Digital_Human/Dockerfile

# 使用多阶段构建优化镜像大小
# 第一阶段：构建阶段
FROM nvcr.io/nvidia/cuda:12.4.1-cudnn8-devel-ubuntu22.04 AS builder

# 设置环境变量
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1
ENV DEBIAN_FRONTEND=noninteractive

# 安装系统依赖
RUN apt-get update && apt-get install -y --no-install-recommends \
    wget \
    curl \
    git \
    vim \
    ffmpeg \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# 安装Miniconda
RUN wget https://repo.anaconda.com/miniconda/Miniconda3-latest-Linux-x86_64.sh -O miniconda.sh \
    && bash miniconda.sh -b -p /opt/conda \
    && rm miniconda.sh

# 设置conda环境
ENV PATH=/opt/conda/bin:$PATH

# 创建conda环境
RUN conda create -n livetalking python=3.10 -y

# 激活conda环境
ENV PATH=/opt/conda/envs/livetalking/bin:$PATH

# 设置pip镜像源
RUN pip config set global.index-url https://pypi.tuna.tsinghua.edu.cn/simple

# 安装PyTorch和依赖
RUN pip install torch==2.5.0 torchvision==0.20.0 torchaudio==2.5.0 --index-url https://download.pytorch.org/whl/cu124

# 复制requirements文件
COPY requirements.txt .

# 安装Python依赖
RUN pip install -r requirements.txt

# 第二阶段：运行时阶段
FROM nvcr.io/nvidia/cuda:12.4.1-runtime-ubuntu22.04

# 设置环境变量
ENV PYTHONDONTWRITEBYTECODE=1
ENV PYTHONUNBUFFERED=1
ENV DEBIAN_FRONTEND=noninteractive

# 安装运行时依赖
RUN apt-get update && apt-get install -y --no-install-recommends \
    ffmpeg \
    libsm6 \
    libxext6 \
    libxrender-dev \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# 从构建阶段复制conda环境
COPY --from=builder /opt/conda /opt/conda

# 设置环境变量
ENV PATH=/opt/conda/envs/livetalking/bin:$PATH

# 创建工作目录
WORKDIR /app

# 复制项目文件
COPY . /app/

# 创建模型目录
RUN mkdir -p /app/models

# 设置权限
RUN chmod +x /app/app.py

# 暴露端口
EXPOSE 7860 8080

# 健康检查
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD curl -f http://localhost:7860/health || exit 1

# 启动命令
CMD ["python", "app.py"]