Docker

# Use a lightweight Python image
FROM python:3.9-slim

# Set the working directory
WORKDIR /app

# Install MLflow
RUN pip install mlflow

# Expose the default MLflow port
EXPOSE 7860

COPY start_server.sh .

RUN chmod +x start_server.sh

# Ensure the /data directory exists
RUN mkdir -p /data/mlruns

# Set environment variables
ENV MLFLOW_TRACKING_URI=file:///data/mlruns

# Command to run the MLflow server
CMD ["./start_server.sh"]