A comprehensive Windows desktop application that helps users understand and improve their computer usage habits through AI-powered insights, productivity tracking, and intelligent parental controls.

• Overview
• Features
• Architecture
• Installation
• Development Setup
• Usage
• API Integration
• Contributing
• License

FocusAI Tracker combines the power of AI with comprehensive activity monitoring to provide users with actionable insights about their computer usage. Whether you're a professional looking to boost productivity or a parent wanting to ensure safe computer use for your children, FocusAI Tracker has you covered.

• 📊 Deep Insights: Understand exactly how you spend time on your PC
• 🤖 AI-Powered: Get personalized recommendations for improvement
• 👨‍👩‍👧‍👦 Family-Friendly: Comprehensive parental controls with Kids Mode
• 🔒 Privacy-First: All data stored locally with encryption
• 📈 Productivity Focus: Reduce distractions and maximize focus time

• Real-time Activity Monitoring: Track active windows, applications, and usage duration
• AI Activity Classification: Automatically categorize activities as Productive, Neutral, or Distracting
• Screenshot Capture: Periodic screenshots with configurable intervals and retention
• Idle Time Detection: Accurate tracking of active vs. idle computer usage
• Focus Mode: Block or warn about distracting applications during work sessions

• Interactive Dashboard: Visual summaries of daily, weekly, and monthly usage
• Trend Analysis: Identify patterns and changes in computer usage over time
• Export Capabilities: Generate PDF and Excel reports for deeper analysis
• Custom Categories: Create and manage personalized activity categories

• Smart Recommendations: Daily, weekly, and monthly improvement suggestions
• Usage Pattern Analysis: Identify productivity peaks and distraction triggers
• Goal Setting: AI-assisted productivity goal creation and tracking
• Habit Formation: Personalized strategies for building better computer habits

• Smart Content Filtering: AI-powered detection of inappropriate content
• Screen Time Management: Configurable daily and weekly time limits
• Schedule Control: Set allowed computer usage hours
• Educational Focus: Promote educational app usage with intelligent recommendations
• Safety Alerts: Real-time notifications for inappropriate activity detection
• Parent Dashboard: Comprehensive oversight of child's computer usage

FocusAI Tracker uses a hybrid architecture combining a Python Flask backend with a React/Electron frontend for optimal performance and user experience.

Frontend:

• Electron: Desktop application shell
• React: Component-based UI library (TypeScript)
• Tailwind CSS: Utility-first CSS framework
• Chart.js & react-chartjs-2: Data visualization
• Lucide-react, date-fns, axios, @headlessui/react

Backend:

• Python 3.9+: Core application logic
• Flask: RESTful API framework
• Flask-SQLAlchemy: ORM for database
• Flask-Migrate: Database migrations
• Flask-CORS: CORS support
• Flask-RESTful: API structure
• SQLite: Local database
• Cryptography: Data encryption
• psutil, pywin32, pillow, schedule, requests

AI/ML Integration (Planned/Optional):

• Google Gemini Flash API: Advanced activity classification and advice generation (planned)
• TensorFlow Lite, scikit-learn: Optional for local ML models (future)

FocusAI-Tracker/
├── backend/
│   ├── app/
│   │   ├── api/              # Flask API routes (activity, dashboard, settings, kids_mode, etc.)
│   │   ├── core/             # Core config and logic
│   │   ├── models/           # Database models
│   │   ├── services/         # Business services
│   │   ├── tracking/         # Activity tracking modules
│   │   └── utils/            # Utility functions
│   ├── ai/                   # (Planned) AI/ML modules
│   ├── scripts/              # Utility scripts
│   ├── tests/                # Backend tests
│   ├── instance/             # Flask instance folder
│   ├── tracking/             # (Legacy/extra tracking modules)
│   ├── requirements.txt
│   ├── requirements-dev.txt
│   └── run.py                # Backend entrypoint
├── frontend/
│   ├── src/
│   │   ├── components/       # React components
│   │   ├── pages/            # Application pages
│   │   ├── services/         # API communication
│   │   ├── utils/            # Frontend utilities
│   │   ├── assets/           # Static assets
│   │   ├── styles/           # Tailwind and custom CSS
│   │   ├── contexts/         # React contexts
│   │   ├── hooks/            # Custom hooks
│   │   └── layouts/          # Layout components
│   ├── public/               # Static files for Electron/React
│   ├── app/                  # (If used for Electron preload)
│   ├── main.js               # Electron main process
│   ├── package.json
│   ├── tailwind.config.js
│   ├── tsconfig.json
│   └── postcss.config.js
├── shared/
│   ├── config/               # Shared configuration
│   └── schemas/              # Shared data schemas
├── docs/                     # Documentation
├── template/                 # (If used for templates)
├── docker-compose.yml        # (If used for deployment)
├── LICENSE
├── .gitignore
└── readme.md

