_VALUE)
+        self.assertIn("less than or equal to 1", data["error"]["message"])
+
+
+if __name__ == "__main__":
+    unittest.main()