# Humanoid Skateboarding (mjlab_husky)
# Ubuntu 22.04 + CUDA 13（训练需 NVIDIA 驱动与 nvidia-container-toolkit）
#
# 构建：
#   docker build -t husky-skate:latest .
#
# 运行（GPU，Rerun Web）：映射 Web + gRPC 两端口（与终端打印一致）
#   docker run --gpus all -it --rm -p 8080:8080 -p 9876:9876 husky-skate:latest
#
# 若宿主机 8080/9876 已被其他容器占用，可换映射（示例 18080/19876）：
#   docker run --gpus all -it --rm -p 18080:18080 -p 19876:19876 husky-skate:latest \
#     uv run play Mjlab-Skater-Flat-Unitree-G1 --checkpoint_file ckpts/test.pt \
#       --viewer rerun --rerun-web-port 18080 --rerun-grpc-port 19876 --no-rerun-open-browser
#
# 仅进 shell 调试：
#   docker run --gpus all -it --rm --entrypoint /bin/bash husky-skate:latest

FROM nvidia/cuda:13.0.1-cudnn-devel-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive \
    PYTHONUNBUFFERED=1 \
    PATH="/root/.local/bin:${PATH}" \
    MUJOCO_GL=egl

RUN apt-get update && apt-get install -y --no-install-recommends \
    git \
    curl \
    ca-certificates \
    build-essential \
    libgl1 \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

RUN curl -LsSf https://astral.sh/uv/install.sh | sh

WORKDIR /app

COPY . .

RUN uv sync && uv pip install -e .

ENV VIRTUAL_ENV=/app/.venv \
    PATH="/app/.venv/bin:${PATH}"

# 容器内无桌面：默认 Rerun Web；不自动打开浏览器（在宿主机打开终端打印的 URL）
CMD ["uv", "run", "play", "Mjlab-Skater-Flat-Unitree-G1", "--checkpoint_file", "ckpts/test.pt", "--viewer", "rerun", "--no-rerun-open-browser"]