Discord RAG Bot with Dashboard

A Discord bot with a web dashboard for managing RAG (Retrieval-Augmented Generation) entries and auto-responses. The dashboard syncs with the bot in real-time, allowing you to continuously improve the bot's knowledge base.

Features

• 🤖 Discord Bot: Automatically responds to forum posts using RAG and AI
• 📊 Web Dashboard: Manage RAG entries and auto-responses through a beautiful UI
• 🔄 Real-time Sync: Dashboard changes automatically sync to the bot
• 🎯 Smart Matching: Keyword-based matching with relevance scoring
• 🧠 AI-Powered: Uses Google Gemini AI for intelligent responses

Architecture

• Frontend: React + TypeScript + Vite (deployed on Vercel)
• Backend API: Vercel Serverless Functions
• Discord Bot: Python with discord.py
• AI: Google Gemini API

Setup Instructions

1. Clone and Install Dependencies

git clone <your-repo-url>
cd RAG-Bot-v2
npm install
pip install -r requirements.txt

2. Environment Variables

For the Dashboard (Vercel):

Create a .env file or set in Vercel dashboard:

VITE_API_URL=https://your-app.vercel.app/api

For the Bot:

Create a .env file in the root:

DISCORD_BOT_TOKEN=your_discord_bot_token
GEMINI_API_KEY=your_gemini_api_key
SUPPORT_FORUM_CHANNEL_ID=your_channel_id
DATA_API_URL=https://your-app.vercel.app/api/data

3. Discord Bot Setup

1. Go to Discord Developer Portal
2. Create a new application
3. Go to "Bot" section and create a bot
4. Copy the bot token
5. Enable these intents:
   • Message Content Intent
   • Server Members Intent
6. Invite bot to your server with appropriate permissions

4. Deploy Dashboard to Vercel

1. Push code to GitHub
2. Import project in Vercel
3. Set build command: npm run build
4. Set output directory: dist
5. Add environment variables in Vercel dashboard
6. Deploy!

5. Update Bot Configuration

After deploying to Vercel, update your bot's .env file:

DATA_API_URL=https://your-actual-vercel-url.vercel.app/api/data

6. Run the Bot

python bot.py

The bot will:

• Fetch initial data from the dashboard API
• Sync data every 5 minutes automatically
• Respond to new forum posts in your configured channel

Usage

Dashboard

1. Access your dashboard at https://your-app.vercel.app
2. Navigate to "RAG Management"
3. Add/Edit/Delete RAG entries and auto-responses
4. Changes automatically sync to the bot within 5 minutes
5. Use /reload command in Discord to force immediate sync

Bot Commands

• /reload - Manually reload data from dashboard (Admin only)
• /stop - Stop the bot gracefully (Admin only)

File Structure

├── api/
│   └── data.ts              # Vercel API route for data sync
├── components/              # React components
├── services/
│   ├── dataService.ts       # API service for dashboard
│   └── geminiService.ts     # Gemini AI service
├── hooks/
│   └── useMockData.ts       # Data management hook
├── bot.py                   # Discord bot
├── requirements.txt         # Python dependencies
└── package.json             # Node dependencies

How Syncing Works

1. Dashboard → Bot:

   • Dashboard saves changes to Vercel API
   • Bot polls API every 5 minutes
   • Bot updates its internal database

2. Bot → Dashboard:

   • Bot uses current data for responses
   • Dashboard fetches data on load
   • Both stay in sync automatically

Important Notes

⚠️ Current Implementation: The API uses in-memory storage, which resets on serverless function restarts. For production, you should:

• Use a database (Supabase, MongoDB Atlas, or Vercel Postgres)
• Implement proper authentication
• Add rate limiting
• Use environment variables for sensitive data

Troubleshooting

Bot not responding?

• Check bot is online in Discord
• Verify channel ID is correct
• Check bot has permissions in the channel

Data not syncing?

• Verify DATA_API_URL in bot's .env matches your Vercel URL
• Check API is accessible: curl https://your-app.vercel.app/api/data
• Check bot logs for error messages

Dashboard not loading?

• Verify build completed successfully
• Check Vercel deployment logs
• Ensure environment variables are set

Contributing

1. Fork the repository
2. Create a feature branch
3. Make your changes
4. Test thoroughly
5. Submit a pull request

License

MIT