# ============================================================================
# Avvio dell'app via Docker. CPU di default.
# Per la GPU: usare un'immagine base CUDA e abilitare la sezione `deploy`.
# ============================================================================
services:
  app:
    build:
      context: .
      args:
        ENABLE_ML: "${ENABLE_ML:-false}"
    image: anonimyzer-gare:latest
    ports:
      - "8000:8000"
    env_file:
      - .env
    environment:
      DEVICE: "${DEVICE:-cpu}"
    restart: unless-stopped
    healthcheck:
      test: ["CMD", "python", "-c", "import urllib.request; urllib.request.urlopen('http://localhost:8000/healthz')"]
      interval: 30s
      timeout: 5s
      retries: 3

    # --- GPU opzionale (decommentare con runtime NVIDIA disponibile) ---
    # deploy:
    #   resources:
    #     reservations:
    #       devices:
    #         - driver: nvidia
    #           count: 1
    #           capabilities: [gpu]

  # --- Coda asincrona opzionale per i job pesanti in produzione ---
  # redis:
  #   image: redis:7-alpine
  #   restart: unless-stopped