wehub-resource-sync
11 KiB
FemTracker Agent - AI-Powered Women's Health Companion
2. Use Case
FemTracker Agent is an innovative AI-powered women's health tracking platform that leverages cutting-edge multi-agent technology to provide personalized health insights, cycle predictions, and comprehensive wellness monitoring. The system features 8 specialized AI agents that work together to deliver intelligent health assistance, real-time analytics, and WHO-standard health scoring.
Key Problems Solved:
- Complex health data tracking and pattern recognition across multiple health domains
- Lack of personalized, AI-driven health insights and recommendations for women's health
- Fragmented health management between cycle tracking, fertility, nutrition, and fitness
- Limited conversational AI assistance for women's health-specific concerns
- Need for intelligent coordination and orchestration of specialized health agents
3. Technologies Used
Frontend Stack:
- Next.js 15 (App Router)
- React 19
- TypeScript 5
- CopilotKit (AI Integration & Conversational Interface)
- TailwindCSS + Custom Design System
- Radix UI Components
- Framer Motion
Backend & AI Stack:
- Python 3.12
- LangGraph (AI Agent Orchestration)
- OpenAI GPT-4
- Supabase PostgreSQL
- Redis (Performance Optimization)
- Vercel Blob Storage
Specialized AI Agents:
- Main Coordinator Agent (CopilotKit Integration)
- Cycle Tracker Agent
- Fertility Tracker Agent
- Symptom Mood Agent
- Nutrition Guide Agent
- Exercise Coach Agent
- Lifestyle Manager Agent
- Health Insights Agent
4. GitHub + YouTube
-
GitHub Repo: https://github.com/ChanMeng666/femtracker-agent
-
Deployed Demo: https://femtracker-agent.vercel.app/
Note: Include a screenshot of your demo in action
6. Who Are You?
Chan Meng - AI & Healthcare Technology Developer
LinkedIn: chanmeng666
⭐️ Project README with installation and getting started steps ⭐️👇
🌸 FemTracker Agent
AI-Powered Women's Health Companion
An innovative women's health tracking platform that leverages cutting-edge AI multi-agent technology to provide personalized health insights, cycle predictions, and comprehensive wellness monitoring.
Built with CopilotKit for seamless conversational AI experience
🌟 Introduction
FemTracker Agent is a cutting-edge women's health companion that combines the power of AI multi-agent systems with comprehensive health tracking. Built with CopilotKit integration, it features 8 specialized AI agents that provide personalized health insights, cycle predictions, and wellness monitoring through natural language conversations.
✨ Key Features
🤖 CopilotKit-Powered Conversational AI
- Natural Language Interface: Seamless conversation with health AI agents
- Intelligent Agent Coordination: CopilotKit orchestrates 8 specialized health agents
- Real-time AI Assistance: Instant health guidance and recommendations
- Context-Aware Responses: AI understands your health history and patterns
📊 AI Multi-Agent Architecture
- Main Coordinator Agent: Routes queries to specialized agents via CopilotKit
- Cycle Tracker Agent: Menstrual cycle prediction and pattern analysis
- Fertility Tracker Agent: Ovulation prediction and conception guidance
- Symptom Mood Agent: Emotional health and symptom pattern recognition
- Nutrition Guide Agent: Personalized dietary recommendations
- Exercise Coach Agent: Cycle-aware fitness guidance
- Lifestyle Manager Agent: Sleep optimization and stress management
- Health Insights Agent: AI-powered analytics and correlation analysis
💎 Advanced Health Analytics
- WHO-Standard Scoring: Medical-grade health metrics (0-100 scores)
- Predictive Insights: AI-powered trend analysis and health forecasting
- Correlation Analysis: Identify patterns between lifestyle factors and health
- Real-time Synchronization: Live updates across all health modules
🚀 Getting Started
Prerequisites
# Required
Node.js 18.0+
Python 3.12+
Supabase Account
OpenAI API Key
# Optional for enhanced performance
Redis
Quick Installation
1. Clone Repository
git clone https://github.com/ChanMeng666/femtracker-agent.git
cd femtracker-agent
2. Frontend Setup
npm install
# or
pnpm install
3. AI Agent Setup
cd agent
python -m venv venv
source venv/bin/activate # Windows: venv\Scripts\activate
pip install -r requirements.txt
Environment Configuration
Frontend (.env.local):
# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here
# Supabase Configuration
NEXT_PUBLIC_SUPABASE_URL=your_supabase_project_url
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_supabase_anon_key
SUPABASE_SERVICE_ROLE_KEY=your_supabase_service_role_key
