refactor(api): 优化错误处理和日志记录

对多个模块进行了重构，以改进错误处理和日志记录机制。主要变更包括： - 在 `gemini_routes` 中，现在会返回更具体的错误信息，包括错误码和错误消息，而不仅仅是异常的字符串表示。 - 在 `api_client` 中，简化了 Gemini API 客户端的错误处理逻辑，移除了冗余的 `try...except` 块，让异常直接向上抛出。 - 在多个服务（如 `openai_chat_service`, `embedding_service`, `tts_service` 等）中，增加了根据配置项 `ERROR_LOG_RECORD_REQUEST_BODY` 来决定是否记录请求体的逻辑，以增强隐私和性能控制。 - 在前端 `keys_status.js` 中，更新了密钥验证结果的处理逻辑，以适应后端返回的新的错误对象结构（包含 `error_code` 和 `error_message`），并移除了冗余的 `executeVerifyAllKeys` 函数。
2026-09-07 00:36:36 +08:00 · 2025-09-18 09:59:32 +08:00
parent 68b65814bc
commit 95b5acad66
8 changed files with 103 additions and 195 deletions
@@ -659,7 +659,11 @@ class OpenAIChatService:
                error_type="openai-image-stream",
                error_log=error_log_msg,
                error_code=status_code,
-                request_msg={"image_data_truncated": image_data[:1000]},
+                request_msg=(
+                    {"image_data_truncated": image_data[:1000]}
+                    if settings.ERROR_LOG_RECORD_REQUEST_BODY
+                    else None
+                ),
                request_datetime=request_datetime,
            )
            raise
@@ -709,7 +713,11 @@ class OpenAIChatService:
                error_type="openai-image-non-stream",
                error_log=error_log_msg,
                error_code=status_code,
-                request_msg={"image_data_truncated": image_data[:1000]},
+                request_msg=(
+                    {"image_data_truncated": image_data[:1000]}
+                    if settings.ERROR_LOG_RECORD_REQUEST_BODY
+                    else None
+                ),
                request_datetime=request_datetime,
            )
            raise
@@ -99,34 +99,21 @@ class GeminiApiClient(ApiClient):

        async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
            url = f"{self.base_url}/models/{model}:generateContent?key={api_key}"
+            response = await client.post(url, json=payload, headers=headers)

-            try:
-                response = await client.post(url, json=payload, headers=headers)
+            if response.status_code != 200:
+                error_content = response.text
+                logger.error(
+                    f"API call failed - Status: {response.status_code}, Content: {error_content}"
+                )
+                raise Exception(response.status_code, error_content)
+            response_data = response.json()

-                if response.status_code != 200:
-                    error_content = response.text
-                    logger.error(
-                        f"API call failed - Status: {response.status_code}, Content: {error_content}"
-                    )
-                    raise Exception(response.status_code, error_content)
+            # 检查响应结构的基本信息
+            if not response_data.get("candidates"):
+                logger.warning("No candidates found in API response")

-                response_data = response.json()
-
-                # 检查响应结构的基本信息
-                if not response_data.get("candidates"):
-                    logger.warning("No candidates found in API response")
-
-                return response_data
-
-            except httpx.TimeoutException as e:
-                logger.error(f"Request timeout: {e}")
-                raise Exception(500, f"Request timeout: {e}")
-            except httpx.RequestError as e:
-                logger.error(f"Request error: {e}")
-                raise Exception(500, f"Request error: {e}")
-            except Exception as e:
-                logger.error(f"Unexpected error: {e}")
-                raise Exception(500, f"Unexpected error: {e}")
+            return response_data

    async def stream_generate_content(
        self, payload: Dict[str, Any], model: str, api_key: str
@@ -196,28 +183,14 @@ class GeminiApiClient(ApiClient):
        headers = self._prepare_headers()
        async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
            url = f"{self.base_url}/models/{model}:embedContent?key={api_key}"
-
-            try:
-                response = await client.post(url, json=payload, headers=headers)
-
-                if response.status_code != 200:
-                    error_content = response.text
-                    logger.error(
-                        f"Embedding API call failed - Status: {response.status_code}, Content: {error_content}"
-                    )
-                    raise Exception(response.status_code, error_content)
-
-                return response.json()
-
-            except httpx.TimeoutException as e:
-                logger.error(f"Embedding request timeout: {e}")
-                raise Exception(500, f"Request timeout: {e}")
-            except httpx.RequestError as e:
-                logger.error(f"Embedding request error: {e}")
-                raise Exception(500, f"Request error: {e}")
-            except Exception as e:
-                logger.error(f"Unexpected embedding error: {e}")
-                raise Exception(500, f"Unexpected embedding error: {e}")
+            response = await client.post(url, json=payload, headers=headers)
+            if response.status_code != 200:
+                error_content = response.text
+                logger.error(
+                    f"Embedding API call failed - Status: {response.status_code}, Content: {error_content}"
+                )
+                raise Exception(response.status_code, error_content)
+            return response.json()

    async def batch_embed_contents(
        self, payload: Dict[str, Any], model: str, api_key: str
@@ -237,28 +210,14 @@ class GeminiApiClient(ApiClient):
        headers = self._prepare_headers()
        async with httpx.AsyncClient(timeout=timeout, proxy=proxy_to_use) as client:
            url = f"{self.base_url}/models/{model}:batchEmbedContents?key={api_key}"
-
-            try:
-                response = await client.post(url, json=payload, headers=headers)
-
-                if response.status_code != 200:
-                    error_content = response.text
-                    logger.error(
-                        f"Batch embedding API call failed - Status: {response.status_code}, Content: {error_content}"
-                    )
-                    raise Exception(response.status_code, error_content)
-
-                return response.json()
-
-            except httpx.TimeoutException as e:
-                logger.error(f"Batch embedding request timeout: {e}")
-                raise Exception(500, f"Request timeout: {e}")
-            except httpx.RequestError as e:
-                logger.error(f"Batch embedding request error: {e}")
-                raise Exception(500, f"Request error: {e}")
-            except Exception as e:
-                logger.error(f"Unexpected batch embedding error: {e}")
-                raise Exception(500, f"Unexpected batch embedding error: {e}")
+            response = await client.post(url, json=payload, headers=headers)
+            if response.status_code != 200:
+                error_content = response.text
+                logger.error(
+                    f"Batch embedding API call failed - Status: {response.status_code}, Content: {error_content}"
+                )
+                raise Exception(response.status_code, error_content)
+            return response.json()


 class OpenaiApiClient(ApiClient):
@@ -69,7 +69,11 @@ class EmbeddingService:
                    error_type="openai-embedding",
                    error_log=error_log_msg,
                    error_code=status_code,
-                    request_msg=request_msg_log,
+                    request_msg=(
+                        request_msg_log
+                        if settings.ERROR_LOG_RECORD_REQUEST_BODY
+                        else None
+                    ),
                    request_datetime=request_datetime,
                )
            await add_request_log(
@@ -88,7 +88,7 @@ class OpenAICompatiableService:
                error_type="openai-compatiable-non-stream",
                error_log=error_log_msg,
                error_code=status_code,
-                request_msg=request,
+                request_msg=request if settings.ERROR_LOG_RECORD_REQUEST_BODY else None,
            )
            raise e
        finally:
@@ -3,14 +3,16 @@
 继承自原始聊天服务，添加原生Gemini TTS支持（单人和多人），保持向后兼容
 """

-import time
 import datetime
+import time
 from typing import Any, Dict
-from app.service.chat.gemini_chat_service import GeminiChatService
-from app.service.tts.native.tts_response_handler import TTSResponseHandler
+
+from app.config.config import settings
+from app.database.services import add_error_log, add_request_log
 from app.domain.gemini_models import GeminiRequest
 from app.log.logger import get_gemini_logger
-from app.database.services import add_request_log, add_error_log
+from app.service.chat.gemini_chat_service import GeminiChatService
+from app.service.tts.native.tts_response_handler import TTSResponseHandler

 logger = get_gemini_logger()

@@ -28,7 +30,9 @@ class TTSGeminiChatService(GeminiChatService):
        super().__init__(base_url, key_manager)
        # 使用TTS响应处理器替换原始处理器
        self.response_handler = TTSResponseHandler()
-        logger.info("TTS Gemini Chat Service initialized with multi-speaker TTS support")
+        logger.info(
+            "TTS Gemini Chat Service initialized with multi-speaker TTS support"
+        )

    async def generate_content(
        self, model: str, request: GeminiRequest, api_key: str
@@ -55,7 +59,9 @@ class TTSGeminiChatService(GeminiChatService):
            logger.error(f"TTS API call failed with error: {e}")
            raise

