fix(api): 统一错误日志时间戳并传递 request_datetime

- 统一 add_error_log 的 request_time：优先使用 request_datetime，
  否则使用 datetime.now()，去除 timezone.utc，避免与请求日志时区不一致
- 在 Gemini/OpenAI/Vertex/Embedding 等服务的异常处理处补充传入
  request_datetime，使错误日志与请求日志可一一对应
- stats: 移除失败记录的错误日志时间窗匹配与 error_log_id 附带，降低查询开销
  与误关联风险；建议通过统一时间戳（key + request_time）或独立错误日志
  查询接口完成关联
- 调整部分导入顺序与长行换行等代码风格，无功能改动

BREAKING CHANGE: 统计详情接口不再返回 error_log_id 字段。需要关联错误日志的
客户端请改为基于 key 与 request_time 在错误日志接口中检索。

app/database/services.py

@@ -141,9 +141,7 @@ async def add_error_log(
             model_name=model_name,
             error_code=error_code,
             request_msg=request_msg_json,
-            request_time=(
-                request_datetime if request_datetime else datetime.now(timezone.utc)
-            ),
+            request_time=(request_datetime if request_datetime else datetime.now()),
         )
         await database.execute(query)
         logger.info(f"Added error log for key: {redact_key_for_logging(gemini_key)}")

app/service/chat/gemini_chat_service.py

@@ -1,19 +1,20 @@
 # app/services/chat_service.py
 
+import datetime
 import json
 import re
-import datetime
 import time
 from typing import Any, AsyncGenerator, Dict, List
+
 from app.config.config import settings
 from app.core.constants import GEMINI_2_FLASH_EXP_SAFETY_SETTINGS
+from app.database.services import add_error_log, add_request_log, get_file_api_key
 from app.domain.gemini_models import GeminiRequest
 from app.handler.response_handler import GeminiResponseHandler
 from app.handler.stream_optimizer import gemini_optimizer
 from app.log.logger import get_gemini_logger
 from app.service.client.api_client import GeminiApiClient
 from app.service.key.key_manager import KeyManager
-from app.database.services import add_error_log, add_request_log, get_file_api_key
 from app.utils.helpers import redact_key_for_logging
 
 logger = get_gemini_logger()
@@ -28,6 +29,7 @@ def _has_image_parts(contents: List[Dict[str, Any]]) -> bool:
                     return True
     return False
 
+
 def _extract_file_references(contents: List[Dict[str, Any]]) -> List[str]:
     """從內容中提取文件引用"""
     file_names = []
@@ -42,7 +44,9 @@ def _extract_file_references(contents: List[Dict[str, Any]]) -> List[str]:
                 file_uri = file_data["fileUri"]
                 # 從 URI 中提取文件名
                 # 1. https://generativelanguage.googleapis.com/v1beta/files/{file_id}
-                match = re.match(rf"{re.escape(settings.BASE_URL)}/(files/.*)", file_uri)
+                match = re.match(
+                    rf"{re.escape(settings.BASE_URL)}/(files/.*)", file_uri
+                )
                 if not match:
                     logger.warning(f"Invalid file URI: {file_uri}")
                     continue
@@ -51,19 +55,36 @@ def _extract_file_references(contents: List[Dict[str, Any]]) -> List[str]:
                 logger.info(f"Found file reference: {file_id}")
     return file_names
 
+
 def _clean_json_schema_properties(obj: Any) -> Any:
     """清理JSON Schema中Gemini API不支持的字段"""
     if not isinstance(obj, dict):
         return obj
-    
+
     # Gemini API不支持的JSON Schema字段
     unsupported_fields = {
-        "exclusiveMaximum", "exclusiveMinimum", "const", "examples", 
-        "contentEncoding", "contentMediaType", "if", "then", "else",
-        "allOf", "anyOf", "oneOf", "not", "definitions", "$schema",
-        "$id", "$ref", "$comment", "readOnly", "writeOnly"
+        "exclusiveMaximum",
+        "exclusiveMinimum",
+        "const",
+        "examples",
+        "contentEncoding",
+        "contentMediaType",
+        "if",
+        "then",
+        "else",
+        "allOf",
+        "anyOf",
+        "oneOf",
+        "not",
+        "definitions",
+        "$schema",
+        "$id",
+        "$ref",
+        "$comment",
+        "readOnly",
+        "writeOnly",
     }
-    
+
     cleaned = {}
     for key, value in obj.items():
         if key in unsupported_fields:
@@ -74,13 +95,13 @@ def _clean_json_schema_properties(obj: Any) -> Any:
             cleaned[key] = [_clean_json_schema_properties(item) for item in value]
         else:
             cleaned[key] = value
-    
+
     return cleaned
 
