Dockerfile

FROM nvidia/cuda:12.4.1-cudnn-runtime-ubuntu22.04

ENV DEBIAN_FRONTEND=noninteractive \
    PYTHONUNBUFFERED=1 \
    GRADIO_SERVER_NAME=0.0.0.0 \
    GRADIO_SERVER_PORT=7860 \
    HF_HOME=/home/user/.cache/huggingface \
    PYTORCH_CUDA_ALLOC_CONF=expandable_segments:True

RUN apt-get update && apt-get install -y --no-install-recommends \
    python3.10 python3-pip git libgl1 libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

RUN useradd -m -u 1000 user
USER user
ENV HOME=/home/user PATH=/home/user/.local/bin:$PATH
WORKDIR /home/user/app
COPY --chown=user . /home/user/app
RUN python3.10 -m pip install --user --upgrade pip && \
    python3.10 -m pip install --user --no-cache-dir -r requirements.txt

# Keep the baseline image buildable when the experimental DA3 API changes.
# GPU research builders can opt in with --build-arg SIMAM3D_INSTALL_DA3=1.
ARG SIMAM3D_INSTALL_DA3=0
RUN if [ "$SIMAM3D_INSTALL_DA3" = "1" ]; then \
      python3.10 -m pip install --user --no-cache-dir -r requirements-da3.txt; \
    fi

EXPOSE 7860
HEALTHCHECK --interval=30s --timeout=5s --start-period=120s --retries=3 \
  CMD python3.10 -c "import urllib.request; urllib.request.urlopen('http://127.0.0.1:7860/', timeout=4)"
CMD ["python3.10", "app.py"]