FROM ghcr.io/astral-sh/uv:latest AS uv_bin
FROM nvidia/cuda:12.4.1-base-ubuntu22.04

ENV UV_LINK_MODE=copy \
    UV_COMPILE_BYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    UV_PROJECT_ENVIRONMENT=/app/.venv \
    TORCH_CUDA_ARCH_LIST="8.6" \
    CUDA_VISIBLE_DEVICES=0 \
    UV_TORCH_BACKEND=cu128

COPY --from=uv_bin /uv /uvx /bin/

#RUN apt-get update && apt-get install -y --no-install-recommends \
#    ca-certificates curl gnupg && \
#    sed -i 's|http://archive.ubuntu.com/ubuntu/|http://mirrors.cloud.tencent.com/ubuntu/|g' /etc/apt/sources.list && \
#    sed -i 's|http://security.ubuntu.com/ubuntu/|http://mirrors.cloud.tencent.com/ubuntu/|g' /etc/apt/sources.list && \
#    apt-get update && \
#    apt-get install -y --no-install-recommends \
#    git \
#    ffmpeg libsm6 libxext6 \
#    build-essential g++ \
#    && apt-get clean && rm -rf /var/lib/apt/lists/*

WORKDIR /app

# 3. 安装依赖 (不加 --system，让 uv 创建受管的虚拟环境)
# 这里会根据 pyproject.toml 自动下载并安装 Python 3.11
COPY pyproject.toml uv.lock ./
#RUN uv sync --frozen --no-dev --no-install-project --python 3.9
# 4. 拷贝项目文件并安装项目本身
COPY . .
#RUN uv sync --frozen --no-dev --python 3.9

# 5. 【最关键】将虚拟环境的 bin 目录提到最前面
# 注意：uv sync 创建的 python 就在这个目录下
ENV PATH="/app/.venv/bin:$PATH"

EXPOSE 8000

# 验证路径并运行
# 此时运行 python 实际上是运行 /app/.venv/bin/python
CMD ["sleep", "infinity"]