Dockerfile

FROM nvidia/cuda:12.3.1-base-ubuntu22.04

# Prevent interactive prompts during build
ENV DEBIAN_FRONTEND=noninteractive

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

# Set working directory
WORKDIR /app

# Setup CUDA based on environment
ARG INSTALL_TYPE=network
RUN if [ "$INSTALL_TYPE" = "network" ]; then \
        # Network install method
        wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-keyring_1.1-1_all.deb && \
        dpkg -i cuda-keyring_1.1-1_all.deb && \
        apt-get update && \
        apt-get -y install cuda-toolkit-12-6; \
    elif [ "$INSTALL_TYPE" = "local" ]; then \
        # Local install method
        wget https://developer.download.nvidia.com/compute/cuda/repos/ubuntu2204/x86_64/cuda-ubuntu2204.pin && \
        mv cuda-ubuntu2204.pin /etc/apt/preferences.d/cuda-repository-pin-600 && \
        wget https://developer.download.nvidia.com/compute/cuda/12.6.3/local_installers/cuda-repo-ubuntu2204-12-6-local_12.6.3-560.35.05-1_amd64.deb && \
        dpkg -i cuda-repo-ubuntu2204-12-6-local_12.6.3-560.35.05-1_amd64.deb && \
        cp /var/cuda-repo-ubuntu2204-12-6-local/cuda-*-keyring.gpg /usr/share/keyrings/ && \
        apt-get update && \
        apt-get -y install cuda-toolkit-12-6; \
    fi

# Copy requirements first to leverage Docker cache
COPY requirements.txt .
RUN pip3 install --no-cache-dir -r requirements.txt

# Copy application code
COPY . .

# Create necessary directories
RUN mkdir -p data models output

# Set environment variables
ENV PYTHONUNBUFFERED=1
ENV NVIDIA_VISIBLE_DEVICES=all
ENV PYTHONPATH=/app

# Expose port
EXPOSE 8000

# Start application
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]