Dockerfile

# Use an official PyTorch image with CUDA support
FROM pytorch/pytorch:2.1.0-cuda12.1-cudnn8-runtime

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    GRADIO_ALLOW_FLAGGING=never \
    GRADIO_NUM_PORTS=1 \
    GRADIO_SERVER_NAME="0.0.0.0" \
    GRADIO_THEME=huggingface \
    HOME=/home/user

# Install system dependencies
RUN apt-get update && apt-get install -y \
    git \
    libgl1-mesa-glx \
    libglib2.0-0 \
    && rm -rf /var/lib/apt/lists/*

# Create a non-root user
RUN useradd -m -u 1000 user
USER user
WORKDIR $HOME/app

# Copy requirements and install
# (Assuming you have a requirements.txt with diffusers, transformers, accelerate, gradio)
COPY --chown=user requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of the application
COPY --chown=user . .

# Make the startup script executable
RUN chmod +x start.sh

# Expose the port Gradio runs on
EXPOSE 7860

# Run the startup script
CMD ["./start.sh"]