• Windows 10/11 (64-bit)
• Python 3.9+
• Node.js 16+
• npm

1. Download the latest release from Releases
2. Run the installer (FocusAI-Tracker-Setup.exe)
3. Follow the installation wizard
4. Launch FocusAI Tracker from Start Menu or Desktop

# Clone the repository
git clone https://github.com/yourusername/focusai-tracker.git
cd focusai-tracker

# Install Python dependencies
cd backend
pip install -r requirements.txt

# Install Node.js dependencies
cd ../frontend
npm install

# Build the frontend (for production)
npm run build

# Clone the repository
git clone https://github.com/yourusername/focusai-tracker.git
cd focusai-tracker

# Create Python virtual environment
python -m venv venv
venv\Scripts\activate  # Windows
# source venv/bin/activate  # Linux/Mac

# Install backend dependencies
cd backend
pip install -r requirements.txt
pip install -r requirements-dev.txt  # Development dependencies

# Install frontend dependencies
cd ../frontend
npm install

# Copy environment template (if available)
cp .env.example .env

# Edit .env with your settings (see backend/app/core/config.py for options)
# DATABASE_URL=sqlite:///focusai.db
# GEMINI_API_KEY=your_gemini_api_key_here
# DEBUG=true
# SECRET_KEY=your-secret-key

# Terminal 1: Start Python backend (Flask)
cd backend
python run.py

# Terminal 2: Start React frontend (for web)
cd frontend
npm start

# Terminal 3: Start Electron desktop app (after React dev server is running)
cd frontend
npm run electron-dev

• The database is auto-created on first run (SQLite by default).
• For migrations, use Flask-Migrate (see scripts or docs for details).

1. Launch Application: Open FocusAI Tracker from your desktop or start menu
2. Initial Configuration: Set up basic preferences and screenshot settings
3. AI Setup: Optionally configure Gemini API key for advanced features (future)
4. Kids Mode: Enable and configure parental controls if needed

• Automatic Tracking: The app runs in the background, tracking your activity
• Review Dashboard: Check daily progress and AI recommendations
• Focus Sessions: Use Focus Mode to block distractions during work
• Weekly Reviews: Analyze trends and adjust productivity strategies

1. Enable Kids Mode: Navigate to Settings > Kids Mode
2. Set PIN: Create a secure PIN for parental access
3. Configure Limits: Set daily screen time and allowed hours
4. Content Filtering: Adjust AI sensitivity for content detection
5. Monitor Progress: Review child's usage through parent dashboard

# Configuration in .env file
GEMINI_API_KEY=your_api_key_here
GEMINI_MODEL=gemini-flash

# Usage in code (planned)
# from app.services.ai_service import AIService
# ai_service = AIService()
# advice = ai_service.generate_daily_advice(user_activity_data)

# Add custom classification models (future)
# from app.ai.custom_classifier import CustomClassifier
# classifier = CustomClassifier()
# classifier.train(training_data)
# activity_type = classifier.classify(window_title, app_name)

We welcome contributions from the community! Please see our Contributing Guidelines for details.

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

• Python: Follow PEP 8 guidelines, use type hints
• JavaScript/TypeScript: Use ESLint and Prettier for code formatting
• Testing: Write unit tests for new features
• Documentation: Update documentation for API changes

• Local Storage: All data stored locally with AES-256 encryption
• Minimal API Calls: Only essential data sent to external services
• Opt-in Features: All cloud features require explicit user consent
• Screen Capture: Screenshots encrypted and auto-deleted per user settings
• Kids Mode: PIN-protected with secure session management

• Basic activity tracking
• AI classification (basic)
• Simple reporting
• Kids Mode foundation

• Advanced AI recommendations
• Browser extension integration
• Productivity gamification
• Enhanced Kids Mode features

• Multi-device synchronization
• Team collaboration features
• Advanced machine learning models
• Mobile companion app

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

• Google Gemini: AI-powered insights and recommendations (planned)
• Electron Community: Cross-platform desktop application framework
• Python Community: Robust backend development ecosystem
• Contributors: All developers who help improve FocusAI Tracker

• Documentation: Wiki
• Issues: GitHub Issues
• Discussions: GitHub Discussions
• Email: [email protected]

Made with ❤️ by [Your Name]

Empowering productivity through intelligent computer usage insights