Training Monitor

Real-time monitoring system for ML training processes, specialized for diffusion model training visualization.

Features

• Real-time training progress visualization
• Training metrics monitoring (loss, learning rate, ETA)
• Sample image gallery with timeline view
• Remote SFTP data source integration
• Docker-based deployment

Project Structure

training-monitor/
├── frontend/                 # React frontend application
│   ├── src/
│   ├── public/
│   ├── Dockerfile
│   └── package.json
├── backend/                  # FastAPI backend application
│   ├── app/
│   │   ├── api/             # API routes
│   │   ├── core/            # Core functionality
│   │   ├── models/          # Data models
│   │   └── services/        # Business logic
│   ├── tests/
│   └── Dockerfile
├── docker/
│   └── docker-compose.yml
└── scripts/                  # Utility scripts

Tech Stack

• Frontend: React (v18+)

  • Tailwind CSS for styling
  • React Query for data fetching
  • React Router for navigation

• Backend: FastAPI

  • Paramiko for SFTP operations
  • Pydantic for data validation
  • SQLAlchemy for database (if needed)

Setup Instructions

1. Clone the repository:

git clone https://github.com/yourusername/training-monitor.git
cd training-monitor

2. Start the development environment:

docker-compose up --build

The application will be available at:

• Frontend: http://localhost:3000
• Backend API: http://localhost:8000
• API Documentation: http://localhost:8000/docs

Development

Frontend Development

cd frontend
npm install
npm run dev

Backend Development

cd backend
python -m venv venv
source venv/bin/activate  # or `venv\Scripts\activate` on Windows
pip install -r requirements.txt
uvicorn app.main:app --reload

Configuration

Create a .env file in the root directory:

# Backend
SFTP_HOST=42.42.42.42
SFTP_USER=username
SFTP_PASSWORD=your_password
SFTP_PATH=/data/samples

# Frontend
REACT_APP_API_URL=http://localhost:8000

Contributing

1. Create a feature branch
2. Commit your changes
3. Push to the branch
4. Create a Pull Request

License

This project is licensed under the MIT License - see the LICENSE file for details.