 
 def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
     """构建工具"""
-    
+
     def _has_function_call(contents: List[Dict[str, Any]]) -> bool:
         """检查内容中是否包含 functionCall"""
         if not contents or not isinstance(contents, list):
@@ -95,7 +116,7 @@ def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
                 if isinstance(part, dict) and "functionCall" in part:
                     return True
         return False
-    
+
     def _merge_tools(tools: List[Dict[str, Any]]) -> Dict[str, Any]:
         record = dict()
         for item in tools:
@@ -146,16 +167,18 @@ def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
             and not _has_image_parts(payload.get("contents", []))
         ):
             tool["codeExecution"] = {}
-            
+
         if model.endswith("-search"):
             tool["googleSearch"] = {}
-            
+
         real_model = _get_real_model(model)
         if real_model in settings.URL_CONTEXT_MODELS and settings.URL_CONTEXT_ENABLED:
             tool["urlContext"] = {}
 
     # 解决 "Tool use with function calling is unsupported" 问题
-    if tool.get("functionDeclarations") or _has_function_call(payload.get("contents", [])):
+    if tool.get("functionDeclarations") or _has_function_call(
+        payload.get("contents", [])
+    ):
         tool.pop("googleSearch", None)
         tool.pop("codeExecution", None)
         tool.pop("urlContext", None)
@@ -189,10 +212,16 @@ def _filter_empty_parts(contents: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
 
     filtered_contents = []
     for content in contents:
-        if not content or "parts" not in content or not isinstance(content.get("parts"), list):
+        if (
+            not content
+            or "parts" not in content
+            or not isinstance(content.get("parts"), list)
+        ):
             continue
 
-        valid_parts = [part for part in content["parts"] if isinstance(part, dict) and part]
+        valid_parts = [
+            part for part in content["parts"] if isinstance(part, dict) and part
+        ]
 
         if valid_parts:
             new_content = content.copy()
@@ -241,30 +270,32 @@ def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
     if model.endswith("-image") or model.endswith("-image-generation"):
         payload.pop("systemInstruction")
         payload["generationConfig"]["responseModalities"] = ["Text", "Image"]
-    
+
     # 处理思考配置：优先使用客户端提供的配置，否则使用默认配置
     client_thinking_config = None
     if request.generationConfig and request.generationConfig.thinkingConfig:
         client_thinking_config = request.generationConfig.thinkingConfig
-    
+
     if client_thinking_config is not None:
         # 客户端提供了思考配置，直接使用
         payload["generationConfig"]["thinkingConfig"] = client_thinking_config
     else:
-        # 客户端没有提供思考配置，使用默认配置    
+        # 客户端没有提供思考配置，使用默认配置
         if model.endswith("-non-thinking"):
             if "gemini-2.5-pro" in model:
                 payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 128}
             else:
-                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 0} 
+                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 0}
         elif _get_real_model(model) in settings.THINKING_BUDGET_MAP:
             if settings.SHOW_THINKING_PROCESS:
                 payload["generationConfig"]["thinkingConfig"] = {
-                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model,1000),
-                    "includeThoughts": True
+                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model, 1000),
+                    "includeThoughts": True,
                 }
             else:
-                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": settings.THINKING_BUDGET_MAP.get(model,1000)}
+                payload["generationConfig"]["thinkingConfig"] = {
+                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model, 1000)
+                }
 
