Datasets:
| # Use a lightweight Python base image | |
| FROM python:3.9-slim-buster | |
| # Set the working directory inside the container | |
| WORKDIR /app | |
| # Copy the requirements file and install dependencies | |
| COPY requirements.txt . | |
| RUN pip install --no-cache-dir -r requirements.txt | |
| # Copy the trained model | |
| # Assuming the model was saved as 'best_random_forest_model.joblib' in the root of the project | |
| COPY best_random_forest_model.joblib . | |
| # Copy the application code | |
| COPY app.py . | |
| # Expose the port your Flask app will run on | |
| EXPOSE 5000 | |
| # Command to run the application | |
| CMD ["python", "app.py"] | |