v0.1.0: CRM/ERP 系统内测版本 - 安全加固完成
- Docker bridge 网络隔离（8000 端口封死） - Gunicorn 4 Worker 多进程 - Alembic 数据库迁移基线 - 日志轮转 20m×3 - JWT 密钥 + DB 密码 + CORS 收紧 - 3-2-1 备份链路（NAS + R740-B 冷备） - 连接池 pool_pre_ping + pool_recycle=3600
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hankin
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# -*- coding: utf-8 -*-
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"""
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认证端点
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处理用户登录，签发 JWT 令牌。
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"""
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from fastapi import APIRouter, Depends, HTTPException, status
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.database import get_db
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from app.core.security import create_access_token
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from app.crud.user import authenticate_user
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from app.schemas.user import Token, UserLogin
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router = APIRouter()
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@router.post("/login", response_model=Token, summary="用户登录", tags=["认证"])
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async def login(body: UserLogin, db: AsyncSession = Depends(get_db)):
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"""
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校验用户名密码，成功后签发 JWT access_token。
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前端后续请求需在 Authorization 头携带 Bearer <token>。
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"""
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user = await authenticate_user(db, body.username, body.password)
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if not user:
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raise HTTPException(
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status_code=status.HTTP_401_UNAUTHORIZED,
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detail="用户名或密码错误",
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headers={"WWW-Authenticate": "Bearer"},
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)
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token = create_access_token(subject=user.username, role=user.role)
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return Token(
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access_token=token,
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role=user.role,
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username=user.username,
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)
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# -*- coding: utf-8 -*-
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"""
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健康检查端点
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用于 Nginx/LB 探活和数据库连接状态探测。
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"""
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from fastapi import APIRouter, Depends
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from sqlalchemy import text
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.core.database import get_db
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router = APIRouter()
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@router.get("/health", summary="健康检查", tags=["系统"])
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async def health_check(db: AsyncSession = Depends(get_db)):
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"""
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探测服务与数据库连接是否存活。
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- 数据库可达 → {"status": "healthy", "database": "connected"}
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- 数据库不可达 → {"status": "degraded", "database": "disconnected", "detail": "..."}
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"""
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try:
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await db.execute(text("SELECT 1"))
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return {"status": "healthy", "database": "connected"}
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except Exception as e:
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return {
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"status": "degraded",
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"database": "disconnected",
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"detail": str(e),
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}
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# -*- coding: utf-8 -*-
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"""
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客户沟通日志 API
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POST /api/v1/logs - 提交日志并触发后台 AI 标签提取
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"""
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import uuid
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from fastapi import APIRouter, BackgroundTasks, Depends, HTTPException, status
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from pydantic import BaseModel, Field
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.deps import get_current_user
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from app.core.database import get_db
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from app.models.crm_business import CustomerLog
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from app.services.ai_workflow import process_log_with_ai
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router = APIRouter()
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# ---- 请求/响应模型 ----
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class LogCreate(BaseModel):
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"""提交沟通日志请求"""
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customer_id: uuid.UUID = Field(..., description="关联客户 ID")
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content: str = Field(..., min_length=5, max_length=5000, description="沟通日志内容")
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class LogResponse(BaseModel):
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"""提交成功响应"""
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id: uuid.UUID
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message: str = "日志已提交，AI 正在后台分析标签和待办"
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# ---- 路由 ----
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@router.post(
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"",
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response_model=LogResponse,
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status_code=status.HTTP_200_OK,
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summary="提交客户沟通日志",
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tags=["客户日志"],
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)
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async def create_customer_log(
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body: LogCreate,
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background_tasks: BackgroundTasks,
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db: AsyncSession = Depends(get_db),
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current_user: dict = Depends(get_current_user),
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):
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"""
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接收前端提交的客户沟通日志：
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1. 立即存入 customer_logs 表
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2. 将 AI 标签提取任务加入 BackgroundTasks 后台队列
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3. 立即返回 200 OK（不等待 AI 处理完成）
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AI 后台任务会：
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- 调用 qwen3:14b 分析日志内容
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- 自动提取最多 3 个客户标签 → customer_tags
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- 自动生成 1 个跟进待办 → follow_up_todos
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"""
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# Step 1: 立即写入日志记录
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log = CustomerLog(
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customer_id=body.customer_id,
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content=body.content,
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)
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db.add(log)
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await db.flush()
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await db.refresh(log)
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# Step 2: 将 AI 处理加入后台队列
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# *** 关键：传入 log.id / body.content / body.customer_id 三个值 ***
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# process_log_with_ai 会创建独立的 DB Session，不与当前请求的 db 共享
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background_tasks.add_task(
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process_log_with_ai,
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log_id=log.id,
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content=body.content,
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customer_id=body.customer_id,
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)
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# Step 3: 立即返回（不等待 AI）
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return LogResponse(id=log.id)
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# -*- coding: utf-8 -*-
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"""
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销售复盘报告 API
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GET /api/v1/reports/monthly - 获取当月销售复盘报告 (AI 生成)
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"""
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from fastapi import APIRouter, Depends
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from pydantic import BaseModel
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.api.deps import get_current_user
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from app.core.database import get_db
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from app.services.analytics import generate_monthly_report
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router = APIRouter()
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# ---- 响应模型 ----
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class StageMetric(BaseModel):
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"""单个阶段的统计指标"""
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stage: str
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count: int
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total_amount: float
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class MonthlyReportResponse(BaseModel):
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"""月度复盘报告响应"""
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metrics: list[StageMetric]
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report: str
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# ---- 路由 ----
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@router.get(
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"/monthly",
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response_model=MonthlyReportResponse,
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summary="获取当月销售复盘报告",
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tags=["数据报告"],
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)
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async def get_monthly_report(
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db: AsyncSession = Depends(get_db),
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current_user: dict = Depends(get_current_user),
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):
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"""
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生成当月销售复盘报告：
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1. SQL 预聚合统计各阶段的机会数量和金额
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2. 将真实数据注入 Prompt，调用 qwen3:14b 生成分析报告
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3. 同步返回结构化数据 + AI 报告文本
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注意：此接口为同步等待模式（用户主动触发），
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AI 生成可能需要 10-30 秒，前端应显示加载状态。
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"""
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result = await generate_monthly_report(db)
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return MonthlyReportResponse(**result)
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@@ -0,0 +1,22 @@
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# -*- coding: utf-8 -*-
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"""
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API v1 路由汇总
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所有 v1 版本的子路由在此注册，由 main.py 统一挂载到 /api/v1 前缀。
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"""
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from fastapi import APIRouter
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from app.api.v1.endpoints import auth, health, logs, reports
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api_v1_router = APIRouter()
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# 挂载各业务模块路由
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api_v1_router.include_router(health.router, prefix="", tags=["系统"])
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api_v1_router.include_router(auth.router, prefix="/auth", tags=["认证"])
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api_v1_router.include_router(logs.router, prefix="/logs", tags=["客户日志"])
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api_v1_router.include_router(reports.router, prefix="/reports", tags=["数据报告"])
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# 后续新增模块在此追加，例如:
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# from app.api.v1.endpoints import clients, expenses
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# api_v1_router.include_router(clients.router, prefix="/clients", tags=["客户管理"])
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# api_v1_router.include_router(expenses.router, prefix="/expenses", tags=["报销管理"])
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