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+"""
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+AI MCP Web UI - FastAPI 后端
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+提供聊天界面与 MCP 工具调用的桥梁
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+"""
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+import os
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+import asyncio
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+import uuid
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+import json as json_module
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+from typing import Optional, Dict, List, Any
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+from contextlib import asynccontextmanager
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+
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+from fastapi import FastAPI, Request, HTTPException, Header
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+from fastapi.middleware.cors import CORSMiddleware
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+from fastapi.responses import StreamingResponse, JSONResponse
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+from fastapi.staticfiles import StaticFiles
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+import httpx
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+from anthropic import Anthropic
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+
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+from config import MCP_SERVERS, ANTHROPIC_API_KEY, ANTHROPIC_BASE_URL, ANTHROPIC_MODEL
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+from conversation_manager import ConversationManager
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+from tool_handler import ToolCallHandler
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+
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+
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+# 存储认证会话 (生产环境应使用 Redis 或数据库)
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+auth_sessions: Dict[str, dict] = {}
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+
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+
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+def create_anthropic_client(api_key: str, base_url: str) -> Anthropic:
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+ """
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+ 创建 Anthropic 客户端，支持自定义认证格式
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+
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+ 自定义 API 代理需要 'Authorization: Bearer <token>' 格式，
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+ 而不是 Anthropic SDK 默认的 'x-api-key' header。
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+ """
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+ # 创建自定义 httpx client，设置正确的 Authorization header
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+ http_client = httpx.Client(
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+ headers={"Authorization": f"Bearer {api_key}"},
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+ timeout=120.0
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+ )
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+ return Anthropic(base_url=base_url, http_client=http_client)
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+
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+
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+# 初始化 Claude 客户端（使用自定义认证格式）
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+client = create_anthropic_client(
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+ api_key=ANTHROPIC_API_KEY,
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+ base_url=ANTHROPIC_BASE_URL
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+)
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+
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+
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+@asynccontextmanager
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+async def lifespan(app: FastAPI):
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+ """应用生命周期管理"""
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+ # 启动时执行
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+ print(f"FastAPI 应用启动 - 模型: {ANTHROPIC_MODEL}")
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+ print(f"MCP 服务器: {list(MCP_SERVERS.keys())}")
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+ yield
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+ # 关闭时执行
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+ print("FastAPI 应用关闭")
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+
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+
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+# 创建 FastAPI 应用
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+app = FastAPI(
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+ title="AI MCP Web UI Backend",
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+ description="AI MCP Web UI 后端服务 - 支持 Claude AI 和 MCP 工具调用",
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+ version="2.0.0",
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+ lifespan=lifespan
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+)
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+
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+# CORS 配置
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+app.add_middleware(
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+ CORSMiddleware,
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+ allow_origins=["*"],
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+ allow_credentials=True,
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+ allow_methods=["*"],
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+ allow_headers=["*"],
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+)
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+
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+# 挂载静态文件
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+frontend_path = os.path.join(os.path.dirname(os.path.dirname(__file__)), "frontend")
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+app.mount("/static", StaticFiles(directory=frontend_path), name="static")
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+
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+
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+# ========== 根路由 ==========
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+
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+@app.get("/")
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+async def index():
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+ """返回前端主页"""
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+ from fastapi.responses import FileResponse
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+ index_path = os.path.join(frontend_path, "index.html")
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+ return FileResponse(index_path)
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+
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+
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+# ========== 健康检查 ==========
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+
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+@app.get("/api/health")
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+async def health():
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+ """健康检查端点"""
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+ return {
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+ "status": "ok",
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+ "model": ANTHROPIC_MODEL,
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+ "mcp_servers": list(MCP_SERVERS.keys())
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+ }
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+
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+
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+# ========== 聊天 API ==========
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+
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+@app.post("/api/chat")
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+async def chat(request: Request):
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+ """
