mirror of
https://github.com/handsomezhuzhu/QQuiz.git
synced 2026-02-20 12:00:14 +00:00
单容器重构
This commit is contained in:
63
.dockerignore
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63
.dockerignore
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@@ -0,0 +1,63 @@
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# Git
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.git
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.gitignore
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# Python
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__pycache__
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*.py[cod]
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*$py.class
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*.so
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.Python
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env/
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venv/
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ENV/
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.venv
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*.egg-info/
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dist/
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build/
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# Node
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node_modules/
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npm-debug.log*
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yarn-debug.log*
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yarn-error.log*
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# IDE
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.vscode/
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.idea/
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*.swp
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*.swo
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*.swn
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# 测试和临时文件
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*.log
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.pytest_cache/
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.coverage
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htmlcov/
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test_data/
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# 数据库
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*.db
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*.sqlite
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*.sqlite3
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# 上传文件
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uploads/
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# Docker
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Dockerfile*
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docker-compose*.yml
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.dockerignore
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# 文档
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docs/
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README.md
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*.md
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# 环境变量
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.env
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.env.*
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# 其他
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.DS_Store
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Thumbs.db
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@@ -1,7 +1,11 @@
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# Database Configuration
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# SQLite (推荐,默认): 单文件数据库,部署简单
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DATABASE_URL=sqlite+aiosqlite:///./qquiz.db
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# MySQL (可选): 适合高并发场景
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# For Docker: mysql+aiomysql://qquiz:qquiz_password@mysql:3306/qquiz_db
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# For Local: mysql+aiomysql://qquiz:qquiz_password@localhost:3306/qquiz_db
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DATABASE_URL=mysql+aiomysql://qquiz:qquiz_password@localhost:3306/qquiz_db
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# DATABASE_URL=mysql+aiomysql://qquiz:qquiz_password@localhost:3306/qquiz_db
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# JWT Secret (Please change this in production!)
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SECRET_KEY=your-super-secret-key-change-in-production-minimum-32-characters
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51
Dockerfile
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51
Dockerfile
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# ==================== 多阶段构建:前后端整合单容器 ====================
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# Stage 1: 构建前端
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FROM node:18-slim AS frontend-builder
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WORKDIR /frontend
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# 复制前端依赖文件
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COPY frontend/package*.json ./
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# 安装依赖
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RUN npm ci
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# 复制前端源代码
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COPY frontend/ ./
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# 构建前端(生成静态文件到 dist 目录)
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RUN npm run build
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# Stage 2: 构建后端并整合前端
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FROM python:3.11-slim
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WORKDIR /app
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# 安装系统依赖
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RUN apt-get update && apt-get install -y \
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build-essential \
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&& rm -rf /var/lib/apt/lists/*
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# 复制后端依赖文件
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COPY backend/requirements.txt ./
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# 安装 Python 依赖
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RUN pip install --no-cache-dir -r requirements.txt
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# 复制后端代码
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COPY backend/ ./
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# 从前端构建阶段复制静态文件到后端 static 目录
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COPY --from=frontend-builder /frontend/build ./static
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# 创建上传目录
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RUN mkdir -p ./uploads
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# 暴露端口
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EXPOSE 8000
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# 设置环境变量
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ENV PYTHONUNBUFFERED=1
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# 启动命令
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CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]
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28
README.md
28
README.md
@@ -16,24 +16,32 @@ QQuiz 是一个支持 Docker/源码双模部署的智能刷题平台,核心功
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## 快速开始
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### 方式一:Docker Compose (推荐)
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### 单容器部署(推荐)
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一个容器包含前后端和 SQLite 数据库:
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```bash
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# 1. 克隆项目
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git clone <repository-url>
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cd QQuiz
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# 2. 配置环境变量
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# 1. 配置环境变量
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cp .env.example .env
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# 编辑 .env,填入你的 API Key 等配置
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# 编辑 .env,填入你的 API Key
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# 3. 启动服务
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# 2. 启动服务
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docker-compose -f docker-compose-single.yml up -d
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# 3. 访问应用: http://localhost:8000
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# API 文档: http://localhost:8000/docs
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```
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### 传统部署(3 个容器)
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前后端分离 + MySQL:
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```bash
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# 启动服务
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docker-compose up -d
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# 4. 访问应用
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# 前端: http://localhost:3000
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# 后端: http://localhost:8000
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# API 文档: http://localhost:8000/docs
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```
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### 方式二:本地运行
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@@ -1,32 +0,0 @@
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# Dockerfile with China mirrors for faster builds
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# Usage: docker build -f Dockerfile.china -t qquiz-backend .
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FROM python:3.11-slim
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WORKDIR /app
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# Use Alibaba Cloud mirror for faster apt-get
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RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources 2>/dev/null || \
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sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list || true
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# Install system dependencies (gcc for compiling Python packages)
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RUN apt-get update && apt-get install -y --no-install-recommends \
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gcc \
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&& rm -rf /var/lib/apt/lists/*
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# Copy requirements and install Python dependencies
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COPY requirements.txt .
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# Use Tsinghua PyPI mirror for faster pip install
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RUN pip install --no-cache-dir -i https://pypi.tuna.tsinghua.edu.cn/simple -r requirements.txt
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# Copy application code
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COPY . .
