Dockerfile

# Use NVIDIA CUDA base image for GPU support
FROM nvidia/cuda:11.8.0-cudnn8-runtime-ubuntu22.04

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    DEBIAN_FRONTEND=noninteractive

# Install system dependencies
RUN apt-get update && apt-get install -y \
    python3-pip \
    python3-dev \
    git \
    wget \
    ffmpeg \
    libsm6 \
    libxext6 \
    && rm -rf /var/lib/apt/lists/*

# Set working directory
WORKDIR /app

# Upgrade pip
RUN pip3 install --no-cache-dir --upgrade pip

# Install Python dependencies
# We install torch first to ensure correct CUDA version
RUN pip3 install --no-cache-dir torch torchvision torchaudio --index-url https://download.pytorch.org/whl/cu118

# Copy requirements and install
COPY requirements.txt .
RUN pip3 install --no-cache-dir -r requirements.txt

# Create a user to run the application (Hugging Face Spaces requirement for security)
RUN useradd -m -u 1000 user
USER user
ENV HOME=/home/user \
    PATH=/home/user/.local/bin:$PATH

# Set working directory for the user
WORKDIR $HOME/app

# Copy the rest of the application code
COPY --chown=user . $HOME/app

# Expose the port (Hugging Face Spaces maps port 7860 by default)
EXPOSE 7860

# Command to run the application
CMD ["uvicorn", "app:app", "--host", "0.0.0.0", "--port", "7860"]