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+ 聊天端点 - 接收用户消息，返回 Claude 响应（支持 MCP 工具调用）
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+ """
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+ try:
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+ data = await request.json()
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+ message = data.get('message', '')
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+ conversation_history = data.get('history', [])
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+ session_id = request.headers.get('X-Session-ID')
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+
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+ if not message:
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+ raise HTTPException(status_code=400, detail="Message is required")
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+
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+ # 创建对话管理器
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+ conv_manager = ConversationManager(
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+ api_key=ANTHROPIC_API_KEY,
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+ base_url=ANTHROPIC_BASE_URL,
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+ model=ANTHROPIC_MODEL,
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+ session_id=session_id
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+ )
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+
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+ # 格式化对话历史
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+ formatted_history = ConversationManager.format_history_for_claude(conversation_history)
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+
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+ # 执行多轮对话（自动处理工具调用）
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+ result = await conv_manager.chat(
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+ user_message=message,
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+ conversation_history=formatted_history,
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+ max_turns=5
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+ )
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+
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+ # 提取响应文本
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+ response_text = result.get("response", "")
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+ tool_calls = result.get("tool_calls", [])
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+
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+ return {
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+ "response": response_text,
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+ "model": ANTHROPIC_MODEL,
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+ "tool_calls": tool_calls,
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+ "has_tools": len(tool_calls) > 0
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+ }
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+
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+ except HTTPException:
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+ raise
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+ except Exception as e:
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+ import traceback
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+ return JSONResponse(
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+ status_code=500,
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+ content={
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+ "error": str(e),
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+ "traceback": traceback.format_exc()
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+ }
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+ )
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+
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+
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+async def generate_chat_stream(
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+ message: str,
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+ conversation_history: List[Dict[str, Any]],
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+ session_id: Optional[str]
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+):
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+ """生成 SSE 流式响应的异步生成器"""
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+ try:
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+ # 发送开始事件
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+ yield f"event: start\ndata: {json_module.dumps({'status': 'started'})}\n\n"
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+
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+ # 创建对话管理器
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+ conv_manager = ConversationManager(
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+ api_key=ANTHROPIC_API_KEY,
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+ base_url=ANTHROPIC_BASE_URL,
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+ model=ANTHROPIC_MODEL,
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+ session_id=session_id
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+ )
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+
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+ # 格式化对话历史
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+ formatted_history = ConversationManager.format_history_for_claude(conversation_history)
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+ messages = formatted_history + [{"role": "user", "content": message}]
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+
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+ current_messages = messages
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+ tool_calls_info = []
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+
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+ for turn in range(5): # 最多 5 轮
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+ # 获取可用工具
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+ tools = await conv_manager.get_available_tools()
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+
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+ # 发送工具列表
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+ yield f"event: tools\ndata: {json_module.dumps({'count': len(tools), 'tools': [t['name'] for t in tools[:5]]})}\n\n"
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+
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+ # 调用 Claude API（流式）
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+ if tools:
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+ response_stream = conv_manager.client.messages.create(
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+ model=conv_manager.model,
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+ max_tokens=4096,
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+ messages=current_messages,
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+ tools=tools,
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+ stream=True
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+ )
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+ else:
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+ response_stream = conv_manager.client.messages.create(
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+ model=conv_manager.model,
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+ max_tokens=4096,
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+ messages=current_messages,
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+ stream=True
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+ )
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+
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+ # 处理流式响应
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+ content_blocks = []
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+ tool_use_blocks = []
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+ response_text = ""
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+ current_block_type = None
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+ current_tool_index = -1
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+ partial_json = ""
