docker-compose.gpu.yml

version: "3.8"

services:
  celery_worker:
    build:
      context: .
      args:
        CPU_ONLY: "false"
    image: converter-gpu-image
    command: poetry run celery -A worker.celery_config worker --pool=solo -n worker_primary --loglevel=info
    volumes:
      - .:/app
    environment:
      - REDIS_HOST=${REDIS_HOST}
      - ENV=production
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    depends_on:
      - redis

  app:
    container_name: marker-api-gpu
    build:
      context: .
      args:
        CPU_ONLY: "false"
    image: converter-gpu-image
    command: poetry run uvicorn --port 8080 --host 0.0.0.0 main:app
    environment:
      - REDIS_HOST=${REDIS_HOST}
      - ENV=production
      - NVIDIA_VISIBLE_DEVICES=all
    ports:
      - "8080:8080"
    volumes:
      - .:/app
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]
    depends_on:
      - redis
      - celery_worker

  redis:
    container_name: redis
    image: redis:7.2.4-alpine
    ports:
      - "6379:6379"

  flower:
    container_name: flower_gpu
    build:
      context: .
      args:
        CPU_ONLY: "false"
    image: converter-gpu-image
    command: poetry run celery -A worker.celery_config flower --port=5555
    ports:
      - "5556:5555"
    volumes:
      - .:/app
    environment:
      - REDIS_HOST=${REDIS_HOST}
      - ENV=production
    depends_on:
      - app
      - redis
      - celery_worker
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: 1
              capabilities: [gpu]