Dockerfile

# Use a stable Python base image
FROM python:3.9-slim

# Set the working directory inside the container
WORKDIR /app

# Install system dependencies needed for libraries like OpenCV or Pillow
RUN apt-get update && apt-get install -y --no-install-recommends \
    ffmpeg \
    libsm6 \
    libxext6 \
    && rm -rf /var/lib/apt/lists/*

# Copy the requirements file first to leverage Docker's layer caching
COPY requirements.txt .

# Install Python dependencies
RUN pip install --no-cache-dir -r requirements.txt

# Copy the rest of the application files into the container
COPY . .

# Create a directory for the generated files
RUN mkdir -p /app/generated

# Expose the port the app will run on
EXPOSE 5000

# Command to run the application using Gunicorn, a production-grade server
# The timeout is increased because the AI model can take a long time to respond.
CMD ["gunicorn", "--bind", "0.0.0.0:5000", "--workers", "1", "--timeout", "300", "app:app"]