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+
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+ for event in response_stream:
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+ # 处理内容块开始 - 检查是否是工具调用
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+ if event.type == "content_block_start":
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+ # 检查块的类型
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+ if hasattr(event, "content_block"):
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+ current_block_type = getattr(event.content_block, "type", None)
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+ if current_block_type == "tool_use":
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+ # 这是工具调用块的开始
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+ tool_use_id = getattr(event.content_block, "id", "")
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+ # content_block 包含 name
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+ tool_name = getattr(event.content_block, "name", "")
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+ tool_use_blocks.append({
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+ "type": "tool_use",
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+ "id": tool_use_id,
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+ "name": tool_name,
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+ "input": {}
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+ })
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+ current_tool_index = len(tool_use_blocks) - 1
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+ partial_json = ""
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+
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+ # 处理内容块增量
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+ elif event.type == "content_block_delta":
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+ delta_type = getattr(event.delta, "type", "")
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+
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+ # 文本增量
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+ if delta_type == "text_delta":
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+ text = event.delta.text
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+ response_text += text
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+ yield f"event: token\ndata: {json_module.dumps({'text': text})}\n\n"
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+
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+ # 工具名称增量
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+ elif delta_type == "tool_use_delta":
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+ # 获取工具名称和参数增量
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+ delta_name = getattr(event.delta, "name", None)
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+ delta_input = getattr(event.delta, "input", None)
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+
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+ if current_tool_index >= 0 and current_tool_index < len(tool_use_blocks):
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+ if delta_name is not None:
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+ tool_use_blocks[current_tool_index]["name"] = delta_name
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+ if delta_input is not None:
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+ # 更新输入参数
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+ current_input = tool_use_blocks[current_tool_index]["input"]
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+ if isinstance(delta_input, dict):
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+ current_input.update(delta_input)
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+ tool_use_blocks[current_tool_index]["input"] = current_input
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+
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+ # 工具参数增量 - input_json_delta
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+ elif delta_type == "input_json_delta":
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+ # 累积 partial_json 构建完整参数
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+ partial_json_str = getattr(event.delta, "partial_json", "")
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+ if partial_json_str:
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+ partial_json += partial_json_str
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+ try:
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+ # 尝试解析累积的 JSON
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+ parsed_input = json_module.loads(partial_json)
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+ if current_tool_index >= 0 and current_tool_index < len(tool_use_blocks):
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+ tool_use_blocks[current_tool_index]["input"] = parsed_input
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+ except json_module.JSONDecodeError:
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+ # JSON 还不完整，继续累积
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+ pass
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+
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+ # 处理内容块停止
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+ elif event.type == "content_block_stop":
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+ current_block_type = None
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+ current_tool_index = -1
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+ partial_json = ""
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+
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+ # 如果没有工具调用，发送完成事件
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+ if not tool_use_blocks:
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+ yield f"event: complete\ndata: {json_module.dumps({'response': response_text, 'tool_calls': tool_calls_info})}\n\n"
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+ return
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+
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+ # 处理工具调用
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+ yield f"event: tools_start\ndata: {json_module.dumps({'count': len(tool_use_blocks)})}\n\n"
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+
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+ # 为每个工具调用发送 tool_call 事件
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+ for tool_block in tool_use_blocks:
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+ yield f"event: tool_call\ndata: {json_module.dumps({'tool': tool_block['name'], 'args': tool_block['input'], 'tool_id': tool_block['id']})}\n\n"
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+
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+ tool_results = await conv_manager.tool_handler.process_tool_use_blocks(
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+ tool_use_blocks
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+ )
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+
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+ for tr in tool_results:
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+ tool_name = tr.get("tool_name", "")
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+ tool_result = tr.get("result", {})
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+ tool_use_id = tr.get("tool_use_id", "")
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+
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+ # 发送工具完成事件
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+ if "error" in tool_result:
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+ yield f"event: tool_error\ndata: {json_module.dumps({'tool': tool_name, 'tool_id': tool_use_id, 'error': tool_result['error']})}\n\n"
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+ else:
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+ result_data = tool_result.get('result', '')
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+ # 限制结果长度避免传输过大
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+ if isinstance(result_data, str) and len(result_data) > 500:
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+ result_data = result_data[:500] + '...'