     return payload
 
@@ -311,11 +342,15 @@ class GeminiChatService:
             logger.info(f"Request contains file references: {file_names}")
             file_api_key = await get_file_api_key(file_names[0])
             if file_api_key:
-                logger.info(f"Found API key for file {file_names[0]}: {redact_key_for_logging(file_api_key)}")
+                logger.info(
+                    f"Found API key for file {file_names[0]}: {redact_key_for_logging(file_api_key)}"
+                )
                 api_key = file_api_key  # 使用文件的 API key
             else:
-                logger.warning(f"No API key found for file {file_names[0]}, using default key: {redact_key_for_logging(api_key)}")
-        
+                logger.warning(
+                    f"No API key found for file {file_names[0]}, using default key: {redact_key_for_logging(api_key)}"
+                )
+
         payload = _build_payload(model, request)
         start_time = time.perf_counter()
         request_datetime = datetime.datetime.now()
@@ -344,7 +379,8 @@ class GeminiChatService:
                 error_type="gemini-chat-non-stream",
                 error_log=error_log_msg,
                 error_code=status_code,
-                request_msg=payload
+                request_msg=payload,
+                request_datetime=request_datetime,
             )
             raise e
         finally:
@@ -356,7 +392,7 @@ class GeminiChatService:
                 is_success=is_success,
                 status_code=status_code,
                 latency_ms=latency_ms,
-                request_time=request_datetime
+                request_time=request_datetime,
             )
 
     async def count_tokens(
@@ -364,7 +400,9 @@ class GeminiChatService:
     ) -> Dict[str, Any]:
         """计算token数量"""
         # countTokens API只需要contents
-        payload = {"contents": _filter_empty_parts(request.model_dump().get("contents", []))}
+        payload = {
+            "contents": _filter_empty_parts(request.model_dump().get("contents", []))
+        }
         start_time = time.perf_counter()
         request_datetime = datetime.datetime.now()
         is_success = False
@@ -392,7 +430,7 @@ class GeminiChatService:
                 error_type="gemini-count-tokens",
                 error_log=error_log_msg,
                 error_code=status_code,
-                request_msg=payload
+                request_msg=payload,
             )
             raise e
         finally:
@@ -404,7 +442,7 @@ class GeminiChatService:
                 is_success=is_success,
                 status_code=status_code,
                 latency_ms=latency_ms,
-                request_time=request_datetime
+                request_time=request_datetime,
             )
 
     async def stream_generate_content(
@@ -417,11 +455,15 @@ class GeminiChatService:
             logger.info(f"Request contains file references: {file_names}")
             file_api_key = await get_file_api_key(file_names[0])
             if file_api_key:
-                logger.info(f"Found API key for file {file_names[0]}: {redact_key_for_logging(file_api_key)}")
+                logger.info(
+                    f"Found API key for file {file_names[0]}: {redact_key_for_logging(file_api_key)}"
+                )
                 api_key = file_api_key  # 使用文件的 API key
             else:
-                logger.warning(f"No API key found for file {file_names[0]}, using default key: {redact_key_for_logging(api_key)}")
-                
+                logger.warning(
+                    f"No API key found for file {file_names[0]}, using default key: {redact_key_for_logging(api_key)}"
+                )
+
         retries = 0
         max_retries = settings.MAX_RETRIES
         payload = _build_payload(model, request)
@@ -482,20 +524,23 @@ class GeminiChatService:
                     error_type="gemini-chat-stream",
                     error_log=error_log_msg,
                     error_code=status_code,
-                    request_msg=payload
+                    request_msg=payload,
+                    request_datetime=request_datetime,
                 )
 
-                api_key = await self.key_manager.handle_api_failure(current_attempt_key, retries)
+                api_key = await self.key_manager.handle_api_failure(
+                    current_attempt_key, retries
+                )
                 if api_key:
-                    logger.info(f"Switched to new API key: {redact_key_for_logging(api_key)}")
+                    logger.info(
+                        f"Switched to new API key: {redact_key_for_logging(api_key)}"
+                    )
                 else:
                     logger.error(f"No valid API key available after {retries} retries.")
                     break
 
                 if retries >= max_retries:
-                    logger.error(
-                        f"Max retries ({max_retries}) reached for streaming."
-                    )
+                    logger.error(f"Max retries ({max_retries}) reached for streaming.")
                     break
             finally:
                 end_time = time.perf_counter()
@@ -506,5 +551,5 @@ class GeminiChatService:
                     is_success=is_success,
                     status_code=status_code,
                     latency_ms=latency_ms,
-                    request_time=request_datetime
+                    request_time=request_datetime,
                 )

app/service/chat/openai_chat_service.py

@@ -559,6 +559,7 @@ class OpenAIChatService:
                     error_log=error_log_msg,
                     error_code=status_code,
                     request_msg=payload,
+                    request_datetime=request_datetime,
                 )
 