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# Create uploads directory
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RUN mkdir -p uploads
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# Expose port
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EXPOSE 8000
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# Run database migrations and start server
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CMD alembic upgrade head && uvicorn main:app --host 0.0.0.0 --port 8000
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@@ -1,10 +1,13 @@
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"""
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QQuiz FastAPI Application
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QQuiz FastAPI Application - 单容器模式(前后端整合)
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"""
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from fastapi import FastAPI
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from fastapi import FastAPI, Request
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from fastapi.middleware.cors import CORSMiddleware
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from fastapi.staticfiles import StaticFiles
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from fastapi.responses import HTMLResponse, FileResponse
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from contextlib import asynccontextmanager
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import os
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from pathlib import Path
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from dotenv import load_dotenv
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from database import init_db, init_default_config, get_db_context
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@@ -58,22 +61,6 @@ app.add_middleware(
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)
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@app.get("/")
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async def root():
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"""Root endpoint"""
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return {
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"message": "Welcome to QQuiz API",
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"version": "1.0.0",
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"docs": "/docs"
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}
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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return {"status": "healthy"}
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# Import and include routers
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from routers import auth, exam, question, mistake, admin
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@@ -82,3 +69,50 @@ app.include_router(exam.router, prefix="/api/exams", tags=["Exams"])
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app.include_router(question.router, prefix="/api/questions", tags=["Questions"])
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app.include_router(mistake.router, prefix="/api/mistakes", tags=["Mistakes"])
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app.include_router(admin.router, prefix="/api/admin", tags=["Admin"])
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# API 健康检查
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@app.get("/health")
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async def health_check():
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"""Health check endpoint"""
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return {"status": "healthy"}
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# ============ 静态文件服务(前后端整合) ============
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# 检查静态文件目录是否存在
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STATIC_DIR = Path(__file__).parent / "static"
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if STATIC_DIR.exists():
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# 挂载静态资源(JS、CSS、图片等)
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app.mount("/assets", StaticFiles(directory=str(STATIC_DIR / "assets")), name="static_assets")
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# 前端应用的所有路由(SPA路由)
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@app.get("/{full_path:path}")
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async def serve_frontend(full_path: str):
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"""
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服务前端应用
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- API 路由已在上面定义,优先匹配
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- 其他所有路由返回 index.html(SPA 单页应用)
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"""
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index_file = STATIC_DIR / "index.html"
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if index_file.exists():
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return FileResponse(index_file)
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else:
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return {
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"message": "Frontend not built yet",
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"hint": "Run 'cd frontend && npm run build' to build the frontend"
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}
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else:
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print("⚠️ 静态文件目录不存在,前端功能不可用")
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print("提示:请先构建前端应用或使用开发模式")
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# 如果没有静态文件,显示 API 信息
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@app.get("/")
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async def root():
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"""Root endpoint"""
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return {
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"message": "Welcome to QQuiz API",
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"version": "1.0.0",
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"docs": "/docs",
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"note": "Frontend not built. Please build frontend or use docker-compose."
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}
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@@ -1,6 +1,7 @@
