Dockerfile

FROM python:3.9-slim

# Set the working directory inside the container
WORKDIR /app

# Copy all files from the current directory to the container's working directory
COPY . .

# Install dependencies from the requirements file without using cache to reduce image size
RUN pip install --upgrade pip
RUN pip install --no-cache-dir -r requirements.txt

# Verify model file exists
RUN if [ ! -f "superkart_prediction.joblib" ]; then \
        echo "❌ Model file not found!" && exit 1; \
    else \
        echo "✅ Model file exists, proceeding"; \
    fi

# expose port (Spaces listens on 7860)
ENV PORT=7860
EXPOSE 7860

# Define the command to start the application using Gunicorn with 4 worker processes
# - '-w 4': Uses 4 worker processes for handling requests
# - '-b 0.0.0.0:7860': Binds the server to port 7860 on all network interfaces
# - 'app: app': Runs the Flask app (assuming 'app.py' contains the Flask instance named 'app')
CMD ["gunicorn", "-w", "4", "-b", "0.0.0.0:7860", "app:superkart_api"]