AI Community Rewards + Telegram Mini App

A Telegram Mini App (TMA) that rewards active community participation through AI-powered analysis and blockchain rewards, powered by Dynamic wallet integration.

Overview

This project combines Telegram's Mini App functionality with AI-driven community engagement tracking and blockchain rewards. It:

• Analyzes and scores user interactions in Telegram communities
• Distributes ERC20 token rewards across Starknet and EVM chains
• Provides seamless wallet integration through Dynamic
• Ensures secure data handling with Phala Network and Nillion

Quick Start

1. Create a Telegram Bot:

   • Use BotFather to create your bot
   • Save the Bot TOKEN for later use

2. Setup the project:

   git clone <repository-url>
   cp .env.sample .env

   Update .env with:

   • Your Dynamic environment ID (NEXT_PUBLIC_DYNAMIC_ENV_ID)
   • Bot TOKEN from Telegram
   • Website URL as LOGIN_URL

3. Deploy the website:

   • Follow Vercel deployment guide
   • Or use your preferred hosting solution

4. Configure Telegram Mini App:

   • Use BotFather to set up your Mini App
   • Add your deployed website URL

5. Run the Telegram bot:

   # Install ts-node if you haven't already
   npm -g i ts-node
   
   # Run the bot
   ts-node scripts/bot.ts

6. Test the integration:

   • Go to your Telegram Bot
   • Type /start

Technical Architecture

The system leverages several key technologies:

• AI Processing & Security

  • Phala Network for Remote Attestation
  • Red Pill API for conversation analysis

• Data Privacy

  • Nillion for encrypted storage
  • Secure API endpoints for data access

• Blockchain Integration

  • Dynamic for embedded wallets
  • Multi-chain support (Starknet & EVM)

Environment Variables

BOT_TOKEN=your_telegram_bot_token LOGIN_URL=your_deployed_website_url

Resources

• Build Around the Telegram Ecosystem
• Telegram Mini Apps Documentation
• Dynamic Documentation

Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

License

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