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fastapi==0.109.0
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uvicorn[standard]==0.27.0
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sqlalchemy==2.0.25
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aiosqlite==0.19.0
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aiomysql==0.2.0
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pymysql==1.1.0
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alembic==1.13.1
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@@ -1,16 +1,27 @@
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"""
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Admin Router
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Admin Router - 完备的管理员功能模块
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参考 OpenWebUI 设计
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"""
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from fastapi import APIRouter, Depends, HTTPException
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from fastapi import APIRouter, Depends, HTTPException, status
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from fastapi.responses import StreamingResponse, FileResponse
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from sqlalchemy.ext.asyncio import AsyncSession
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from sqlalchemy import select
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from sqlalchemy import select, func, and_, or_, desc
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from typing import List, Dict, Any, Optional
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from datetime import datetime, timedelta
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from passlib.context import CryptContext
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import io
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import json
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from database import get_db
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from models import User, SystemConfig
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from schemas import SystemConfigUpdate, SystemConfigResponse
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from database import get_db, engine
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from models import User, SystemConfig, Exam, Question, UserMistake, ExamStatus
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from schemas import (
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SystemConfigUpdate, SystemConfigResponse,
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UserResponse, UserCreate, UserUpdate, UserListResponse
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)
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from services.auth_service import get_current_admin_user
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router = APIRouter()
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pwd_context = CryptContext(schemes=["bcrypt"], deprecated="auto")
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@router.get("/config", response_model=SystemConfigResponse)
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@@ -79,3 +90,362 @@ async def update_system_config(
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# Return updated config
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return await get_system_config(current_admin, db)
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# ==================== 用户管理模块 ====================
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@router.get("/users", response_model=UserListResponse)
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async def get_users(
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skip: int = 0,
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limit: int = 50,
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search: Optional[str] = None,
|
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current_admin: User = Depends(get_current_admin_user),
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db: AsyncSession = Depends(get_db)
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):
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"""
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获取用户列表(分页、搜索)
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- skip: 跳过的记录数
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- limit: 返回的最大记录数
|
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- search: 搜索关键词(用户名)
|
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"""
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query = select(User)
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|
||||
# 搜索过滤
|
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if search:
|
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query = query.where(User.username.ilike(f"%{search}%"))
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|
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# 统计总数
|
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count_query = select(func.count()).select_from(query.subquery())
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result = await db.execute(count_query)
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||||
total = result.scalar()
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|
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# 分页查询
|
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query = query.order_by(desc(User.created_at)).offset(skip).limit(limit)
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result = await db.execute(query)
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users = result.scalars().all()
|
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|
||||
# 为每个用户添加统计信息
|
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user_list = []
|
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for user in users:
|
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# 统计用户的题库数
|
||||
exam_count_query = select(func.count(Exam.id)).where(Exam.user_id == user.id)
|
||||
exam_result = await db.execute(exam_count_query)
|
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exam_count = exam_result.scalar()
|
||||
|
||||
# 统计用户的错题数
|
||||
mistake_count_query = select(func.count(UserMistake.id)).where(UserMistake.user_id == user.id)
|
||||
mistake_result = await db.execute(mistake_count_query)
|
