style: 统一代码格式并修复格式问题

server/routers/chat_router.py

@@ -228,7 +228,7 @@ async def save_partial_message(conv_mgr, thread_id, full_msg=None, error_message
         extra_metadata = {
             "error_type": error_type,
             "is_error": True,
-            "error_message": error_message or f"发生错误: {error_type}"
+            "error_message": error_message or f"发生错误: {error_type}",
         }
         if full_msg:
             # 保存部分生成的AI消息
@@ -522,10 +522,7 @@ async def chat_agent(
         # Input guard
         if conf.enable_content_guard and await content_guard.check(query):
             yield make_chunk(
-                status="error",
+                status="error", error_type="content_guard_blocked", error_message="输入内容包含敏感词", meta=meta
-                error_type="content_guard_blocked",
-                error_message="输入内容包含敏感词",
-                meta=meta
             )
             return
 
@@ -537,7 +534,7 @@ async def chat_agent(
                 status="error",
                 error_type="agent_error",
                 error_message=f"智能体 {agent_id} 获取失败: {str(e)}",
-                meta=meta
+                meta=meta,
             )
             return
 
@@ -679,12 +676,7 @@ async def chat_agent(
                     error_type=error_type,
                 )
 
-            yield make_chunk(
+            yield make_chunk(status="error", error_type=error_type, error_message=error_msg, meta=meta)
-                status="error",
-                error_type=error_type,
-                error_message=error_msg,
-                meta=meta
-            )
 
     return StreamingResponse(stream_messages(), media_type="application/json")
 
@@ -1043,7 +1035,9 @@ async def create_thread(
 
 
 @chat.get("/threads", response_model=list[ThreadResponse])
-async def list_threads(agent_id: str, db: AsyncSession = Depends(get_db), current_user: User = Depends(get_required_user)):
+async def list_threads(
+    agent_id: str, db: AsyncSession = Depends(get_db), current_user: User = Depends(get_required_user)
+):
     """获取用户的所有对话线程 (使用新存储系统)"""
     assert agent_id, "agent_id 不能为空"
 
@@ -1071,7 +1065,9 @@ async def list_threads(agent_id: str, db: AsyncSession = Depends(get_db), curren
 
 
 @chat.delete("/thread/{thread_id}")
-async def delete_thread(thread_id: str, db: AsyncSession = Depends(get_db), current_user: User = Depends(get_required_user)):
+async def delete_thread(
+    thread_id: str, db: AsyncSession = Depends(get_db), current_user: User = Depends(get_required_user)
+):
     """删除对话线程 (使用新存储系统)"""
     # Use new storage system
     conv_manager = ConversationManager(db)
@@ -1288,7 +1284,9 @@ async def get_message_feedback(
     """Get feedback status for a specific message (for current user)"""
     try:
         # Get user's feedback for this message
-        feedback_result = await db.execute(select(MessageFeedback).filter_by(message_id=message_id, user_id=str(current_user.id)))
+        feedback_result = await db.execute(
+            select(MessageFeedback).filter_by(message_id=message_id, user_id=str(current_user.id))
+        )
         feedback = feedback_result.scalar_one_or_none()
 
         if not feedback:

server/utils/auth_middleware.py

@@ -60,6 +60,7 @@ async def get_current_user(token: str | None = Depends(oauth2_scheme), db: Async
 
     # 查找用户（异步版本）
     from sqlalchemy import select
+
     result = await db.execute(select(User).filter(User.id == user_id))
     user = result.scalar_one_or_none()
     if user is None:
@@ -78,6 +79,7 @@ async def get_required_user(user: User | None = Depends(get_current_user)):
         )
     return user
 
+
 # 获取管理员用户
 async def get_admin_user(current_user: User = Depends(get_required_user)):
     if current_user.role not in ["admin", "superadmin"]:
@@ -87,6 +89,7 @@ async def get_admin_user(current_user: User = Depends(get_required_user)):
         )
     return current_user
 
+
 # 获取超级管理员用户
 async def get_superadmin_user(current_user: User = Depends(get_required_user)):
     if current_user.role != "superadmin":

src/agents/common/mcp.py

@@ -1,13 +1,12 @@
 """MCP Client setup and management for LangGraph ReAct Agent."""
-import os
 
+
+import traceback
 from collections.abc import Callable
 from typing import Any, cast
-import traceback
 
 from langchain_mcp_adapters.client import MultiServerMCPClient
 
-
 from src.utils import logger
 
 # Global MCP tools cache
@@ -37,6 +36,7 @@ MCP_SERVERS = {
     # 更多用法参考：https://xerrors.github.io/Yuxi-Know/latest/advanced/agents-config.html#内置工具与-mcp-集成
 }
 
