docker-compose.yml

version: '3.8'

services:
  # Main training service
  finetuning-lab:
    build:
      context: .
      dockerfile: Dockerfile
    image: synthoraai/llm-finetuning-lab:latest
    container_name: llm-finetuning-lab
    volumes:
      - ./checkpoints:/app/checkpoints
      - ./datasets:/app/datasets
      - ./logs:/app/logs
      - ./outputs:/app/outputs
      - ./configs:/app/configs
    environment:
      - CUDA_VISIBLE_DEVICES=0
      - PYTHONUNBUFFERED=1
    deploy:
      resources:
        reservations:
          devices:
            - driver: nvidia
              count: all
              capabilities: [gpu]
    command: tail -f /dev/null

  # Jupyter notebook service
  jupyter:
    build:
      context: .
      dockerfile: Dockerfile
    image: synthoraai/llm-finetuning-lab:latest
    container_name: llm-finetuning-jupyter
    ports:
      - "8888:8888"
    volumes:
      - ./notebooks:/app/notebooks
      - ./checkpoints:/app/checkpoints
      - ./datasets:/app/datasets
    environment:
      - JUPYTER_ENABLE_LAB=yes
    command: jupyter lab --ip=0.0.0.0 --port=8888 --no-browser --allow-root --NotebookApp.token='' --NotebookApp.password=''

  # TensorBoard service
  tensorboard:
    build:
      context: .
      dockerfile: Dockerfile
    image: synthoraai/llm-finetuning-lab:latest
    container_name: llm-finetuning-tensorboard
    ports:
      - "6006:6006"
    volumes:
      - ./runs:/app/runs
      - ./logs:/app/logs
    command: tensorboard --logdir=/app/runs --host=0.0.0.0 --port=6006

  # MongoDB (for data storage)
  mongodb:
    image: mongo:7.0
    container_name: llm-finetuning-mongodb
    ports:
      - "27017:27017"
    volumes:
      - mongodb_data:/data/db
    environment:
      - MONGO_INITDB_ROOT_USERNAME=admin
      - MONGO_INITDB_ROOT_PASSWORD=password

  # Redis (for caching)
  redis:
    image: redis:7-alpine
    container_name: llm-finetuning-redis
    ports:
      - "6379:6379"
    volumes:
      - redis_data:/data

volumes:
  mongodb_data:
  redis_data: