# 开发镜像（GPU）：Ubuntu 22.04 + CUDA 12.1 runtime + Node 22 + cadquery + PyTorch(cu121) + PyTorch3D
# 用于装配检测「最近零件」服务端 GPU（scripts/assembly_nearest_gpu.py）
# 宿主机需：NVIDIA 驱动 + nvidia-container-toolkit；构建不要求 GPU，运行需 --gpus
#
# 构建：docker build -t massive-point-cloud-app-dev:local -f docker/Dockerfile.dev.gpu .
#
# 无 NVIDIA 的机器请改用 docker/Dockerfile.dev（仅 CPU），compose 中去掉 gpus 与 ASSEMBLY_USE_GPU

FROM nvidia/cuda:12.1.1-cudnn8-runtime-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive \
    PYTHON3_PATH=/usr/bin/python3 \
    ASSEMBLY_USE_GPU=1 \
    NVIDIA_VISIBLE_DEVICES=all \
    NVIDIA_DRIVER_CAPABILITIES=compute,utility

# apt 换阿里云（国内构建加速）；需官方源时可在下方注释掉本段
RUN set -eux; \
    if [ -f /etc/apt/sources.list ]; then \
      sed -i 's|http://archive.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
      sed -i 's|http://security.ubuntu.com/ubuntu|http://mirrors.aliyun.com/ubuntu|g' /etc/apt/sources.list; \
    fi

RUN apt-get update && apt-get install -y --no-install-recommends \
    python3 \
    python3-pip \
    python3-dev \
    ca-certificates \
    curl \
    gnupg \
    libgl1 \
    libglib2.0-0 \
    libxrender1 \
    libxext6 \
    libsm6 \
    libice6 \
    libx11-6 \
    libgomp1 \
    && rm -rf /var/lib/apt/lists/*

# CUDA runtime 镜像默认不带 nvidia-smi；装 Ubuntu 的 nvidia-utils（主版本与宿主机驱动大版本一致，如 535/550）
# 构建失败时改：--build-arg NVIDIA_UTILS_MAJOR=550
ARG NVIDIA_UTILS_MAJOR=535
RUN apt-get update && apt-get install -y --no-install-recommends \
    "nvidia-utils-${NVIDIA_UTILS_MAJOR}" \
    && rm -rf /var/lib/apt/lists/*

RUN mkdir -p /etc/apt/keyrings \
    && curl -fsSL https://deb.nodesource.com/gpgkey/nodesource-repo.gpg.key | gpg --dearmor -o /etc/apt/keyrings/nodesource.gpg \
    && echo "deb [signed-by=/etc/apt/keyrings/nodesource.gpg] https://deb.nodesource.com/node_22.x nodistro main" > /etc/apt/sources.list.d/nodesource.list \
    && apt-get update && apt-get install -y --no-install-recommends nodejs \
    && rm -rf /var/lib/apt/lists/*

RUN python3 -m pip install --no-cache-dir --upgrade pip setuptools wheel

# 安装 Miniforge + pythonocc-core（conda-forge，无 Anaconda ToS 限制）
ARG MINIFORGE_URL=https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-Linux-x86_64.sh
RUN set -eux \
    && curl -fsSL "${MINIFORGE_URL}" -o /tmp/miniforge.sh \
    && bash /tmp/miniforge.sh -b -p /opt/conda \
    && rm /tmp/miniforge.sh \
    && /opt/conda/bin/conda install -y -n base -c conda-forge \
        "python=3.10" pythonocc-core=7.9.3 \
    && /opt/conda/bin/conda clean -afy \
    && ln -sf /opt/conda/lib/python3.10/site-packages/OCC \
              /usr/local/lib/python3.10/dist-packages/OCC
# conda-forge 编译的 .so 需要新版 libstdc++；用 conda 自带的覆盖系统库
RUN ln -sf /opt/conda/lib/libstdc++.so.6 /usr/lib/x86_64-linux-gnu/libstdc++.so.6 \
    && python3 -c "from OCC.Core.STEPControl import STEPControl_Reader; print('pythonocc-core OK')"

# cadquery（与 Dockerfile.dev 一致）
ARG PIP_INDEX_URL=https://pypi.tuna.tsinghua.edu.cn/simple
ARG PIP_DEFAULT_TIMEOUT=300
COPY requirements-geometry.txt /tmp/requirements-geometry.txt
RUN python3 -m pip install --no-cache-dir --break-system-packages \
    --default-timeout="${PIP_DEFAULT_TIMEOUT}" \
    --retries 10 \
    -i "${PIP_INDEX_URL}" \
    -r /tmp/requirements-geometry.txt \
    && rm /tmp/requirements-geometry.txt \
    && python3 -c "import cadquery; print('cadquery OK')"

# PyTorch CUDA 12.1：默认官方 CDN；覆盖示例：--build-arg TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
ARG TORCH_INDEX_URL=https://download.pytorch.org/whl/cu121
RUN python3 -m pip install --no-cache-dir --break-system-packages \
    --default-timeout=600 --retries 10 \
    torch==2.3.1 torchvision==0.18.1 \
    --index-url "${TORCH_INDEX_URL}"

# PyTorch3D 预编译轮仅 Meta 官方 CDN，无稳定国内镜像；加大超时。可本地下载 wheel 后 COPY + pip install。
RUN python3 -m pip install --no-cache-dir --break-system-packages \
    --default-timeout=300 --retries 10 \
    -i https://pypi.tuna.tsinghua.edu.cn/simple \
    trimesh \
    && python3 -m pip install --no-cache-dir --break-system-packages \
    --default-timeout=600 --retries 15 \
    pytorch3d -f https://dl.fbaipublicfiles.com/pytorch3d/packaging/wheels/py310_cu121_pyt231/download.html

RUN python3 -c "import torch; import pytorch3d; import trimesh; print('pytorch', torch.__version__, 'pytorch3d', pytorch3d.__version__)"

WORKDIR /app

RUN corepack enable && corepack prepare pnpm@latest --activate

CMD ["node", "-e", "console.log('use docker-compose command')"]