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+ yield f"event: tool_done\ndata: {json_module.dumps({'tool': tool_name, 'tool_id': tool_use_id, 'result': result_data})}\n\n"
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+
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+ tool_calls_info.append({
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+ "tool": tool_name,
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+ "result": tool_result
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+ })
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+
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+ # 构建工具结果消息
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+ tool_result_message = ToolCallHandler.create_tool_result_message(
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+ tool_results
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+ )
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+
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+ # 添加到消息历史
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+ current_messages.append({
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+ "role": "assistant",
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+ "content": content_blocks
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+ })
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+ current_messages.append(tool_result_message)
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+
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+ # 达到最大轮数
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+ yield f"event: complete\ndata: {json_module.dumps({'response': response_text, 'tool_calls': tool_calls_info, 'warning': '达到最大对话轮数'})}\n\n"
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+
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+ except Exception as e:
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+ import traceback
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+ yield f"event: error\ndata: {json_module.dumps({'error': str(e), 'traceback': traceback.format_exc()})}\n\n"
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+
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+
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+@app.post("/api/chat/stream")
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+async def chat_stream(request: Request):
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+ """
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+ 聊天端点 - 流式输出版本（解决超时问题）
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+
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+ 使用 Server-Sent Events (SSE) 实时返回：
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+ 1. Claude 的思考过程
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+ 2. 工具调用状态
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+ 3. 最终响应
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+ """
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+ try:
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+ data = await request.json()
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+ message = data.get('message', '')
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+ conversation_history = data.get('history', [])
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+ session_id = request.headers.get('X-Session-ID')
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+
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+ if not message:
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+ raise HTTPException(status_code=400, detail="Message is required")
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+
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+ return StreamingResponse(
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+ generate_chat_stream(message, conversation_history, session_id),
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+ media_type="text/event-stream",
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+ headers={