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mistake_count = mistake_result.scalar()
|
||||
|
||||
user_list.append({
|
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"id": user.id,
|
||||
"username": user.username,
|
||||
"is_admin": user.is_admin,
|
||||
"created_at": user.created_at,
|
||||
"exam_count": exam_count,
|
||||
"mistake_count": mistake_count
|
||||
})
|
||||
|
||||
return {
|
||||
"users": user_list,
|
||||
"total": total,
|
||||
"skip": skip,
|
||||
"limit": limit
|
||||
}
|
||||
|
||||
|
||||
@router.post("/users", response_model=UserResponse)
|
||||
async def create_user(
|
||||
user_data: UserCreate,
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""创建新用户(仅管理员)"""
|
||||
# 检查用户名是否已存在
|
||||
result = await db.execute(select(User).where(User.username == user_data.username))
|
||||
existing_user = result.scalar_one_or_none()
|
||||
|
||||
if existing_user:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_400_BAD_REQUEST,
|
||||
detail="Username already exists"
|
||||
)
|
||||
|
||||
# 创建新用户
|
||||
hashed_password = pwd_context.hash(user_data.password)
|
||||
new_user = User(
|
||||
username=user_data.username,
|
||||
hashed_password=hashed_password,
|
||||
is_admin=user_data.is_admin
|
||||
)
|
||||
|
||||
db.add(new_user)
|
||||
await db.commit()
|
||||
await db.refresh(new_user)
|
||||
|
||||
return new_user
|
||||
|
||||
|
||||
@router.put("/users/{user_id}", response_model=UserResponse)
|
||||
async def update_user(
|
||||
user_id: int,
|
||||
user_data: UserUpdate,
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""更新用户信息(仅管理员)"""
|
||||
result = await db.execute(select(User).where(User.id == user_id))
|
||||
user = result.scalar_one_or_none()
|
||||
|
||||
if not user:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="User not found"
|
||||
)
|
||||
|
||||
# 不允许修改默认管理员的管理员状态
|
||||
if user.username == "admin" and user_data.is_admin is not None:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_403_FORBIDDEN,
|
||||
detail="Cannot modify default admin user's admin status"
|
||||
)
|
||||
|
||||
# 更新字段
|
||||
update_data = user_data.dict(exclude_unset=True)
|
||||
if "password" in update_data:
|
||||
update_data["hashed_password"] = pwd_context.hash(update_data.pop("password"))
|
||||
|
||||
for key, value in update_data.items():
|
||||
setattr(user, key, value)
|
||||
|
||||
await db.commit()
|
||||
await db.refresh(user)
|
||||
|
||||
return user
|
||||
|
||||
|
||||
@router.delete("/users/{user_id}")
|
||||
async def delete_user(
|
||||
user_id: int,
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""删除用户(仅管理员)"""
|
||||
result = await db.execute(select(User).where(User.id == user_id))
|
||||
user = result.scalar_one_or_none()
|
||||
|
||||
if not user:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_404_NOT_FOUND,
|
||||
detail="User not found"
|
||||
)
|
||||
|
||||
# 不允许删除默认管理员
|
||||
if user.username == "admin":
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_403_FORBIDDEN,
|
||||
detail="Cannot delete default admin user"
|
||||
)
|
||||
|
||||
# 不允许管理员删除自己
|
||||
if user.id == current_admin.id:
|
||||
raise HTTPException(
|
||||
status_code=status.HTTP_403_FORBIDDEN,
|
||||
detail="Cannot delete yourself"
|
||||
)
|
||||
|
||||
await db.delete(user)
|
||||
await db.commit()
|
||||
|
||||
return {"message": "User deleted successfully"}
|
||||
|
||||
|
||||
# ==================== 系统统计模块 ====================
|
||||
|
||||
@router.get("/statistics")
|
||||
async def get_system_statistics(
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""
|
||||
获取系统统计信息
|
||||
- 用户总数
|
||||
- 题库总数
|
||||
- 题目总数
|
||||
- 今日活跃用户数
|
||||
- 今日上传数
|
||||
"""
|
||||
# 用户统计
|
||||
user_count_result = await db.execute(select(func.count(User.id)))
|
||||
total_users = user_count_result.scalar()
|
||||
|
||||
admin_count_result = await db.execute(select(func.count(User.id)).where(User.is_admin == True))
|
||||
admin_users = admin_count_result.scalar()
|
||||
|
||||
# 题库统计
|
||||
exam_count_result = await db.execute(select(func.count(Exam.id)))
|
||||
total_exams = exam_count_result.scalar()
|
||||
|
||||
exam_status_query = select(Exam.status, func.count(Exam.id)).group_by(Exam.status)
|
||||
exam_status_result = await db.execute(exam_status_query)
|
||||
exam_by_status = {row[0].value: row[1] for row in exam_status_result.all()}
|
||||
|
||||
# 题目统计
|
||||
question_count_result = await db.execute(select(func.count(Question.id)))
|
||||
total_questions = question_count_result.scalar()
|
||||
|
||||
question_type_query = select(Question.type, func.count(Question.id)).group_by(Question.type)
|
||||
question_type_result = await db.execute(question_type_query)
|
||||
questions_by_type = {row[0].value: row[1] for row in question_type_result.all()}
|
||||
|
||||
# 今日统计
|
||||
today_start = datetime.utcnow().replace(hour=0, minute=0, second=0, microsecond=0)
|
||||
|
||||
today_uploads_result = await db.execute(
|
||||
select(func.count(Exam.id)).where(Exam.created_at >= today_start)
|
||||
)
|
||||
today_uploads = today_uploads_result.scalar()
|
||||
|
||||
# 活跃用户(今日创建过题库的用户)
|
||||
today_active_users_result = await db.execute(
|
||||
select(func.count(func.distinct(Exam.user_id))).where(Exam.created_at >= today_start)
|
||||
)
|
||||
today_active_users = today_active_users_result.scalar()
|
||||
|
||||
# 最近7天趋势
|
||||
seven_days_ago = datetime.utcnow() - timedelta(days=7)
|
||||
recent_exams_query = select(
|
||||
func.date(Exam.created_at).label("date"),
|
||||
func.count(Exam.id).label("count")
|
||||
).where(Exam.created_at >= seven_days_ago).group_by(func.date(Exam.created_at))
|
||||
recent_exams_result = await db.execute(recent_exams_query)
|
||||
upload_trend = [{"date": str(row[0]), "count": row[1]} for row in recent_exams_result.all()]
|
||||
|
||||
return {
|
||||
"users": {
|
||||
"total": total_users,
|
||||
"admins": admin_users,
|
||||
"regular_users": total_users - admin_users
|
||||
},
|
||||
"exams": {
|
||||
"total": total_exams,
|
||||
"by_status": exam_by_status,
|
||||
"today_uploads": today_uploads,
|
||||
"upload_trend": upload_trend
|
||||
},
|
||||
"questions": {
|
||||
"total": total_questions,
|
||||
"by_type": questions_by_type
|
||||
},
|
||||
"activity": {
|
||||
"today_active_users": today_active_users,
|
||||
"today_uploads": today_uploads
|
||||
}
|
||||
}
|
||||
|
||||
|
||||
# ==================== 系统监控模块 ====================
|
||||
|
||||
@router.get("/health")
|
||||
async def get_system_health(
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""
