# --- AI Engine Dockerfile ---
# Python 3.11 with v20+ prediction stack (XGBoost + LightGBM)

FROM python:3.11-slim

WORKDIR /app

# System dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    libpq-dev \
    curl \
    libgomp1 \
    procps \
    && rm -rf /var/lib/apt/lists/*

# Python dependencies
# Install PyTorch CPU version separately to save space
RUN pip install --no-cache-dir torch --index-url https://download.pytorch.org/whl/cpu

# Copy requirements (without torch)
COPY requirements-docker.txt requirements.txt
RUN pip install --no-cache-dir -r requirements.txt

# Copy application code
COPY . .

# Create models directory
RUN mkdir -p /app/models

# Expose port
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=30s --retries=3 \
    CMD python -c "import urllib.request; urllib.request.urlopen('http://127.0.0.1:8000/health')" || exit 1

# Start FastAPI with uvicorn
CMD ["uvicorn", "main:app", "--host", "0.0.0.0", "--port", "8000"]