-    async def _handle_tts_request(self, model: str, request: GeminiRequest, api_key: str) -> Dict[str, Any]:
+    async def _handle_tts_request(
+        self, model: str, request: GeminiRequest, api_key: str
+    ) -> Dict[str, Any]:
        """
        处理TTS特定的请求，包含完整的日志记录功能
        """
@@ -89,14 +95,24 @@ class TTSGeminiChatService(GeminiChatService):
            if request.generationConfig:
                # 添加TTS特定字段
                if request.generationConfig.responseModalities:
-                    payload["generationConfig"]["responseModalities"] = request.generationConfig.responseModalities
-                    logger.info(f"Added responseModalities: {request.generationConfig.responseModalities}")
+                    payload["generationConfig"][
+                        "responseModalities"
+                    ] = request.generationConfig.responseModalities
+                    logger.info(
+                        f"Added responseModalities: {request.generationConfig.responseModalities}"
+                    )

                if request.generationConfig.speechConfig:
-                    payload["generationConfig"]["speechConfig"] = request.generationConfig.speechConfig
-                    logger.info(f"Added speechConfig: {request.generationConfig.speechConfig}")
+                    payload["generationConfig"][
+                        "speechConfig"
+                    ] = request.generationConfig.speechConfig
+                    logger.info(
+                        f"Added speechConfig: {request.generationConfig.speechConfig}"
+                    )
            else:
-                logger.warning("No generationConfig found in request, TTS fields may be missing")
+                logger.warning(
+                    "No generationConfig found in request, TTS fields may be missing"
+                )

            logger.info(f"TTS payload before API call: {payload}")

@@ -117,6 +133,7 @@ class TTSGeminiChatService(GeminiChatService):

            # 尝试从错误消息中提取状态码
            import re
+
            match = re.search(r"status code (\d+)", error_msg)
            if match:
                status_code = int(match.group(1))
@@ -130,7 +147,11 @@ class TTSGeminiChatService(GeminiChatService):
                error_type="tts-api-error",
                error_log=error_msg,
                error_code=status_code,
-                request_msg=request.model_dump(exclude_none=False)
+                request_msg=(
+                    request.model_dump(exclude_none=False)
+                    if settings.ERROR_LOG_RECORD_REQUEST_BODY
+                    else None
+                ),
            )

            logger.error(f"TTS API call failed: {error_msg}")
@@ -147,5 +168,5 @@ class TTSGeminiChatService(GeminiChatService):
                is_success=is_success,
                status_code=status_code,
                latency_ms=latency_ms,
-                request_time=request_datetime
+                request_time=request_datetime,
            )
@@ -40,7 +40,7 @@ class TTSService:
        error_log_msg = ""
        try:
            client = genai.Client(api_key=api_key)
-            response =await client.aio.models.generate_content(
+            response = await client.aio.models.generate_content(
                model=settings.TTS_MODEL,
                contents=f"Speak in a {settings.TTS_SPEED} speed voice: {request.input}",
                config={
@@ -48,7 +48,11 @@ class TTSService:
                    "speech_config": {
                        "voice_config": {
                            "prebuilt_voice_config": {
-                                "voice_name": request.voice if request.voice in TTS_VOICE_NAMES else settings.TTS_VOICE_NAME
+                                "voice_name": (
+                                    request.voice
+                                    if request.voice in TTS_VOICE_NAMES
+                                    else settings.TTS_VOICE_NAME
+                                )
                            }
                        }
                    },
@@ -59,7 +63,9 @@ class TTSService:
                and response.candidates[0].content.parts
                and response.candidates[0].content.parts[0].inline_data
            ):
-                raw_audio_data = response.candidates[0].content.parts[0].inline_data.data
+                raw_audio_data = (
+                    response.candidates[0].content.parts[0].inline_data.data
+                )
                is_success = True
                status_code = 200
                return _create_wav_file(raw_audio_data)
@@ -83,13 +89,17 @@ class TTSService:
                    error_type="google-tts",
                    error_log=error_log_msg,
                    error_code=status_code,
-                    request_msg=request.input
-                 )
+                    request_msg=(
+                        request.input
+                        if settings.ERROR_LOG_RECORD_REQUEST_BODY
+                        else None
+                    ),
+                )
            await add_request_log(
                model_name=settings.TTS_MODEL,
                api_key=api_key,
                is_success=is_success,
                status_code=status_code,
                latency_ms=latency_ms,
-                request_time=request_datetime
-            )
+                request_time=request_datetime,
+            )