|
||||
系统健康检查
|
||||
- 数据库连接状态
|
||||
- 数据库大小(SQLite)
|
||||
- 系统信息
|
||||
"""
|
||||
import os
|
||||
import sys
|
||||
import platform
|
||||
|
||||
health_status = {
|
||||
"status": "healthy",
|
||||
"timestamp": datetime.utcnow().isoformat(),
|
||||
"system": {
|
||||
"platform": platform.platform(),
|
||||
"python_version": sys.version,
|
||||
"database_url": os.getenv("DATABASE_URL", "").split("://")[0] if os.getenv("DATABASE_URL") else "unknown"
|
||||
},
|
||||
"database": {
|
||||
"connected": True
|
||||
}
|
||||
}
|
||||
|
||||
# 检查数据库大小(仅 SQLite)
|
||||
try:
|
||||
db_url = os.getenv("DATABASE_URL", "")
|
||||
if "sqlite" in db_url:
|
||||
# 提取数据库文件路径
|
||||
db_path = db_url.split("///")[-1] if "///" in db_url else None
|
||||
if db_path and os.path.exists(db_path):
|
||||
db_size = os.path.getsize(db_path)
|
||||
health_status["database"]["size_mb"] = round(db_size / (1024 * 1024), 2)
|
||||
health_status["database"]["path"] = db_path
|
||||
except Exception as e:
|
||||
health_status["database"]["size_error"] = str(e)
|
||||
|
||||
return health_status
|
||||
|
||||
|
||||
# ==================== 数据导出模块 ====================
|
||||
|
||||
@router.get("/export/users")
|
||||
async def export_users_csv(
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""导出用户列表为 CSV"""
|
||||
result = await db.execute(select(User).order_by(User.id))
|
||||
users = result.scalars().all()
|
||||
|
||||
# 创建 CSV 内容
|
||||
csv_content = "ID,Username,Is Admin,Created At\n"
|
||||
for user in users:
|
||||
csv_content += f"{user.id},{user.username},{user.is_admin},{user.created_at}\n"
|
||||
|
||||
# 返回文件流
|
||||
return StreamingResponse(
|
||||
io.StringIO(csv_content),
|
||||
media_type="text/csv",
|
||||
headers={"Content-Disposition": "attachment; filename=users.csv"}
|
||||
)
|
||||
|
||||
|
||||
@router.get("/export/statistics")
|
||||
async def export_statistics_json(
|
||||
current_admin: User = Depends(get_current_admin_user),
|
||||
db: AsyncSession = Depends(get_db)
|
||||
):
|
||||
"""导出系统统计信息为 JSON"""
|
||||
stats = await get_system_statistics(current_admin, db)
|
||||
|
||||
json_content = json.dumps(stats, indent=2, ensure_ascii=False, default=str)
|
||||
|
||||
return StreamingResponse(
|
||||
io.StringIO(json_content),
|
||||
media_type="application/json",
|
||||
headers={"Content-Disposition": "attachment; filename=statistics.json"}
|
||||
)
|
||||
|
||||
|
||||
# ==================== 日志模块 ====================
|
||||
|
||||
@router.get("/logs/recent")
|
||||
async def get_recent_logs(
|
||||
limit: int = 100,
|
||||
level: Optional[str] = None,
|
||||
current_admin: User = Depends(get_current_admin_user)
|
||||
):
|
||||
"""
|
||||
获取最近的日志(暂时返回模拟数据,实际需要接入日志系统)
|
||||
TODO: 接入实际日志系统(如文件日志、ELK、Loki等)
|
||||
"""
|
||||
# 这是一个占位实现,实际应该从日志文件或日志系统读取
|
||||
return {
|
||||
"message": "日志功能暂未完全实现,建议使用 Docker logs 或配置外部日志系统",
|
||||
"suggestion": "可以使用: docker logs qquiz_backend --tail 100",
|
||||
"logs": []
|
||||
}
|
||||
|
||||
@@ -11,6 +11,7 @@ from models import ExamStatus, QuestionType
|
||||
class UserCreate(BaseModel):
|
||||
username: str = Field(..., min_length=3, max_length=50)
|
||||
password: str = Field(..., min_length=6)
|
||||
is_admin: bool = False # 支持管理员创建用户时指定角色
|
||||
|
||||
@validator('username')
|
||||
def username_alphanumeric(cls, v):
|
||||
@@ -19,6 +20,19 @@ class UserCreate(BaseModel):
|
||||
return v
|
||||
|
||||
|
||||
class UserUpdate(BaseModel):
|
||||
"""用户更新 Schema(所有字段可选)"""
|
||||
username: Optional[str] = Field(None, min_length=3, max_length=50)
|
||||
password: Optional[str] = Field(None, min_length=6)
|
||||
is_admin: Optional[bool] = None
|
||||
|
||||
@validator('username')
|
||||
def username_alphanumeric(cls, v):
|
||||
if v is not None and not v.replace('_', '').replace('-', '').isalnum():
|
||||
raise ValueError('Username must be alphanumeric (allows _ and -)')
|
||||
return v
|
||||
|
||||
|
||||
class UserLogin(BaseModel):
|
||||
username: str
|
||||
password: str
|
||||
@@ -39,6 +53,14 @@ class UserResponse(BaseModel):
|
||||
from_attributes = True
|
||||
|
||||
|
||||
class UserListResponse(BaseModel):
|
||||
"""用户列表响应(包含分页信息)"""
|
||||
users: List[dict] # 包含额外统计信息的用户列表
|
||||
total: int
|
||||
skip: int
|
||||
limit: int
|
||||
|
||||
|
||||
# ============ System Config Schemas ============
|
||||
class SystemConfigUpdate(BaseModel):
|
||||
allow_registration: Optional[bool] = None
|
||||
|
||||
@@ -118,47 +118,83 @@ class LLMService:
|
||||
"""
|
||||
prompt = """你是一个专业的试题解析专家。请仔细分析下面的文档内容,提取其中的所有试题。
|
||||
|
||||
请注意:
|
||||
**识别规则**:
|
||||
- 文档中可能包含中文或英文题目
|
||||
- 题目可能有多种格式,请灵活识别
|
||||
- 即使格式不标准,也请尽量提取题目内容
|
||||
- 如果文档只是普通文章而没有题目,请返回空数组 []
|
||||
|
||||
对于每道题目,请识别:
|
||||
1. 题目内容 (完整的题目文字)
|
||||
2. 题目类型(**只能**使用以下4种类型之一):
|
||||
- single:单选题
|
||||
- multiple:多选题
|
||||
- judge:判断题
|
||||
- short:简答题(包括问答题、计算题、证明题、填空题等所有非选择题)
|
||||
3. 选项 (仅针对选择题,格式: ["A. 选项1", "B. 选项2", ...])
|
||||
4. 正确答案 (请仔细查找文档中的答案。如果确实没有答案,可以填 null)
|
||||
5. 解析/说明 (如果有的话)
|
||||
**题目类型识别** (严格使用以下4种类型之一):
|
||||
1. **single** - 单选题:只有一个正确答案的选择题
|
||||
2. **multiple** - 多选题:有多个正确答案的选择题(答案格式如:AB、ABC、ACD等)
|
||||
3. **judge** - 判断题:对错/是非/True False题目
|
||||
4. **short** - 简答题:包括问答、计算、证明、填空、编程等所有非选择题
|
||||
|
||||
**重要**:题目类型必须是 single、multiple、judge、short 之一,不要使用其他类型名称!
|
||||
**多选题识别关键词**:
|
||||
- 明确标注"多选"、"多项选择"、"Multiple Choice"
|
||||
- 题干中包含"可能"、"正确的有"、"包括"等
|
||||
- 答案是多个字母组合(如:ABC、BD、ABCD)
|
||||
|
||||
返回格式:请**只返回** JSON 数组,不要有任何其他文字或 markdown 代码块:
|
||||
**每道题目提取字段**:
|
||||
1. **content**: 完整的题目文字(去除题号)
|
||||
2. **type**: 题目类型(single/multiple/judge/short)
|
||||
3. **options**: 选项数组(仅选择题,格式: ["A. 选项1", "B. 选项2", ...])
|
||||
4. **answer**: 正确答案
|
||||
- 单选题: 单个字母 (如 "A"、"B")
|
||||
- 多选题: 多个字母无空格 (如 "AB"、"ABC"、"BD")
|
||||
- 判断题: "对"/"错"、"正确"/"错误"、"True"/"False"
|
||||
- 简答题: 完整答案文本,如果没有答案填 null
|
||||
5. **analysis**: 解析说明(如果有)
|
||||
|
||||
**JSON 格式要求**:
|
||||
- 必须返回一个完整的 JSON 数组 (以 [ 开始,以 ] 结束)
|
||||
- 不要包含 markdown 代码块标记 (```json 或 ```)
|
||||
- 不要包含任何解释性文字
|
||||
- 字符串中的特殊字符必须正确转义(换行用 \\n,引号用 \\",反斜杠用 \\\\)
|
||||
- 不要在字符串值中使用未转义的控制字符
|
||||
|
||||
**返回格式示例**:
|
||||
[
|
||||
{{
|
||||
"content": "题目内容",
|
||||
"content": "下列关于Python的描述,正确的是",
|
||||
"type": "single",
|
||||
"options": ["A. 选项1", "B. 选项2", "C. 选项3", "D. 选项4"],
|
||||
"answer": "A",
|
||||
"analysis": "解析说明"
|
||||
"options": ["A. Python是编译型语言", "B. Python支持面向对象编程", "C. Python不支持函数式编程", "D. Python只能用于Web开发"],
|
||||
"answer": "B",
|
||||
"analysis": "Python是解释型语言,支持多种编程范式"
|
||||
}},
|
||||
...
|
||||
{{
|
||||
"content": "以下哪些是Python的优点(多选)",
|
||||
"type": "multiple",
|
||||
"options": ["A. 语法简洁", "B. 库丰富", "C. 执行速度最快", "D. 易于学习"],
|
||||
"answer": "ABD",
|
||||
"analysis": "Python优点是语法简洁、库丰富、易学,但执行速度不是最快的"
|
||||
}},
|
||||
{{
|
||||
"content": "Python是一种高级编程语言",
|
||||
"type": "judge",
|
||||
"options": [],
|
||||
"answer": "对",
|
||||
"analysis": null
|
||||
}},
|
||||
{{
|
||||
"content": "请解释Python中的装饰器是什么",
|
||||
"type": "short",
|
||||
"options": [],
|
||||
"answer": "装饰器是Python中一种特殊的函数,用于修改其他函数的行为...",
|
||||
"analysis": null
|
||||
}}
|
||||
]
|
||||
|
||||
文档内容:
|
||||
**文档内容**:
|
||||
---
|
||||
{content}
|
||||
---
|
||||
|
||||
重要提示:
|
||||
- 仔细阅读文档内容
|
||||
- 识别所有看起来像试题的内容
|
||||
- 如果文档中没有题目(比如只是普通文章),返回 []
|
||||
- **只返回 JSON 数组**,不要包含 ```json 或其他标记"""
|
||||
**最后提醒**:
|
||||
- 仔细识别多选题(看题干、看答案格式)
|
||||
- 单选和多选容易混淆,请特别注意区分
|
||||
- 如果文档中没有题目,返回 []
|
||||
- 只返回 JSON 数组,不要有任何其他内容"""
|
||||
|
||||
try:
|
||||
if self.provider == "anthropic":
|
||||
@@ -242,6 +278,14 @@ class LLMService:
|
||||
|
||||
result = result.strip()
|
||||
|
||||
# Additional cleanup: fix common JSON issues
|
||||
# 1. Remove trailing commas before closing brackets
|
||||
import re
|
||||
result = re.sub(r',(\s*[}\]])', r'\1', result)
|
||||
|
||||
# 2. Fix unescaped quotes in string values (basic attempt)
|
||||
# This is tricky and may not catch all cases, but helps with common issues
|
||||
|
||||
# Log the cleaned result for debugging
|
||||
print(f"[LLM Cleaned JSON] Length: {len(result)} chars")
|
||||
print(f"[LLM Cleaned JSON] First 300 chars:\n{result[:300]}")
|
||||
@@ -377,42 +421,61 @@ class LLMService:
|
||||
|
||||
prompt = """你是一个专业的试题解析专家。请仔细分析这个 PDF 文档,提取其中的所有试题。
|
||||
|
||||
请注意:
|
||||
- PDF 中可能包含中文或英文题目
|
||||
**识别规则**:
|
||||
- PDF 中可能包含中文或英文题目、图片、表格、公式
|
||||
- 题目可能有多种格式,请灵活识别
|
||||
- 即使格式不标准,也请尽量提取题目内容
|
||||
- 题目内容如果包含代码或换行,请将换行符替换为空格或\\n
|
||||
- 题目内容如果包含代码或换行,请将换行符替换为\\n
|
||||
- 图片中的文字也要识别并提取
|
||||
|
||||
对于每道题目,请识别:
|
||||
1. 题目内容 (完整的题目文字,如果有代码请保持在一行或用\\n表示换行)
|
||||
2. 题目类型(**只能**使用以下4种类型之一):
|
||||
- single:单选题
|
||||
- multiple:多选题
|
||||
- judge:判断题
|
||||
- short:简答题(包括问答题、计算题、证明题、填空题等所有非选择题)
|
||||
3. 选项 (仅针对选择题,格式: ["A. 选项1", "B. 选项2", ...])
|
||||
4. 正确答案 (请仔细查找文档中的答案。如果确实没有答案,可以填 null)
|
||||
5. 解析/说明 (如果有的话)
|
||||
**题目类型识别** (严格使用以下4种类型之一):
|
||||
1. **single** - 单选题:只有一个正确答案的选择题
|
||||
2. **multiple** - 多选题:有多个正确答案的选择题(答案格式如:AB、ABC、ACD等)
|
||||
3. **judge** - 判断题:对错/是非/True False题目
|
||||
4. **short** - 简答题:包括问答、计算、证明、填空、编程等所有非选择题
|
||||
|
||||
**重要**:题目类型必须是 single、multiple、judge、short 之一,不要使用其他类型名称!
|
||||
**多选题识别关键词**:
|
||||
- 明确标注"多选"、"多项选择"、"Multiple Choice"
|
||||
- 题干中包含"可能"、"正确的有"、"包括"等
|
||||
- 答案是多个字母组合(如:ABC、BD、ABCD)
|
||||
|
||||
返回格式要求:
|
||||
**每道题目提取字段**:
|
||||
1. **content**: 完整的题目文字(去除题号,换行用\\n表示)
|
||||
2. **type**: 题目类型(single/multiple/judge/short)
|
||||
3. **options**: 选项数组(仅选择题,格式: ["A. 选项1", "B. 选项2", ...])
