Dockerfile

# Use an official Python base image
FROM python:3.12

# Set the working directory
WORKDIR /app

# Copy the current directory contents into the container
COPY . /app

# Install MLflow and required dependencies
# RUN pip install mlflow==2.9.2 gunicorn
RUN pip install --upgrade pip setuptools wheel \
    && pip install mlflow gunicorn psycopg2-binary
  
RUN mkdir -p /app/mlflow_data && chmod -R 777 /app/mlflow_data
# Expose the MLflow server port
EXPOSE 7860

# Set environment variables (optional)
ENV MLFLOW_TRACKING_USERNAME=admin
ENV MLFLOW_TRACKING_PASSWORD=password

# Run the MLflow server script
CMD ["python", "app.py"]