                 if self.key_manager:
@@ -672,6 +673,7 @@ class OpenAIChatService:
                 error_log=error_log_msg,
                 error_code=status_code,
                 request_msg={"image_data_truncated": image_data[:1000]},
+                request_datetime=request_datetime,
             )
             yield f"data: {json.dumps({'error': error_log_msg})}\n\n"
             yield "data: [DONE]\n\n"
@@ -722,6 +724,7 @@ class OpenAIChatService:
                 error_log=error_log_msg,
                 error_code=status_code,
                 request_msg={"image_data_truncated": image_data[:1000]},
+                request_datetime=request_datetime,
             )
             raise e
         finally:

app/service/chat/vertex_express_chat_service.py

@@ -1,19 +1,20 @@
 # app/services/chat_service.py
 
+import datetime
 import json
 import re
-import datetime
 import time
 from typing import Any, AsyncGenerator, Dict, List
+
 from app.config.config import settings
 from app.core.constants import GEMINI_2_FLASH_EXP_SAFETY_SETTINGS
+from app.database.services import add_error_log, add_request_log
 from app.domain.gemini_models import GeminiRequest
 from app.handler.response_handler import GeminiResponseHandler
 from app.handler.stream_optimizer import gemini_optimizer
 from app.log.logger import get_gemini_logger
 from app.service.client.api_client import GeminiApiClient
 from app.service.key.key_manager import KeyManager
-from app.database.services import add_error_log, add_request_log
 from app.utils.helpers import redact_key_for_logging
 
 logger = get_gemini_logger()
@@ -33,15 +34,31 @@ def _clean_json_schema_properties(obj: Any) -> Any:
     """清理JSON Schema中Gemini API不支持的字段"""
     if not isinstance(obj, dict):
         return obj
-    
+
     # Gemini API不支持的JSON Schema字段
     unsupported_fields = {
-        "exclusiveMaximum", "exclusiveMinimum", "const", "examples", 
-        "contentEncoding", "contentMediaType", "if", "then", "else",
-        "allOf", "anyOf", "oneOf", "not", "definitions", "$schema",
-        "$id", "$ref", "$comment", "readOnly", "writeOnly"
+        "exclusiveMaximum",
+        "exclusiveMinimum",
+        "const",
+        "examples",
+        "contentEncoding",
+        "contentMediaType",
+        "if",
+        "then",
+        "else",
+        "allOf",
+        "anyOf",
+        "oneOf",
+        "not",
+        "definitions",
+        "$schema",
+        "$id",
+        "$ref",
+        "$comment",
+        "readOnly",
+        "writeOnly",
     }
-    
+
     cleaned = {}
     for key, value in obj.items():
         if key in unsupported_fields:
@@ -52,13 +69,13 @@ def _clean_json_schema_properties(obj: Any) -> Any:
             cleaned[key] = [_clean_json_schema_properties(item) for item in value]
         else:
             cleaned[key] = value
-    
+
     return cleaned
 
 
 def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
     """构建工具"""
-    
+
     def _has_function_call(contents: List[Dict[str, Any]]) -> bool:
         """检查内容中是否包含 functionCall"""
         if not contents or not isinstance(contents, list):
@@ -73,7 +90,7 @@ def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
                 if isinstance(part, dict) and "functionCall" in part:
                     return True
         return False
-    
+
     def _merge_tools(tools: List[Dict[str, Any]]) -> Dict[str, Any]:
         record = dict()
         for item in tools:
@@ -124,16 +141,18 @@ def _build_tools(model: str, payload: Dict[str, Any]) -> List[Dict[str, Any]]:
             and not _has_image_parts(payload.get("contents", []))
         ):
             tool["codeExecution"] = {}
-            
+
         if model.endswith("-search"):
             tool["googleSearch"] = {}
-            
+
         real_model = _get_real_model(model)
         if real_model in settings.URL_CONTEXT_MODELS and settings.URL_CONTEXT_ENABLED:
             tool["urlContext"] = {}
 
