Dockerfile_gunicorn

# Use official Python 3.11 image
FROM python:3.11

# Metadata
LABEL Name="SynAnno" Version="1.0.0"

# Set the working directory
WORKDIR /app

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

# Install system dependencies (Only if needed)
RUN apt-get update && apt-get install -y \
    qtbase5-dev \
    qtchooser \
    qt5-qmake \
    qttools5-dev-tools \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Install Rust (if needed)
RUN curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh -s -- -y
ENV PATH="/root/.cargo/bin:${PATH}"

# Verify Cargo version (if needed)
RUN cargo --version

RUN pip install uv
RUN uv pip install --system --no-cache-dir torch torchvision --index-url https://download.pytorch.org/whl/cpu
RUN uv pip install --system --no-cache-dir torchsummary
RUN uv pip install --system --no-cache-dir tqdm gunicorn

# Copy application code, configuration, and setup files
COPY setup.py /app/
COPY synanno /app/synanno
COPY run_production.py /app/
COPY h01/h01_104_materialization.csv /app/h01/h01_104_materialization.csv

# Install required Python packages
RUN uv pip install --system --no-cache-dir -e .

# Expose necessary ports
EXPOSE 80 9015

# Set environment variables
ENV DEBUG_APP="False"
ENV APP_IP="0.0.0.0"
ENV NG_IP="0.0.0.0"
ENV NG_PORT="9015"
ENV APP_PORT="80"
ENV EXECUTION_ENV="docker"


# Start the Flask application using Gunicorn (on port 80)
CMD ["gunicorn", "-w", "1", "--timeout", "300", "-b", "0.0.0.0:80", "run_production:app"]