# CopilotKit Agent Configuration
NEXT_PUBLIC_COPILOTKIT_AGENT_NAME=main_coordinator
NEXT_PUBLIC_COPILOTKIT_AGENT_DESCRIPTION="AI health companion with specialized agents for women's health tracking"
# Optional: Redis for Performance
REDIS_URL=your_redis_connection_string
Backend (agent/.env):
# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here
Database Setup
Execute SQL files in your Supabase SQL Editor in order:
database/1-database-setup.sql- Core schemadatabase/2-database-fix.sql- RLS policiesdatabase/6-fertility-tables.sql- Fertility trackingdatabase/7-recipe-tables.sql- Recipe management- Additional SQL files as needed
Development Mode
Terminal 1 - AI Agent System:
cd agent
langgraph dev
Terminal 2 - Frontend:
npm run dev
Access Application:
- Frontend: http://localhost:3000
- AI Agent System: http://localhost:2024
🏗️ CopilotKit Integration Architecture
Agent Coordination Flow
graph TB
subgraph "CopilotKit Interface"
A[User Input] --> B[CopilotKit Provider]
B --> C[Conversational AI]
end
subgraph "Agent Orchestration"
D[Main Coordinator] --> E{Intelligent Routing}
E --> F[Specialized Agents]
F --> G[Health Processing]
end
subgraph "Response Generation"
H[Agent Responses] --> I[CopilotKit State]
I --> J[User Interface]
end
C --> D
G --> H
J --> A
CopilotKit Agent Configuration
// src/app/api/copilotkit/route.ts
const agents = [
{
name: "main_coordinator",
description:
"Main health coordinator that routes requests to specialized agents",
graph_id: "main_coordinator",
},
{
name: "cycle_tracker",
description:
"Specialized agent for menstrual cycle tracking and predictions",
graph_id: "cycle_tracker",
},
// Additional specialized agents...
];
💬 Usage Examples
Natural Language Health Conversations
Cycle Tracking:
User: "I think my period started today, can you help me track it?"
AI: "I'll help you track your period! Let me log that your cycle started today and update your predictions. Based on your history, your next period is likely around [date]. How is your flow today - light, medium, or heavy?"
Fertility Monitoring:
User: "Am I in my fertile window this week?"
AI: "Based on your cycle data, you're approaching your fertile window! Your predicted ovulation is in 2-3 days. I recommend tracking your BBT and cervical mucus for more accurate predictions. Would you like me to set up reminders?"
Health Insights:
User: "I've been feeling more tired lately, any patterns you notice?"
AI: "I've analyzed your recent data and noticed your fatigue tends to increase during the luteal phase of your cycle, which is normal. Your sleep quality has also decreased by 15% this week. Let me suggest some cycle-aware wellness strategies..."
🎯 Key Benefits
- 🤖 Conversational AI: Natural language interaction via CopilotKit
- 🧠 Multi-Agent Intelligence: 8 specialized agents for comprehensive health support
- 📊 Medical-Grade Analytics: WHO-standard health scoring algorithms
- 🔒 Privacy-First: Military-grade encryption for all health data
- 📱 Mobile-Optimized: Progressive Web App with offline capabilities
- ⚡ High Performance: 95+ Lighthouse score, Redis caching, real-time sync
- 🌐 Accessible: WCAG 2.1 compliant for inclusive health tracking
🛳 Deployment
Vercel (Frontend)
LangGraph Platform (AI Agents)
cd agent
langgraph up
Manual Deployment
# Install Vercel CLI
npm i -g vercel
# Deploy frontend
vercel --prod
# Deploy AI agents
cd agent && langgraph up
🤝 Contributing
We welcome contributions to advance women's health technology:
- Fork the repository
- Create feature branch (
git checkout -b feature/health-improvement) - Follow development guidelines (TypeScript, accessibility, medical accuracy)
- Add comprehensive tests for health modules
- Submit pull request with detailed description
Contribution Areas:
- 🤖 New AI agent capabilities
- 📊 Health analytics improvements
- 🎨 UI/UX enhancements
- 📚 Documentation and guides
- 🔒 Security and privacy features
📄 License
This project is licensed under the MIT License - see the LICENSE file for details.
🙏 Acknowledgments
- CopilotKit Team for providing exceptional AI integration capabilities
- LangGraph for powerful agent orchestration framework
- Supabase for robust database and authentication services
- WHO Guidelines for health standard compliance
- Open Source Community for advancing women's health technology
🌟 Star History
If you find FemTracker Agent helpful, please consider giving it a star!
Built with CopilotKit • Pioneering the future of conversational healthcare
⭐ Star us on GitHub • 🚀 Try Live Demo • 🤖 Explore AI Agents • 🤝 Join Community
Made with ❤️ for women's health empowerment