     # 解决 "Tool use with function calling is unsupported" 问题
-    if tool.get("functionDeclarations") or _has_function_call(payload.get("contents", [])):
+    if tool.get("functionDeclarations") or _has_function_call(
+        payload.get("contents", [])
+    ):
         tool.pop("googleSearch", None)
         tool.pop("codeExecution", None)
         tool.pop("urlContext", None)
@@ -167,7 +186,7 @@ def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
         if request.generationConfig.maxOutputTokens is None:
             # 如果未指定最大输出长度，则不传递该字段，解决截断的问题
             request_dict["generationConfig"].pop("maxOutputTokens")
-    
+
     payload = {
         "contents": request_dict.get("contents", []),
         "tools": _build_tools(model, request_dict),
@@ -179,30 +198,32 @@ def _build_payload(model: str, request: GeminiRequest) -> Dict[str, Any]:
     if model.endswith("-image") or model.endswith("-image-generation"):
         payload.pop("systemInstruction")
         payload["generationConfig"]["responseModalities"] = ["Text", "Image"]
-        
+
     # 处理思考配置：优先使用客户端提供的配置，否则使用默认配置
     client_thinking_config = None
     if request.generationConfig and request.generationConfig.thinkingConfig:
         client_thinking_config = request.generationConfig.thinkingConfig
-    
+
     if client_thinking_config is not None:
         # 客户端提供了思考配置，直接使用
         payload["generationConfig"]["thinkingConfig"] = client_thinking_config
     else:
-        # 客户端没有提供思考配置，使用默认配置    
+        # 客户端没有提供思考配置，使用默认配置
         if model.endswith("-non-thinking"):
             if "gemini-2.5-pro" in model:
                 payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 128}
             else:
-                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 0} 
+                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": 0}
         elif _get_real_model(model) in settings.THINKING_BUDGET_MAP:
             if settings.SHOW_THINKING_PROCESS:
                 payload["generationConfig"]["thinkingConfig"] = {
-                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model,1000),
-                    "includeThoughts": True
+                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model, 1000),
+                    "includeThoughts": True,
                 }
             else:
-                payload["generationConfig"]["thinkingConfig"] = {"thinkingBudget": settings.THINKING_BUDGET_MAP.get(model,1000)}
+                payload["generationConfig"]["thinkingConfig"] = {
+                    "thinkingBudget": settings.THINKING_BUDGET_MAP.get(model, 1000)
+                }
 
     return payload
 
@@ -271,7 +292,8 @@ class GeminiChatService:
                 error_type="gemini-chat-non-stream",
                 error_log=error_log_msg,
                 error_code=status_code,
-                request_msg=payload
+                request_msg=payload,
+                request_datetime=request_datetime,
             )
             raise e
         finally:
@@ -283,7 +305,7 @@ class GeminiChatService:
                 is_success=is_success,
                 status_code=status_code,
                 latency_ms=latency_ms,
-                request_time=request_datetime
+                request_time=request_datetime,
             )
 
     async def stream_generate_content(
@@ -301,7 +323,7 @@ class GeminiChatService:
             request_datetime = datetime.datetime.now()
             start_time = time.perf_counter()
             current_attempt_key = api_key
-            final_api_key = current_attempt_key # Update final key used
+            final_api_key = current_attempt_key  # Update final key used
             try:
                 async for line in self.api_client.stream_generate_content(
                     payload, model, current_attempt_key
@@ -350,20 +372,23 @@ class GeminiChatService:
                     error_type="gemini-chat-stream",
                     error_log=error_log_msg,
                     error_code=status_code,
-                    request_msg=payload
+                    request_msg=payload,
+                    request_datetime=request_datetime,
                 )
 
-                api_key = await self.key_manager.handle_api_failure(current_attempt_key, retries)
+                api_key = await self.key_manager.handle_api_failure(
+                    current_attempt_key, retries
+                )
                 if api_key:
-                    logger.info(f"Switched to new API key: {redact_key_for_logging(api_key)}")
+                    logger.info(
+                        f"Switched to new API key: {redact_key_for_logging(api_key)}"
+                    )
                 else:
                     logger.error(f"No valid API key available after {retries} retries.")
                     break
 
                 if retries >= max_retries:
-                    logger.error(
-                        f"Max retries ({max_retries}) reached for streaming."
-                    )
+                    logger.error(f"Max retries ({max_retries}) reached for streaming.")
                     break
             finally:
                 end_time = time.perf_counter()
@@ -374,5 +399,5 @@ class GeminiChatService:
                     is_success=is_success,
                     status_code=status_code,
                     latency_ms=latency_ms,
-                    request_time=request_datetime
+                    request_time=request_datetime,
                 )

app/service/embedding/embedding_service.py

@@ -1,6 +1,6 @@
 import datetime
-import time
 import re
+import time
 from typing import List, Union
 
 import openai
@@ -8,8 +8,8 @@ from openai import APIStatusError
 from openai.types import CreateEmbeddingResponse
 
 from app.config.config import settings
-from app.log.logger import get_embeddings_logger
 from app.database.services import add_error_log, add_request_log
+from app.log.logger import get_embeddings_logger
 
 logger = get_embeddings_logger()
 
