OnlyJobs Desktop

An AI-powered job application tracking desktop app that automatically syncs with Gmail, classifies job-related emails using machine learning, and provides real-time analytics.

Features

• 🔐 Gmail Integration: Secure OAuth 2.0 authentication with Gmail
• 🤖 AI Classification: Automatically identifies and classifies job-related emails
• 📊 Real-time Dashboard: Track your job applications with live updates
• 🔄 Multi-Account Support: Connect multiple Gmail accounts
• 💾 Local Storage: All data stored locally using SQLite
• 🎯 Smart Extraction: Extracts company names, positions, and application dates

Prerequisites

• Node.js (v18 or higher)
• Python 3.8+
• Gmail account
• Google Cloud Platform project with Gmail API enabled

Installation

1. Clone the repository (including the ML classifier submodule):

git clone --recurse-submodules https://github.com/yourusername/onlyjobs-desktop.git
cd onlyjobs-desktop
# if you already cloned without submodules
git submodule update --init --recursive

1. Install dependencies:

npm install

1. Install Python dependencies for the ML classifier:

cd ml-classifier
pip install -r requirements.txt
cd ..

1. Add configuration files:
2. Place gmail_credentials.json in the project root (downloaded from Google Cloud Console).
3. Create a .env file in the project root with values for:
   • GOOGLE_CLIENT_ID
   • GOOGLE_CLIENT_SECRET
   • GOOGLE_REDIRECT_URI
   • any REACT_APP_* Firebase variables required by the React app

4. Create electron/.env with:

   • GOOGLE_OAUTH_CLIENT_ID
   • GOOGLE_OAUTH_CLIENT_SECRET
   • GOOGLE_OAUTH_REDIRECT_URI

5. (Optional) Run the setup script to install all dependencies automatically:

bash setup.sh

Running the App

Development Mode

Start both React and Electron in development mode:

# Terminal 1 - Start React dev server
npm start

# Terminal 2 - Start Electron
npm run electron-dev

Production Build

# Build React app
npm run build

# Package Electron app
npm run electron-pack

Testing

Run the Jest test suite:

npm test

Project Structure

onlyjobs-desktop/
├── electron/           # Electron main process files
│   ├── main.js        # Main entry point
│   ├── ipc-handlers.js # IPC communication handlers
│   ├── gmail-auth.js  # Gmail authentication
│   └── gmail-multi-auth.js # Multi-account support
├── src/               # React app source
│   ├── components/    # React components
│   ├── pages/        # Page components
│   └── ElectronApp.tsx # Main Electron app component
├── ml-classifier/     # Python ML classifier
│   ├── scripts/      # Classification scripts
│   └── data/models/  # Trained ML models
└── public/           # Static assets

Key Technologies

• Frontend: React 19, TypeScript, Material-UI
• Desktop: Electron 37
• Database: SQLite3 (better-sqlite3)
• ML: Python, scikit-learn
• Authentication: Google OAuth 2.0 (AppAuth-JS)

Development Notes

Gmail Sync Process

1. Fetch Stage: Downloads emails from Gmail with full content
2. Classification Stage: Processes emails through ML classifier
3. Storage: Saves job-related emails to local SQLite database

Database Schema

The app uses SQLite with the following main tables:
- emails: Stores all fetched emails
- jobs: Stores classified job applications
- gmail_accounts: Manages multiple Gmail accounts
- sync_status: Tracks sync progress

ML Classification

The classifier uses a trained model to identify job-related emails based on:
- Email content and structure
- Keywords and patterns
- Sender information
- Subject line analysis

Troubleshooting

Better-SQLite3 Issues

If you encounter module version mismatch errors:

# For Electron
npm rebuild better-sqlite3 --runtime=electron --target=37.2.5 --dist-url=https://electronjs.org/headers

# For Node.js (testing)
npm rebuild better-sqlite3

OAuth Redirect Issues

Ensure redirect URIs use 127.0.0.1 (not localhost) as per Google's requirements.

Email Content Display

HTML emails are automatically converted to plain text for better readability.

Contributing

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

License

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

Acknowledgments

• ML classifier model provided by contributor
• Built with Electron and React
• Gmail API integration powered by Google APIs