Dockerfile

FROM python:3.10-slim

# Set the working directory in the container
WORKDIR /app

# Enable local file store for MLflow tracking backend
ENV MLFLOW_ALLOW_FILE_STORE=true

# Install system dependencies (required for some ML libraries like XGBoost/Pandas)
RUN apt-get update && apt-get install -y \
    libgomp1 \
    && rm -rf /var/lib/apt/lists/*

# Copy requirements first to leverage Docker cache
COPY requirements.txt .

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

# Copy the rest of the application code
COPY src/ src/
COPY data/ data/
COPY .dvc/ .dvc/
COPY .dvcignore .
COPY .git/ .git/
COPY mlruns/ mlruns/

# Make the entrypoint script executable
COPY entrypoint.sh .
RUN chmod +x entrypoint.sh

# Expose the ports for FastAPI and Streamlit (Hugging Face Spaces uses 7860)
EXPOSE 8000 7860

# Command to run both API and Dashboard using the entrypoint script
CMD ["./entrypoint.sh"]