@@ -27,12 +27,20 @@ class EmbeddingService:
         response = None
         error_log_msg = ""
         if isinstance(input_text, list):
-            request_msg_log = {"input_truncated": [str(item)[:100] + "..." if len(str(item)) > 100 else str(item) for item in input_text[:5]]}
+            request_msg_log = {
+                "input_truncated": [
+                    str(item)[:100] + "..." if len(str(item)) > 100 else str(item)
+                    for item in input_text[:5]
+                ]
+            }
             if len(input_text) > 5:
-                 request_msg_log["input_truncated"].append("...")
+                request_msg_log["input_truncated"].append("...")
         else:
-            request_msg_log = {"input_truncated": input_text[:1000] + "..." if len(input_text) > 1000 else input_text}
-
+            request_msg_log = {
+                "input_truncated": (
+                    input_text[:1000] + "..." if len(input_text) > 1000 else input_text
+                )
+            }
 
         try:
             client = openai.OpenAI(api_key=api_key, base_url=settings.BASE_URL)
@@ -66,13 +74,14 @@ 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,
+                    request_datetime=request_datetime,
+                )
             await add_request_log(
                 model_name=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,
             )

app/service/embedding/gemini_embedding_service.py

@@ -84,6 +84,7 @@ class GeminiEmbeddingService:
                 error_log=error_log_msg,
                 error_code=status_code,
                 request_msg=payload,
+                request_datetime=request_datetime,
             )
             raise e
         finally:
@@ -133,6 +134,7 @@ class GeminiEmbeddingService:
                 error_log=error_log_msg,
                 error_code=status_code,
                 request_msg=payload,
+                request_datetime=request_datetime,
             )
             raise e
         finally:

app/service/openai_compatiable/openai_compatiable_service.py

@@ -1,4 +1,3 @@
-
 import datetime
 import json
 import re
@@ -11,20 +10,21 @@ from app.database.services import (
     add_request_log,
 )
 from app.domain.openai_models import ChatRequest, ImageGenerationRequest
+from app.log.logger import get_openai_compatible_logger
 from app.service.client.api_client import OpenaiApiClient
 from app.service.key.key_manager import KeyManager
 from app.utils.helpers import redact_key_for_logging
-from app.log.logger import get_openai_compatible_logger
 
 logger = get_openai_compatible_logger()
 
+
 class OpenAICompatiableService:
 
     def __init__(self, base_url: str, key_manager: KeyManager = None):
         self.key_manager = key_manager
         self.base_url = base_url
         self.api_client = OpenaiApiClient(base_url, settings.TIME_OUT)
-        
+
     async def get_models(self, api_key: str) -> Dict[str, Any]:
         return await self.api_client.get_models(api_key)
 
@@ -37,10 +37,12 @@ class OpenAICompatiableService:
         request_dict = request.model_dump()
         # 移除值为null的
         request_dict = {k: v for k, v in request_dict.items() if v is not None}
-        del request_dict["top_k"] # 删除top_k参数，目前不支持该参数
+        del request_dict["top_k"]  # 删除top_k参数，目前不支持该参数
         if request.stream:
             return self._handle_stream_completion(request.model, request_dict, api_key)
-        return await self._handle_normal_completion(request.model, request_dict, api_key)
+        return await self._handle_normal_completion(
+            request.model, request_dict, api_key
+        )
 
     async def generate_images(
         self,
@@ -153,6 +155,7 @@ class OpenAICompatiableService:
                     error_log=error_log_msg,
                     error_code=status_code,
                     request_msg=payload,
+                    request_datetime=request_datetime,
                 )
 
                 if self.key_manager:
@@ -160,15 +163,17 @@ class OpenAICompatiableService:
                         current_attempt_key, retries
                     )
                     if api_key:
-                        logger.info(f"Switched to new API key: {redact_key_for_logging(api_key)}")
+                        logger.info(
+                            f"Switched to new API key: {redact_key_for_logging(api_key)}"
+                        )
                     else:
                         logger.error(
                             f"No valid API key available after {retries} retries."
                         )
-                        break 
+                        break
                 else:
                     logger.error("KeyManager not available for retry logic.")
-                    break 
+                    break
 
