Dockerfile

# Use NVIDIA CUDA base image for GPU support with development tools
FROM nvidia/cuda:12.4.1-devel-ubuntu22.04

# Set environment variables
ENV PYTHONUNBUFFERED=1
ENV PYTHONDONTWRITEBYTECODE=1
ENV PIP_NO_CACHE_DIR=1
ENV PIP_DISABLE_PIP_VERSION_CHECK=1

# Install system dependencies including Python and PDF processing tools
RUN apt-get update && apt-get install -y --no-install-recommends \
    python3 \
    python3-pip \
    curl \
    ca-certificates \
    poppler-utils \
    libpoppler-dev \
    && apt-get clean \
    && rm -rf /var/lib/apt/lists/*

# Set Python 3 as default
RUN update-alternatives --install /usr/bin/python python /usr/bin/python3 1

# Install uv for faster package management
RUN python -m pip install --upgrade pip && pip install uv

# Create app directory
WORKDIR /app

# Copy project files
COPY pyproject.toml ./
COPY nanonets_mcp/ ./nanonets_mcp/
COPY README.md ./

# Install Python dependencies
RUN uv pip install --system -e .

# Create non-root user for security
RUN useradd --create-home --shell /bin/bash app
RUN chown -R app:app /app
USER app

# Create directory for model cache
RUN mkdir -p /app/.cache/huggingface

# Expose port for MCP server
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=5s --retries=3 \
    CMD python -c "from nanonets_mcp.server import mcp; print('OK')" || exit 1

# Default command
CMD ["python", "-m", "nanonets_mcp.server"]