100d1a06eb
- 后端 API（Flask + Gunicorn） - RAG 引擎（混合检索 + 云端 Reranker + 引用溯源） - 文档解析（MinerU + 多格式支持） - Docker 生产部署配置 - 排除前端项目、敏感配置、模型文件
63 lines
2.0 KiB
Docker
63 lines
2.0 KiB
Docker
# Dockerfile.prod - 生产环境优化版
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# ================================
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# 特点：CPU-only、精简依赖、最小化镜像
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FROM python:3.10-slim
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WORKDIR /app
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# 使用阿里云镜像源
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RUN sed -i 's/deb.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources \
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&& sed -i 's/security.debian.org/mirrors.aliyun.com/g' /etc/apt/sources.list.d/debian.sources
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# 系统依赖（精简版）
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RUN apt-get update && apt-get install -y --no-install-recommends \
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build-essential \
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poppler-utils \
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libmagic1 \
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curl \
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&& rm -rf /var/lib/apt/lists/*
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# ==================== PyTorch（CPU 模式） ====================
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# 先从阿里云安装 PyTorch 依赖（避免从 PyPI 下载超时）
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RUN pip install --no-cache-dir networkx sympy mpmath typing-extensions \
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-i https://mirrors.aliyun.com/pypi/simple/
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# 再从 PyTorch 官方源下载 CPU-only 版本（约 200MB），跳过依赖解析
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RUN pip install --no-cache-dir --no-deps torch --index-url https://download.pytorch.org/whl/cpu
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# 设置 PyTorch 使用 CPU 模式
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ENV CUDA_VISIBLE_DEVICES=""
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# ==================== Python 依赖 ====================
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COPY requirements-prod.txt .
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RUN pip install --no-cache-dir -r requirements-prod.txt \
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-i https://mirrors.aliyun.com/pypi/simple/
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# ==================== 应用代码 ====================
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COPY . .
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# ==================== MinerU 配置 ====================
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# 生产环境使用本地模型
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RUN mkdir -p /root && echo '{\n\
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"models-dir": {\n\
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"pipeline": "/app/models/mineru/pipeline",\n\
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"vlm": "/app/models/mineru/vlm"\n\
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},\n\
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"config_version": "1.3.1"\n\
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}' > /root/mineru.json
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ENV MINERU_MODEL_SOURCE=local
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ENV MINERU_TOOLS_CONFIG_JSON=/root/mineru.json
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# ==================== 数据目录 ====================
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RUN mkdir -p knowledge/vector_store documents models .data
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# ==================== 环境变量 ====================
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ENV APP_ENV=prod
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ENV PYTHONUNBUFFERED=1
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EXPOSE 5001
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# 生产模式启动
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CMD ["gunicorn", "-c", "deploy/gunicorn.conf.py", "deploy.wsgi:app"]
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