OpenMed AI - Open Source Medical Data Analysis Platform

OpenMed AI is an open-source platform designed to democratize health data analysis by giving individuals the power to understand their own medical data through AI-powered insights. Upload your blood work, genetic testing results, and get personalized health insights through natural language conversations. Open med can also run 100% locally including local LLM support for complete data privacy! Check out the Live Demo

🌟 Mission

Healthcare data should be accessible and understandable to everyone. OpenMed AI empowers individuals to:

• Take ownership of their health data
• Gain insights from complex medical reports
• Make informed decisions about their health
• Bridge the gap between raw data and actionable knowledge

✨ Features

🩸 Blood Work Analysis

• Upload lab results (PDF, CSV, JSON formats)
• Automatic biomarker extraction and interpretation
• Reference range comparisons with visual indicators
• Trend analysis across multiple test dates
• Out-of-range value identification with explanations

🧬 Genetic Data Analysis

• Support for 23andMe, AncestryDNA, and other raw genetic data
• RSID-based variant lookup and interpretation
• Disease risk assessment based on genetic variants
• Pharmacogenomics insights for drug metabolism
• Evidence-based genetic recommendations

📚 Medical Literature Integration

• Real-time PubMed and medical database searches
• Evidence-based explanations for findings
• Latest research integration for personalized insights
• Citation-backed recommendations

🤖 AI-Powered Chat Interface

• Natural language conversations about your health data
• Multi-step analysis with tool calling
• Personalized insights based on your medical profile
• Interactive data visualizations and cards

🔒 Privacy & Security

• Local data processing options
• Encrypted data storage
• Row-level security policies
• Custom OpenAI API key support (bypass usage limits)
• Complete data ownership and control

📊 Advanced Features

• Usage limits with premium/basic tiers
• Demo mode with sample data
• Conversation history and management
• Medical profile integration
• Multi-model AI support (GPT-4, GPT-5 variants, local Ollama)

🛠 Tech Stack

• Frontend: Next.js 15, React 18, TypeScript, Tailwind CSS
• UI Components: shadcn/ui, Radix UI primitives
• Backend: Next.js API routes with serverless functions
• Database: Supabase (PostgreSQL) with Row Level Security
• AI/ML: OpenAI GPT models (GPT-4, GPT-4 Turbo, GPT-o1), Local Ollama models
• Authentication: Supabase Auth with social providers
• File Processing: PDF parsing, CSV processing, genetic data formats
• Deployment: Vercel (recommended) with Supabase cloud integration

📋 Prerequisites

Before you begin, ensure you have the following installed:

• Node.js 20+ (managed with nvm recommended)
• Docker Desktop (required for local Supabase)
• Git for version control
• OpenAI API key for AI features

🚀 Local Development Setup

1. Clone and Install

# Clone the repository
git clone https://github.com/ianrowan/OpenMed.git
cd OpenMed

# Use Node 20 (recommended)
nvm use

# Install all dependencies
npm install

2. Set Up Supabase Locally

# Start local Supabase (requires Docker Desktop)
npx supabase start

This will:

• Start PostgreSQL, Auth, Realtime, Storage, and Edge Functions
• Create a local Supabase instance on http://localhost:54323
• Provide local development keys

3. Configure Environment Variables

# Copy environment template
cp .env.example .env.local

After running npx supabase start, you'll see output with local credentials. Update .env.local:

# OpenAI Configuration
OPENAI_API_KEY=your_openai_api_key_here

# Local Supabase Configuration (from supabase start output)
NEXT_PUBLIC_SUPABASE_URL=http://localhost:54321
NEXT_PUBLIC_SUPABASE_ANON_KEY=your_local_anon_key
SUPABASE_SERVICE_ROLE_KEY=your_local_service_role_key

# Optional: Production Supabase (for deployment)
# NEXT_PUBLIC_SUPABASE_URL=your_production_supabase_url
# NEXT_PUBLIC_SUPABASE_ANON_KEY=your_production_anon_key
# SUPABASE_SERVICE_ROLE_KEY=your_production_service_role_key

4. Initialize Database Schema

Choose one of these methods to set up the database:

Option A: Command Line (Recommended)

# Apply database schema and seed data
cat complete_database_setup.sql | supabase db query

Option B: Supabase Dashboard

1. Visit the local dashboard: http://localhost:54323/
2. Navigate to SQL Editor
3. Copy and paste the contents of complete_database_setup.sql
4. Execute the SQL

5. Start Development Server

# Start the development server
nvm use && npm run dev

Open http://localhost:3000 to view the application.

🗂 Project Structure

OpenMed/
├── app/                    # Next.js 15 app router
│   ├── api/               # API routes
│   ├── auth/              # Authentication pages
│   ├── chat/              # Chat interface
│   └── dashboard/         # User dashboard
├── components/            # Reusable React components
│   ├── chat/             # Chat-related components
│   ├── dashboard/        # Dashboard components
│   └── ui/               # shadcn/ui components
├── lib/                  # Utility functions and configurations
├── supabase/            # Database migrations and types
├── tools/               # AI function calling tools
└── types/               # TypeScript type definitions

🚨 Medical Disclaimer

IMPORTANT: This application is for informational and educational purposes only. It is not intended to diagnose, treat, cure, or prevent any disease. Always consult with a qualified healthcare professional for medical advice. Do not make medical decisions based solely on this application.

🧪 Using the Application

Demo Mode

• Visit the application without signing up to explore sample data
• Try uploading the provided sample files in /sample-data/
• Experience the full feature set with test medical data

Production Usage

1. Create an account or sign in
2. Upload your medical data:
   • Blood work (PDF lab reports, CSV exports)
   • Genetic data (23andMe, AncestryDNA raw files)
3. Chat with your data using natural language
4. Explore insights through AI-powered analysis
5. Optional: Add your own OpenAI API key to bypass usage limits

🔧 Development Commands

# Development
nvm use && npm run dev     # Start development server
npm run build             # Build for production
npm run start             # Start production build

# Database
npx supabase start        # Start local Supabase
npx supabase stop         # Stop local Supabase
npx supabase db reset     # Reset local database
npx supabase db query     # Run SQL queries

# Code Quality
npm run lint              # Run ESLint
npm run type-check        # TypeScript type checking

🚀 Deployment

Vercel + Supabase Cloud (Recommended)

1. Deploy to Vercel:

   # Deploy with Vercel CLI
   npx vercel --prod

2. Set up production Supabase:

   • Create a new project at supabase.com
   • Run the database setup SQL in the Supabase dashboard
   • Update environment variables in Vercel

3. Configure environment variables in Vercel dashboard with production values

🤝 Contributing

We welcome contributions to democratize health data analysis! Here's how to get involved:

Getting Started

1. Fork the repository
2. Create a feature branch: git checkout -b feature/amazing-feature
3. Follow the local development setup above
4. Make your changes and test thoroughly
5. Submit a pull request

Development Guidelines

• Follow existing code style and TypeScript patterns
• Add tests for new features
• Update documentation for user-facing changes
• Keep medical accuracy and user privacy as top priorities

Areas for Contribution

• 🧬 Additional genetic data format support
• 📊 New data visualization components
• 🔍 Enhanced medical literature search capabilities
• 🌐 Internationalization and accessibility
• 📱 Mobile application development
• 🔒 Additional privacy and security features

🤝 Support & Community

• Issues: Report bugs or request features via GitHub Issues
• Discussions: Join community discussions in GitHub Discussions