Docker

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

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    SHELL=/bin/bash

# Set the working directory
WORKDIR /app

# Copy requirements.txt and install dependencies
COPY requirements.txt .
RUN pip install --no-cache-dir -r requirements.txt

# Copy the app.py file into the container
COPY app.py .

# Expose the default MLflow port
EXPOSE 7860

# Set the command to run the app
CMD ["python", "app.py"]