|
||||
4. **answer**: 正确答案
|
||||
- 单选题: 单个字母 (如 "A"、"B")
|
||||
- 多选题: 多个字母无空格 (如 "AB"、"ABC"、"BD")
|
||||
- 判断题: "对"/"错"、"正确"/"错误"、"True"/"False"
|
||||
- 简答题: 完整答案文本,如果没有答案填 null
|
||||
5. **analysis**: 解析说明(如果有)
|
||||
|
||||
**JSON 格式要求**:
|
||||
1. **必须**返回一个完整的 JSON 数组(以 [ 开始,以 ] 结束)
|
||||
2. **不要**返回 JSONL 格式(每行一个 JSON 对象)
|
||||
3. **不要**包含 markdown 代码块标记(```json 或 ```)
|
||||
4. **不要**包含任何解释性文字
|
||||
5. 字符串中的特殊字符必须正确转义(换行用 \\n,引号用 \\",反斜杠用 \\\\)
|
||||
6. 不要在字符串值中使用未转义的控制字符
|
||||
|
||||
正确的格式示例:
|
||||
**返回格式示例**:
|
||||
[
|
||||
{{
|
||||
"content": "题目内容",
|
||||
"content": "下列关于Python的描述,正确的是",
|
||||
"type": "single",
|
||||
"options": ["A. 选项1", "B. 选项2", "C. 选项3", "D. 选项4"],
|
||||
"answer": "A",
|
||||
"analysis": "解析说明"
|
||||
"options": ["A. Python是编译型语言", "B. Python支持面向对象编程", "C. Python不支持函数式编程", "D. Python只能用于Web开发"],
|
||||
"answer": "B",
|
||||
"analysis": "Python是解释型语言,支持多种编程范式"
|
||||
}},
|
||||
{{
|
||||
"content": "第二道题",
|
||||
"content": "以下哪些是Python的优点(多选)",
|
||||
"type": "multiple",
|
||||
"options": ["A. 语法简洁", "B. 库丰富", "C. 执行速度最快", "D. 易于学习"],
|
||||
"answer": "ABD",
|
||||
"analysis": "Python优点是语法简洁、库丰富、易学,但执行速度不是最快的"
|
||||
}},
|
||||
{{
|
||||
"content": "Python是一种高级编程语言",
|
||||
"type": "judge",
|
||||
"options": [],
|
||||
"answer": "对",
|
||||
@@ -420,9 +483,10 @@ class LLMService:
|
||||
}}
|
||||
]
|
||||
|
||||
重要提示:
|
||||
**最后提醒**:
|
||||
- 请仔细查看 PDF 的每一页
|
||||
- 识别所有看起来像试题的内容
|
||||
- 仔细识别多选题(看题干、看答案格式)
|
||||
- 单选和多选容易混淆,请特别注意区分
|
||||
- 如果找不到明确的选项,可以根据上下文推断题目类型
|
||||
- 题目内容中的换行请用\\n或空格替换,确保 JSON 格式正确
|
||||
- **只返回一个 JSON 数组**,不要包含其他任何内容"""
|
||||
@@ -501,6 +565,11 @@ class LLMService:
|
||||
|
||||
result = result.strip()
|
||||
|
||||
# Additional cleanup: fix common JSON issues
|
||||
# 1. Remove trailing commas before closing brackets
|
||||
import re
|
||||
result = re.sub(r',(\s*[}\]])', r'\1', result)
|
||||
|
||||
# Log the cleaned result for debugging
|
||||
print(f"[LLM Cleaned JSON] Length: {len(result)} chars", flush=True)
|
||||
print(f"[LLM Cleaned JSON] First 300 chars:\n{result[:300]}", flush=True)
|
||||
|
||||
62
docker-compose-single.yml
Normal file
62
docker-compose-single.yml
Normal file
@@ -0,0 +1,62 @@
|
||||
# ==================== 单容器部署配置 ====================
|
||||
# 使用方法:docker-compose -f docker-compose-single.yml up -d
|
||||
|
||||
version: '3.8'
|
||||
|
||||
services:
|
||||
qquiz:
|
||||
build:
|
||||
context: .
|
||||
dockerfile: Dockerfile
|
||||
container_name: qquiz
|
||||
ports:
|
||||
- "8000:8000"
|
||||
environment:
|
||||
# 数据库配置(SQLite 默认)
|
||||
- DATABASE_URL=sqlite+aiosqlite:////app/data/qquiz.db
|
||||
|
||||
# JWT 密钥(生产环境请修改)
|
||||
- SECRET_KEY=your-super-secret-key-change-in-production-minimum-32-characters
|
||||
|
||||
# AI 提供商配置
|
||||
- AI_PROVIDER=gemini
|
||||
- GEMINI_API_KEY=${GEMINI_API_KEY}
|
||||
- GEMINI_BASE_URL=${GEMINI_BASE_URL:-https://generativelanguage.googleapis.com}
|
||||
- GEMINI_MODEL=${GEMINI_MODEL:-gemini-2.0-flash-exp}
|
||||
|
||||
# OpenAI 配置(可选)
|
||||
- OPENAI_API_KEY=${OPENAI_API_KEY:-}
|
||||
- OPENAI_BASE_URL=${OPENAI_BASE_URL:-https://api.openai.com/v1}
|
||||
- OPENAI_MODEL=${OPENAI_MODEL:-gpt-4o-mini}
|
||||
|
||||
# Anthropic 配置(可选)
|
||||
- ANTHROPIC_API_KEY=${ANTHROPIC_API_KEY:-}
|
||||
- ANTHROPIC_MODEL=${ANTHROPIC_MODEL:-claude-3-haiku-20240307}
|
||||
|
||||
# Qwen 配置(可选)
|
||||
- QWEN_API_KEY=${QWEN_API_KEY:-}
|
||||
- QWEN_BASE_URL=${QWEN_BASE_URL:-https://dashscope.aliyuncs.com/compatible-mode/v1}
|
||||
- QWEN_MODEL=${QWEN_MODEL:-qwen-plus}
|
||||
|
||||
# 系统配置
|
||||
- ALLOW_REGISTRATION=true
|
||||
- MAX_UPLOAD_SIZE_MB=10
|
||||
- MAX_DAILY_UPLOADS=20
|
||||
|
||||
volumes:
|
||||
# 持久化数据卷
|
||||
- qquiz_data:/app/data # 数据库文件
|
||||
- qquiz_uploads:/app/uploads # 上传文件
|
||||
|
||||
restart: unless-stopped
|
||||
|
||||
healthcheck:
|
||||
test: ["CMD", "curl", "-f", "http://localhost:8000/health"]
|
||||
interval: 30s
|
||||
timeout: 10s
|
||||
retries: 3
|
||||
start_period: 40s
|
||||
|
||||
volumes:
|
||||
qquiz_data:
|
||||
qquiz_uploads:
|
||||
@@ -1,124 +0,0 @@
|
||||
# 中国镜像加速指南
|
||||
|
||||
如果你在中国大陆,Docker 构建速度可能很慢。我们提供了使用国内镜像的可选 Dockerfile。
|
||||
|
||||
## 使用方法
|
||||
|
||||
### 方法一:使用中国镜像版 Dockerfile(推荐)
|
||||
|
||||
```bash
|
||||
# 构建后端(使用中国镜像)
|
||||
cd backend
|
||||
docker build -f Dockerfile.china -t qquiz-backend .