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+ 'Cache-Control': 'no-cache',
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+ 'X-Accel-Buffering': 'no' # 禁用 Nginx 缓冲
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+ }
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+ )
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+
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+ except HTTPException:
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+ raise
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+ except Exception as e:
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+ import traceback
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+ return JSONResponse(
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+ status_code=500,
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+ content={
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+ "error": str(e),
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+ "traceback": traceback.format_exc()
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+ }
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+ )
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+
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+
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+# ========== MCP API ==========
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+
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+@app.get("/api/mcp/servers")
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+async def list_mcp_servers():
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+ """获取已配置的 MCP 服务器列表"""
|
|
|
+ servers = []
|
|
|
+ for name, server in MCP_SERVERS.items():
|
|
|
+ servers.append({
|
|
|
+ "id": name,
|
|
|
+ "name": server.get("name", name),
|
|
|
+ "url": server.get("url", ""),
|
|
|
+ "auth_type": server.get("auth_type", "none"),
|
|
|
+ "enabled": server.get("enabled", False)
|
|
|
+ })
|
|
|
+ return {"servers": servers}
|
|
|
+
|
|
|
+
|
|
|
+@app.get("/api/mcp/tools")
|
|
|
+async def list_mcp_tools(x_session_id: Optional[str] = Header(None, alias='X-Session-ID')):
|
|
|
+ """获取可用的 MCP 工具列表"""
|
|
|
+ try:
|
|
|
+ # 使用静态方法获取工具
|
|
|
+ tools = ConversationManager.get_tools(session_id=x_session_id)
|
|
|
+
|
|
|
+ return {
|
|
|
+ "tools": tools,
|
|
|
+ "count": len(tools)
|
|
|
+ }
|
|
|
+ except Exception as e:
|
|
|
+ import traceback
|
|
|
+ return JSONResponse(
|
|
|
+ status_code=500,
|
|
|
+ content={
|
|
|
+ "error": str(e),
|
|
|
+ "traceback": traceback.format_exc(),
|
|
|
+ "tools": []
|
|
|
+ }
|
|
|
+ )
|
|
|
+
|
|
|
+
|
|
|
+# ========== 认证 API ==========
|
|
|
+
|
|
|
+@app.post("/api/auth/login")
|
|
|
+async def login(request: Request):
|
|
|
+ """
|
|
|
+ Novel Platform 用户登录
|
|
|
+ 代理到实际的登录端点并返回 JWT Token
|
|
|
+ """
|
|
|
+ try:
|
|
|
+ data = await request.json()
|
|
|
+ username = data.get('username')
|
|
|
+ password = data.get('password')
|
|
|
+
|
|
|
+ if not username or not password:
|
|
|
+ raise HTTPException(status_code=400, detail="Username and password are required")
|
|
|
+
|
|
|
+ # 查找需要 JWT 认证的 MCP 服务器
|
|
|
+ target_server = None
|
|
|
+ for server_id, config in MCP_SERVERS.items():
|
|
|
+ if config.get('auth_type') == 'jwt' and 'login_url' in config:
|
|
|
+ target_server = config
|
|
|
+ break
|
|
|
+
|
|
|
+ if not target_server:
|
|
|
+ raise HTTPException(status_code=400, detail="No JWT-authenticated server configured")
|
|
|
+
|
|
|
+ # 构建登录 URL
|
|
|
+ base_url = target_server.get('base_url', '')
|
|
|
+ login_path = target_server.get('login_url', '/api/auth/login')
|
|
|
+ login_url = f"{base_url}{login_path}"
|
|
|
+
|
|
|
+ # 调用实际的登录接口（异步版本）
|
|
|
+ async with httpx.AsyncClient(timeout=30.0) as http_client:
|
|
|
+ response = await http_client.post(
|
|
|
+ login_url,
|
|
|
+ json={"username": username, "password": password}
|
|
|
+ )
|
|
|
+
|
|
|
+ if response.status_code == 200:
|
|
|
+ result = response.json()
|
|
|
+ session_id = str(uuid.uuid4())
|
|
|
+
|
|
|