                 if retries >= max_retries:
                     logger.error(f"Max retries ({max_retries}) reached for streaming.")
@@ -187,5 +192,3 @@ class OpenAICompatiableService:
                 if not is_success and retries >= max_retries:
                     yield f"data: {json.dumps({'error': 'Streaming failed after retries'})}\n\n"
                     yield "data: [DONE]\n\n"
-                    
-    

app/service/stats/stats_service.py

@@ -178,9 +178,6 @@ class StatsService:
 
             results = await database.fetch_all(query)
 
-            # 为失败调用尝试查找匹配的错误日志ID（时间窗口 +/- 5 分钟）
-            from app.database.models import ErrorLog  # 延迟导入避免循环依赖
-
             details: list[dict] = []
             for row in results:
                 status = "failure"
@@ -196,30 +193,6 @@ class StatsService:
                     "latency_ms": row["latency_ms"],
                 }
 
-                # 如果失败，尝试附带一个相关的错误日志ID，便于前端拉取详情
-                if status == "failure" and row["key"]:
-                    try:
-                        ts = row["timestamp"]
-                        start_win = ts - datetime.timedelta(minutes=5)
-                        end_win = ts + datetime.timedelta(minutes=5)
-                        err_query = (
-                            select(ErrorLog.id)
-                            .where(
-                                ErrorLog.gemini_key == row["key"],
-                                ErrorLog.request_time >= start_win,
-                                ErrorLog.request_time <= end_win,
-                            )
-                            .order_by(ErrorLog.request_time.desc())
-                            .limit(1)
-                        )
-                        err = await database.fetch_one(err_query)
-                        if err:
-                            record["error_log_id"] = err["id"]
-                    except Exception as _e:
-                        logger.debug(
-                            f"No matching error log found for key ending ...{row['key'][-4:] if row['key'] else ''}: {_e}"
-                        )
-
                 details.append(record)
 
             logger.info(
@@ -260,8 +233,6 @@ class StatsService:
 
             results = await database.fetch_all(query)
 
-            from app.database.models import ErrorLog
-
             details: list[dict] = []
             for row in results:
                 status = "failure"
@@ -277,29 +248,6 @@ class StatsService:
                     "latency_ms": row["latency_ms"],
                 }
 
-                if status == "failure" and row["key"]:
-                    try:
-                        ts = row["timestamp"]
-                        start_win = ts - datetime.timedelta(minutes=5)
-                        end_win = ts + datetime.timedelta(minutes=5)
-                        err_query = (
-                            select(ErrorLog.id)
-                            .where(
-                                ErrorLog.gemini_key == row["key"],
-                                ErrorLog.request_time >= start_win,
-                                ErrorLog.request_time < end_win,
-                            )
-                            .order_by(ErrorLog.request_time.desc())
-                            .limit(1)
-                        )
-                        err = await database.fetch_one(err_query)
-                        if err:
-                            record["error_log_id"] = err["id"]
-                    except Exception as _e:
-                        logger.debug(
-                            f"No matching error log found for key ending ...{row['key'][-4:] if row['key'] else ''}: {_e}"
-                        )
-
                 details.append(record)
 
             logger.info(
@@ -312,7 +260,9 @@ class StatsService:
             )
             raise
 
-    async def get_attention_keys_last_24h(self, include_keys: set[str], limit: int = 20, status_code: int = 429) -> list[dict]:
+    async def get_attention_keys_last_24h(
+        self, include_keys: set[str], limit: int = 20, status_code: int = 429
+    ) -> list[dict]:
         """返回最近24小时内指定状态码(默认429)最多的Key列表，仅包含include_keys中的Key。
 
         Returns: [{"key": str, "count": int, "status_code": int}, ...] 按次数降序
@@ -344,7 +294,9 @@ class StatsService:
                 if row["key"]
             ]
         except Exception as e:
-            logger.error(f"Failed to get attention keys ({status_code}) in last 24h: {e}")
+            logger.error(
+                f"Failed to get attention keys ({status_code}) in last 24h: {e}"
+            )
             return []
 
     async def get_key_usage_details_last_24h(self, key: str) -> Union[dict, None]: