# 多阶段构建 Dockerfile for AI Story Creator # 阶段1: 构建前端 FROM node:22-alpine AS frontend-builder WORKDIR /frontend # 复制前端依赖文件 COPY frontend/package*.json ./ # 使用国内npm镜像加速 RUN npm config set registry https://registry.npmmirror.com # 安装依赖 RUN npm install # 复制前端源代码 COPY frontend/ ./ # 临时修改vite配置,使其输出到dist目录(而不是../backend/static) RUN sed -i "s|outDir: '../backend/static'|outDir: 'dist'|g" vite.config.ts # 构建前端 RUN npm run build # 阶段2: 构建最终镜像 FROM python:3.11-slim # 设置工作目录 WORKDIR /app # 使用国内镜像源加速 RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources \ && sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources # 安装系统依赖(添加数据库工具) RUN apt-get update && apt-get install -y \ gcc \ postgresql-client \ netcat-traditional \ && rm -rf /var/lib/apt/lists/* # 复制后端依赖文件 COPY backend/requirements.txt ./ # 先从PyTorch官方源安装CPU版本的torch(避免GPU依赖) RUN pip install --no-cache-dir torch==2.7.0 --index-url https://download.pytorch.org/whl/cpu # 再安装其他Python依赖(使用阿里云镜像加速) RUN pip install --no-cache-dir -r requirements.txt -i https://mirrors.aliyun.com/pypi/simple/ # 复制后端代码(包含embedding模型) COPY backend/ ./ # 从前端构建阶段复制构建好的静态文件 COPY --from=frontend-builder /frontend/dist ./static # 复制 Alembic 迁移配置和脚本(PostgreSQL) COPY backend/alembic-postgres.ini ./alembic.ini COPY backend/alembic/postgres ./alembic COPY backend/scripts/entrypoint.sh /app/entrypoint.sh COPY backend/scripts/migrate.py ./scripts/migrate.py # 赋予执行权限 RUN chmod +x /app/entrypoint.sh # 创建必要的目录 RUN mkdir -p /app/data /app/logs # 暴露端口 EXPOSE 8000 # 设置环境变量 ENV PYTHONUNBUFFERED=1 ENV APP_HOST=0.0.0.0 ENV APP_PORT=8000 # 设置Transformers和Sentence-Transformers离线模式 ENV TRANSFORMERS_OFFLINE=1 ENV HF_DATASETS_OFFLINE=1 ENV HF_HUB_OFFLINE=1 ENV SENTENCE_TRANSFORMERS_HOME=/app/embedding # 健康检查 HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \ CMD python -c "import urllib.request; urllib.request.urlopen('http://localhost:8000/health')" || exit 1 # 使用 entrypoint 脚本启动(自动执行迁移) ENTRYPOINT ["/app/entrypoint.sh"]