GluCoPilot - AI-Powered Diabetes Management

A comprehensive, offline-first diabetes management app combining real-time CGM data, activity tracking, food logging, and AI-powered insights to help Type 1 diabetics optimize glucose control.

🚀 Quick Start (Recommended)

For seamless development and debugging, always use the provided script:

./scripts/start_glucopilot.sh

This script: - Sets up and checks your Python/Node environments - Handles backend and frontend dependencies - Configures your local IP for mobile debugging - Starts both backend (FastAPI) and frontend (Expo) servers - Ensures a clean, reproducible dev environment

If you encounter issues, re-run the script to rule out environment/config problems before investigating code bugs.

✨ Core Features

📊 Data Ingestion

• Real-time CGM data from Dexcom
• Apple HealthKit/Google Fit for activity, sleep, heart rate
• MyFitnessPal integration for food logging
• Manual/scan food entry, insulin tracking, mood, sleep, medication, illness, menstrual cycle

🧠 AI-Powered Analysis

• Multi-stream pattern recognition (glucose, food, insulin, activity, sleep, mood, etc.)
• Personalized LLM-generated insights and recommendations
• Community wisdom from r/T1D
• Predictive, actionable suggestions
• Outlier and correlation analysis

📱 User Experience

• Interactive dashboard with real-time trends
• Multi-data visualizations
• Simple service integration UI
• Offline-first, privacy-focused (all data local)
• Actionable, time-specific insights

🏗 Architecture

GluCoPilot/
├── backend/           # Python FastAPI server
├── frontend/          # React Native mobile app
├── ai/                # Local AI models and processing
├── database/          # SQLite schema and migrations
├── docs/              # Documentation
└── scripts/           # Utility and setup scripts

🛠 Manual Setup (Advanced/CI Only)

If you must set up manually (not recommended for dev):

1. Clone repo: git clone https://github.com/EricSpencer00/GluCoPilot.git && cd GluCoPilot
2. Backend: cd backend && python -m venv venv && source venv/bin/activate && pip install -r requirements.txt
3. Frontend: cd frontend && npm install
4. Configure env: cp backend/.env.example backend/.env (edit as needed)
5. DB: cd backend && python -m alembic upgrade head
6. Start backend: uvicorn main:app --reload --host 0.0.0.0 --port 8000
7. Start frontend: cd frontend && npx expo start --clear

📊 Data Sources

� Privacy & Security

• All data stored and processed locally
• SQLite encrypted at rest
• No cloud dependencies
• Open source and auditable

🤝 Contributing

See Contributing Guide for details.

📄 License

MIT License - see LICENSE

🙋‍♂️ Support

Open an issue or contact the dev team.

Built with ❤️ for the Type 1 Diabetes community