Dockerfile

# Use CUDA-enabled base image to match HF Spaces CUDA 12.3
FROM nvidia/cuda:12.3.2-cudnn9-devel-ubuntu22.04

# Set environment variables
ENV PYTHONDONTWRITEBYTECODE=1 \
    PYTHONUNBUFFERED=1 \
    GRADIO_SERVER_NAME="0.0.0.0" \
    GRADIO_SERVER_PORT="7860" \
    DISPLAY=:99

# Set working directory
WORKDIR /app

# Create a non-root user for security
RUN useradd -m myuser && \
    chown myuser:myuser /app

# Install system dependencies
RUN apt-get update && apt-get install -y \
    git \
    ffmpeg \
    xvfb \
    libglib2.0-0 \
    libgomp1 \
    curl \
    && rm -rf /var/lib/apt/lists/* \
    && apt-get clean

# Copy requirements first to leverage Docker cache
COPY requirements.txt .

# Install Python dependencies as non-root user
RUN pip install --no-cache-dir --upgrade pip && \
    pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY --chown=myuser:myuser . .

# Create necessary directories with proper permissions
RUN mkdir -p /tmp/gradio /tmp/model_cache && \
    chmod 777 /tmp/gradio /tmp/model_cache && \
    chown myuser:myuser /tmp/gradio /tmp/model_cache

# Set proper permissions for the app directory
RUN chmod -R 755 /app

# Expose port
EXPOSE 7860

# Health check to ensure the app is running
HEALTHCHECK --interval=30s --timeout=3s \
    CMD curl -f http://localhost:7860/ || exit 1

# Switch to non-root user for security
USER myuser

# Run the application via start.sh to ensure xvfb
CMD ["bash", "start.sh"]