+ # 存储会话信息
|
|
|
+ auth_sessions[session_id] = {
|
|
|
+ "username": username,
|
|
|
+ "token": result.get("token"),
|
|
|
+ "refresh_token": result.get("refresh_token"),
|
|
|
+ "server": target_server.get("name")
|
|
|
+ }
|
|
|
+
|
|
|
+ return {
|
|
|
+ "success": True,
|
|
|
+ "session_id": session_id,
|
|
|
+ "username": username,
|
|
|
+ "server": target_server.get("name"),
|
|
|
+ "token": result.get("token")
|
|
|
+ }
|
|
|
+ else:
|
|
|
+ raise HTTPException(
|
|
|
+ status_code=response.status_code,
|
|
|
+ detail=f"Login failed: {response.text}"
|
|
|
+ )
|
|
|
+
|
|
|
+ except HTTPException:
|
|
|
+ raise
|
|
|
+ except Exception as e:
|
|
|
+ raise HTTPException(status_code=500, detail=str(e))
|
|
|
+
|
|
|
+
|
|
|
+@app.post("/api/auth/admin-login")
|
|
|
+async def admin_login(request: Request):
|
|
|
+ """
|
|
|
+ Novel Platform 管理员登录
|
|
|
+ """
|
|
|
+ try:
|
|
|
+ data = await request.json()
|
|
|
+ username = data.get('username')
|
|
|
+ password = data.get('password')
|
|
|
+
|
|
|
+ if not username or not password:
|
|
|
+ raise HTTPException(status_code=400, detail="Username and password are required")
|
|
|
+
|
|
|
+ # 查找管理员 MCP 服务器
|
|
|
+ target_server = MCP_SERVERS.get('novel-platform-admin')
|
|
|
+ if not target_server:
|
|
|
+ raise HTTPException(status_code=400, detail="Admin server not configured")
|
|
|
+
|
|
|
+ # 构建登录 URL
|
|
|
+ base_url = target_server.get('base_url', '')
|
|
|
+ login_path = target_server.get('login_url', '/api/auth/admin-login')
|
|
|
+ login_url = f"{base_url}{login_path}"
|
|
|
+
|
|
|
+ # 调用实际的登录接口（异步版本）
|
|
|
+ async with httpx.AsyncClient(timeout=30.0) as http_client:
|
|
|
+ response = await http_client.post(
|
|
|
+ login_url,
|
|
|
+ json={"username": username, "password": password}
|
|
|
+ )
|
|
|
+
|
|
|
+ if response.status_code == 200:
|
|
|
+ result = response.json()
|
|
|
+ session_id = str(uuid.uuid4())
|
|
|
+
|
|
|
+ auth_sessions[session_id] = {
|
|
|
+ "username": username,
|
|
|
+ "token": result.get("token"),
|
|
|
+ "refresh_token": result.get("refresh_token"),
|
|
|
+ "server": target_server.get("name"),
|
|
|
+ "role": "admin"
|
|
|
+ }
|
|
|
+
|
|
|
+ return {
|
|
|
+ "success": True,
|
|
|
+ "session_id": session_id,
|
|
|
+ "username": username,
|
|
|
+ "server": target_server.get("name"),
|
|
|
+ "role": "admin",
|
|
|
+ "token": result.get("token")
|
|
|
+ }
|
|
|
+ else:
|
|
|
+ raise HTTPException(
|
|
|
+ status_code=response.status_code,
|
|
|
+ detail=f"Admin login failed: {response.text}"
|
|
|
+ )
|
|
|
+
|
|
|
+ except HTTPException:
|
|
|
+ raise
|
|
|
+ except Exception as e:
|
|
|
+ raise HTTPException(status_code=500, detail=str(e))
|
|
|
+
|
|
|
+
|
|
|
+@app.post("/api/auth/logout")
|
|
|
+async def logout(request: Request):
|
|
|
+ """登出并清除会话"""
|
|
|
+ try:
|
|
|
+ data = await request.json()
|
|
|
+ session_id = data.get('session_id')
|
|
|
+
|
|
|
+ if session_id and session_id in auth_sessions:
|
|
|
+ del auth_sessions[session_id]
|
|
|
+
|
|
|
+ return {"success": True}
|
|
|
+ except Exception as e:
|
|
|
+ raise HTTPException(status_code=500, detail=str(e))
|
|
|
+
|
|
|
+
|
|
|
+@app.get("/api/auth/status")
|
|
|
+async def auth_status(x_session_id: Optional[str] = Header(None, alias='X-Session-ID')):
|
|
|
+ """检查认证状态"""
|
|
|
+ if x_session_id and x_session_id in auth_sessions:
|
|
|
+ session = auth_sessions[x_session_id]
|
|
|
+ return {
|
|
|
+ "authenticated": True,
|
|
|
+ "username": session.get("username"),
|
|
|
+ "server": session.get("server"),
|
|
|
+ "role": session.get("role", "user")
|
|
|
+ }
|
|
|
+
|
|
|
+ return {"authenticated": False}
|
|
|
+
|
|
|
+
|
|
|
+# ========== 主程序入口 ==========
|
|
|
+
|
|
|
+if __name__ == '__main__':
|
|
|
+ import uvicorn
|
|
|
+
|
|
|
+ port = int(os.getenv('PORT', 8080))
|
|
|
+ debug = os.getenv('DEBUG', 'False').lower() == 'true'
|
|
|
+
|
|
|
+ uvicorn.run(
|
|
|
+ "app_fastapi:app",
|
|
|
+ host='0.0.0.0',
|
|
|
+ port=port,
|
|
|
+ reload=debug
|
|
|
+ )
|
Claude AI