Dockerfile

# Use PyTorch base image with CUDA support
FROM pytorch/pytorch:2.9.1-cuda12.6-cudnn9-runtime

# Set up a new user named "user" with user ID 1000
RUN useradd -m -u 1000 user

# Switch to the "user" user
USER user

# Set home to the user's home directory
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH

# Set the working directory to the user's home directory
WORKDIR $HOME/app

# Try and run pip command after setting the user with `USER user` to avoid permission issues with Python
RUN pip install --no-cache-dir --upgrade pip

# Copy requirements.txt and install dependencies
COPY --chown=user requirements.txt $HOME/app/
RUN pip install --no-cache-dir -r requirements.txt

# Copy the current directory contents into the container at $HOME/app setting the owner to the user
COPY --chown=user . $HOME/app

# Expose port 7860 (Hugging Face Space default port)
EXPOSE 7860

# Set the startup command
CMD ["uvicorn", "marker.scripts.server:app", "--host", "0.0.0.0", "--port", "7860"]