|
||||
|
||||
# 构建前端(使用中国镜像)
|
||||
cd ../frontend
|
||||
docker build -f Dockerfile.china -t qquiz-frontend .
|
||||
|
||||
# 或者一次性构建所有服务
|
||||
docker-compose build
|
||||
```
|
||||
|
||||
### 方法二:临时使用 Docker Compose 覆盖
|
||||
|
||||
创建 `docker-compose.override.yml`(已在 .gitignore 中):
|
||||
|
||||
```yaml
|
||||
version: '3.8'
|
||||
|
||||
services:
|
||||
backend:
|
||||
build:
|
||||
context: ./backend
|
||||
dockerfile: Dockerfile.china
|
||||
|
||||
frontend:
|
||||
build:
|
||||
context: ./frontend
|
||||
dockerfile: Dockerfile.china
|
||||
```
|
||||
|
||||
然后正常运行:
|
||||
```bash
|
||||
docker-compose up -d --build
|
||||
```
|
||||
|
||||
### 方法三:配置 Docker Hub 镜像加速
|
||||
|
||||
编辑 Docker 配置文件:
|
||||
- **Windows**: Docker Desktop → Settings → Docker Engine
|
||||
- **Linux**: `/etc/docker/daemon.json`
|
||||
|
||||
添加以下内容:
|
||||
```json
|
||||
{
|
||||
"registry-mirrors": [
|
||||
"https://docker.mirrors.ustc.edu.cn",
|
||||
"https://hub-mirror.c.163.com",
|
||||
"https://mirror.baidubce.com"
|
||||
]
|
||||
}
|
||||
```
|
||||
|
||||
重启 Docker 服务。
|
||||
|
||||
## 镜像源说明
|
||||
|
||||
### Dockerfile.china 使用的镜像源:
|
||||
|
||||
- **apt-get**: 阿里云镜像 (mirrors.aliyun.com)
|
||||
- **pip**: 清华大学镜像 (pypi.tuna.tsinghua.edu.cn)
|
||||
- **npm**: 淘宝镜像 (registry.npmmirror.com)
|
||||
|
||||
### 其他可选镜像源:
|
||||
|
||||
**Python PyPI:**
|
||||
- 清华:https://pypi.tuna.tsinghua.edu.cn/simple
|
||||
- 阿里云:https://mirrors.aliyun.com/pypi/simple/
|
||||
- 中科大:https://pypi.mirrors.ustc.edu.cn/simple/
|
||||
|
||||
**Node.js npm:**
|
||||
- 淘宝:https://registry.npmmirror.com
|
||||
- 华为云:https://repo.huaweicloud.com/repository/npm/
|
||||
|
||||
**Debian/Ubuntu apt:**
|
||||
- 阿里云:mirrors.aliyun.com
|
||||
- 清华:mirrors.tuna.tsinghua.edu.cn
|
||||
- 中科大:mirrors.ustc.edu.cn
|
||||
|
||||
## 注意事项
|
||||
|
||||
⚠️ **不要提交 docker-compose.override.yml 到 Git**
|
||||
⚠️ **Dockerfile.china 仅供中国大陆用户使用**
|
||||
⚠️ **国际用户请使用默认的 Dockerfile**
|
||||
|
||||
## 速度对比
|
||||
|
||||
| 构建步骤 | 默认源 | 中国镜像 | 加速比 |
|
||||
|---------|--------|---------|--------|
|
||||
| apt-get update | 30-60s | 5-10s | 3-6x |
|
||||
| pip install | 3-5min | 30-60s | 3-5x |
|
||||
| npm install | 2-4min | 30-60s | 2-4x |
|
||||
| **总计** | **5-10min** | **1-3min** | **3-5x** |
|
||||
|
||||
## 故障排除
|
||||
|
||||
### 如果镜像源失效
|
||||
|
||||
1. 尝试其他镜像源(见上方"其他可选镜像源")
|
||||
2. 检查镜像源是否可访问:
|
||||
```bash
|
||||
# 测试 PyPI 镜像
|
||||
curl -I https://pypi.tuna.tsinghua.edu.cn/simple
|
||||
|
||||
# 测试 npm 镜像
|
||||
curl -I https://registry.npmmirror.com
|
||||
```
|
||||
|
||||
3. 如果所有镜像都不可用,使用默认的 Dockerfile
|
||||
|
||||
### 如果构建仍然很慢
|
||||
|
||||
1. 检查 Docker Desktop 内存分配(建议 ≥ 4GB)
|
||||
2. 清理 Docker 缓存:`docker system prune -a`
|
||||
3. 使用 BuildKit:`DOCKER_BUILDKIT=1 docker-compose build`
|
||||
@@ -1,22 +0,0 @@
|
||||
# Dockerfile with China mirrors for faster builds
|
||||
# Usage: docker build -f Dockerfile.china -t qquiz-frontend .
|
||||
|
||||
FROM node:18-alpine
|
||||
|
||||
WORKDIR /app
|
||||
|
||||
# Copy package files
|
||||
COPY package*.json ./
|
||||
|
||||
# Install dependencies using Taobao npm registry
|
||||
RUN npm config set registry https://registry.npmmirror.com && \
|
||||
npm install
|
||||
|
||||
# Copy application code
|
||||
COPY . .
|
||||
|
||||
# Expose port
|
||||
EXPOSE 3000
|
||||
|
||||
# Start development server
|
||||
CMD ["npm", "start"]
|
||||
@@ -6,7 +6,7 @@ import toast from 'react-hot-toast'
|
||||
|
||||
// Create axios instance
|
||||
const api = axios.create({
|
||||
baseURL: import.meta.env.VITE_API_URL || 'http://localhost:8000',
|
||||
baseURL: import.meta.env.VITE_API_URL || '/api',
|
||||
timeout: 30000,
|
||||
headers: {
|
||||
'Content-Type': 'application/json'
|
||||
|
||||
Reference in New Issue
Block a user