+
 async def get_mcp_client(
     server_configs: dict[str, Any] | None = None,
 ) -> MultiServerMCPClient | None:

src/agents/deep_agent/context.py

@@ -4,7 +4,6 @@ from dataclasses import dataclass, field
 
 from src.agents.common.context import BaseContext
 
-
 DEEP_PROMPT = """你是一位专家级研究员。你的工作是进行彻底的研究，然后撰写一份精美的报告。
 
 你应该做的第一件事是把原始的用户问题写入 `question.txt`，以便你有一个记录。
@@ -90,6 +89,7 @@ DEEP_PROMPT = """你是一位专家级研究员。你的工作是进行彻底的
 你可以使用一些工具。
 """
 
+
 @dataclass
 class DeepContext(BaseContext):
     """

src/agents/deep_agent/graph.py

@@ -1,7 +1,7 @@
 """Deep Agent - 基于create_deep_agent的深度分析智能体"""
 
 from deepagents import create_deep_agent
-from langchain.agents.middleware import dynamic_prompt, ModelRequest
+from langchain.agents.middleware import ModelRequest, dynamic_prompt
 
 from src.agents.common import BaseAgent, load_chat_model
 from src.agents.common.middlewares import context_based_model, inject_attachment_context
@@ -9,7 +9,6 @@ from src.agents.common.tools import search
 
 from .prompts import DEEP_PROMPT
 
-
 search_tools = [search]
 
 
@@ -54,6 +53,7 @@ def context_aware_prompt(request: ModelRequest) -> str:
     """从 runtime context 动态生成系统提示词"""
     return DEEP_PROMPT + "\n\n\n" + request.runtime.context.system_prompt
 
+
 class DeepAgent(BaseAgent):
     name = "深度分析智能体"
     description = "具备规划、深度分析和子智能体协作能力的智能体，可以处理复杂的多步骤任务"

src/agents/deep_agent/prompts.py

@@ -1,4 +1,3 @@
-
 DEEP_PROMPT = """你是一位专家级研究员。你的工作是进行彻底的研究，然后撰写一份精美的报告。
 
 你应该做的第一件事是把原始的用户问题写入 `question.txt`，以便你有一个记录。

src/agents/reporter/graph.py

@@ -6,13 +6,7 @@ from src.agents.common.middlewares import context_aware_prompt, context_based_mo
 from src.agents.common.toolkits.mysql import get_mysql_tools
 from src.utils import logger
 
-_mcp_servers = {
+_mcp_servers = {"mcp-server-chart": {"command": "npx", "args": ["-y", "@antv/mcp-server-chart"], "transport": "stdio"}}
-    "mcp-server-chart": {
-        "command": "npx",
-        "args": ["-y", "@antv/mcp-server-chart"],
-        "transport": "stdio"
-    }
-}
 
 
 class SqlReporterAgent(BaseAgent):

src/config/static/models.py

@@ -31,6 +31,7 @@ class EmbedModelInfo(BaseModel):
     api_key: str = Field(..., description="API Key 或环境变量名")
     model_id: str | None = Field(None, description="可选的模型 ID")
 
+
 class RerankerInfo(BaseModel):
     """重排序模型配置"""
 

src/knowledge/implementations/milvus.py

@@ -164,6 +164,7 @@ class MilvusKB(KnowledgeBase):
         # 检查是否有 model_id 字段，优先使用 select_embedding_model
         if embed_info and "model_id" in embed_info:
             from src.models.embed import select_embedding_model
+
             return select_embedding_model(embed_info["model_id"])
 
         # 使用原有的逻辑（兼容模式））

src/knowledge/indexing.py

@@ -1,8 +1,8 @@
 import asyncio
 import os
 import re
-import zipfile
 import xml.etree.ElementTree as ET
+import zipfile
 from pathlib import Path
 
 import aiofiles

src/plugins/mineru_parser.py

@@ -159,7 +159,9 @@ class MinerUParser(BaseDocumentProcessor):
                 )
 
             # 检查响应状态
-            logger.debug(f"MinerU 响应状态: {response.status_code}, Content-Type: {response.headers.get('content-type', 'unknown')}")
+            logger.debug(
+                f"MinerU 响应状态: {response.status_code}, Content-Type: {response.headers.get('content-type')}"
+            )
 
             if response.status_code != 200:
                 error_detail = "未知错误"