feat(error_logs): 添加错误日志搜索和日期过滤功能

- 在后端 (`services.py`, `log_routes.py`) 实现按 Gemini 密钥（模糊匹配）、错误类型/内容（模糊匹配）和日期范围（开始/结束日期）过滤错误日志的逻辑。
- 添加新函数 `get_error_logs_count` 以高效获取符合过滤条件的总日志数，用于分页。
- 更新 `/api/logs/errors` API 端点以接受 `key_search`, `error_search`, `start_date`, `end_date` 查询参数。端点现在返回包含过滤后日志和总数的对象。
- 增强前端 (`error_logs.html`, `error_logs.js`, `error_logs.css`)：
    - 添加用于密钥搜索、错误/日志搜索和日期范围选择的输入字段。
    - 实现 JavaScript 逻辑以捕获搜索参数，使用过滤器触发 API 调用，并在新搜索时重置到第一页。
    - 更新表格渲染以显示顺序行号而非数据库 ID。
    - 在表格视图中遮罩 Gemini 密钥（显示前/后 4 个字符）以提高可读性，同时仍在详细信息模态框中显示完整密钥。
    - 优化新搜索控件、表格外观（内边距、边框、悬停效果、斑马条纹）和按钮样式的 CSS，以提供更清晰的用户界面。
- 通过使用 `logger.exception` 包含堆栈跟踪来改进后端服务中的错误日志记录。

app/router/log_routes.py

@@ -1,13 +1,15 @@
 """
 日志路由模块
 """
-from typing import Any, Dict, List
+from typing import Any, Dict, List, Optional
+from datetime import date
+from pydantic import BaseModel
 from fastapi import APIRouter, HTTPException, Request, Query
 from fastapi.responses import RedirectResponse
 
 from app.core.security import verify_auth_token
 from app.log.logger import get_log_routes_logger
-from app.database.services import get_error_logs
+from app.database.services import get_error_logs, get_error_logs_count
 
 # 创建路由
 router = APIRouter(prefix="/api/logs", tags=["logs"])
@@ -15,11 +17,20 @@ router = APIRouter(prefix="/api/logs", tags=["logs"])
 logger = get_log_routes_logger()
 
 
-@router.get("/errors", response_model=List[Dict[str, Any]])
+# Define a response model that includes the total count for pagination
+class ErrorLogResponse(BaseModel):
+    logs: List[Dict[str, Any]]
+    total: int
+
+@router.get("/errors", response_model=ErrorLogResponse)
 async def get_error_logs_api(
     request: Request,
-    limit: int = Query(100, ge=1, le=1000),
-    offset: int = Query(0, ge=0)
+    limit: int = Query(20, ge=1, le=1000), # Default to 20 to match frontend
+    offset: int = Query(0, ge=0),
+    key_search: Optional[str] = Query(None, description="Search term for Gemini key (partial match)"),
+    error_search: Optional[str] = Query(None, description="Search term for error type or log message"),
+    start_date: Optional[date] = Query(None, description="Start date for filtering (YYYY-MM-DD)"),
+    end_date: Optional[date] = Query(None, description="End date for filtering (YYYY-MM-DD)")
 ):
     """
     获取错误日志
@@ -30,7 +41,7 @@ async def get_error_logs_api(
         offset: 偏移量
     
     Returns:
-        List[Dict[str, Any]]: 错误日志列表
+        ErrorLogResponse: An object containing the list of logs and the total count.
     """
     auth_token = request.cookies.get("auth_token")
     if not auth_token or not verify_auth_token(auth_token):
@@ -38,8 +49,23 @@ async def get_error_logs_api(
         return RedirectResponse(url="/", status_code=302)
     
     try:
-        logs = await get_error_logs(limit, offset)
-        return logs
+        # Fetch logs with search parameters
+        logs = await get_error_logs(
+            limit=limit,
+            offset=offset,
+            key_search=key_search,
+            error_search=error_search,
+            start_date=start_date,
+            end_date=end_date
+        )
+        # Fetch total count with the same search parameters
+        total_count = await get_error_logs_count(
+            key_search=key_search,
+            error_search=error_search,
+            start_date=start_date,
+            end_date=end_date
+        )
+        return ErrorLogResponse(logs=logs, total=total_count)
     except Exception as e:
-        logger.error(f"Failed to get error logs: {str(e)}")
+        logger.exception(f"Failed to get error logs: {str(e)}") # Use logger.exception for stack trace
         raise HTTPException(status_code=500, detail=f"Failed to get error logs: {str(e)}")