# Multi-stage Dockerfile for AI Microservice

# Stage 1: Base image with dependencies
FROM python:3.11-slim as base

# Set environment variables
ENV PYTHONUNBUFFERED=1 \
    PYTHONDONTWRITEBYTECODE=1 \
    PIP_NO_CACHE_DIR=1 \
    PIP_DISABLE_PIP_VERSION_CHECK=1

# Install system dependencies
RUN apt-get update && apt-get install -y \
    gcc \
    g++ \
    libpq-dev \
    curl \
    && rm -rf /var/lib/apt/lists/*

# Create app directory
WORKDIR /app

# Copy requirements
COPY requirements.txt .

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

# Stage 2: Application
FROM base as app

# Copy application code
COPY . .

# Create data directory for FAISS
RUN mkdir -p /app/data/faiss_index

# Expose port
EXPOSE 8000

# Health check
HEALTHCHECK --interval=30s --timeout=10s --start-period=40s --retries=3 \
    CMD curl -f http://localhost:8000/health/liveness || exit 1

# Default command (can be overridden)
CMD ["uvicorn", "app.main:app", "--host", "0.0.0.0", "--port", "8000"]

# Stage 3: Celery worker
FROM base as worker

# Copy application code
COPY . .

# Create data directory
RUN mkdir -p /app/data/faiss_index

# Default command for worker
CMD ["celery", "-A", "app.celery_app", "worker", "--loglevel=info", "--concurrency=4"]

# Stage 4: Celery beat (scheduler)
FROM base as beat

# Copy application code
COPY . .

# Default command for beat
CMD ["celery", "-A", "app.celery_app", "beat", "--loglevel=info"]