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# ===== 项目结构 =====
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# .
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# ├── main.py          # 入口文件
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# ├── routers/         # 路由模块
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# │   ├── chat.py
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# │   ├── history.py
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# │   └── upload.py
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# ├── models/          # 数据模型
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# │   └── schemas.py
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# ├── services/        # 业务逻辑
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# │   └── agent.py
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# └── requirements.txt
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# ===== main.py —— 应用入口 =====
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from fastapi import FastAPI
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from fastapi.middleware.cors import CORSMiddleware
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import uvicorn
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# 创建应用实例
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app = FastAPI(
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    title="AI Agent API",
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    description="提供Agent对话、文档上传、历史查询等功能",
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    version="1.0.0"
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)
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# 跨域配置（前后端分离必备）
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app.add_middleware(
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    CORSMiddleware,
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    allow_origins=["*"],           # 生产环境要严格限制
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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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# 注册路由
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from routers import chat, history, upload
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app.include_router(chat.router, prefix="/api/v1")
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app.include_router(history.router, prefix="/api/v1")
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app.include_router(upload.router, prefix="/api/v1")
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@app.get("/health")
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async def health_check():
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    return {"status": "ok", "service": "AI Agent API"}
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if __name__ == "__main__":
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    uvicorn.run("main:app", host="0.0.0.0", port=8000, reload=True)
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# 解释：uvicorn是ASGI服务器，reload=True开发时改代码自动重启
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# ===== routers/chat.py —— 对话接口（最核心） =====
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from fastapi import APIRouter, HTTPException
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from pydantic import BaseModel
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from typing import Optional
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from services.agent import run_agent
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router = APIRouter()
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# 请求体模型（Pydantic自动校验）
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class ChatRequest(BaseModel):
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    message: str
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    session_id: Optional[str] = None
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    stream: bool = False
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class ChatResponse(BaseModel):
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    answer: str
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    session_id: str
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@router.post("/chat", response_model=ChatResponse)
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async def chat(request: ChatRequest):
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    try:
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        answer, session_id = await run_agent(
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            message=request.message,
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            session_id=request.session_id
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        )
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        return ChatResponse(answer=answer, session_id=session_id)
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    except Exception as e:
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        raise HTTPException(status_code=500, detail=str(e))
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# 解释：APIRouter把路由模块化，Pydantic自动做请求校验和文档生成
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# async/await让接口在调用LLM时不会阻塞其他请求
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# ===== services/agent.py —— Agent逻辑封装 =====
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from langgraph.graph import StateGraph, END
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# ...（你的Agent代码，见速通03）
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async def run_agent(message: str, session_id: str = None):
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    """包装Agent调用为异步函数"""
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    # 这里是同步代码的话，用run_in_executor避免阻塞事件循环
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    import asyncio
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    loop = asyncio.get_event_loop()
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    result = await loop.run_in_executor(None, lambda: agent.invoke({
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        "messages": [{"role": "user", "content": message}]
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    }))
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    return result["final_answer"], session_id
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# ===== services/upload.py —— 文件上传 =====
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from fastapi import UploadFile, File
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import shutil
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from pathlib import Path
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UPLOAD_DIR = Path("./uploads")
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UPLOAD_DIR.mkdir(exist_ok=True)
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@router.post("/upload")
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async def upload_file(file: UploadFile = File(...)):
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    # 保存文件
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    file_path = UPLOAD_DIR / file.filename
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    with open(file_path, "wb") as buffer:
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        shutil.copyfileobj(file.file, buffer)
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    # 触发RAG索引更新（见RAG速通文档）
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    # await index_document(file_path)
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    return {"filename": file.filename, "status": "indexed"}
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# 解释：UploadFile是FastAPI对文件上传的内置支持