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Superbot is an AI-powered automation assistant designed to plug into business workflows and act as the brain between users, databases, and systems. It understands natural language, converts intent into actions (like SQL queries, task insights, or summaries), and returns clean, human-friendly responses

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Rathore-Rajpal/Superbot-Demo

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🤖 AI Agent Superbot

A modern, intelligent AI assistant application built with React, TypeScript, and Supabase. Features a beautiful animated UI with chat capabilities and live database management.

🌐 Live Demo

superbot.rathorerajpal.live

✨ Features

  • 💬 AI Chat Interface - Interactive chat with an intelligent AI assistant
  • 📊 Live Database Dashboard - Real-time data visualization and management powered by Supabase
  • 🎨 Modern UI/UX - Beautiful gradient designs with smooth animations
  • ⚡ Fast & Responsive - Built with Vite for optimal performance
  • 🔐 Secure - Environment-based configuration with Supabase integration

🛠️ Tech Stack

  • Frontend Framework: React 18 with TypeScript
  • Build Tool: Vite
  • Styling: Tailwind CSS
  • UI Components: shadcn/ui
  • Database: Supabase (PostgreSQL)
  • Animations: Framer Motion
  • Icons: Lucide React

📂 Project Structure

superbot-demo/
├── src/
│   ├── components/          # React components
│   │   ├── ui/             # shadcn/ui components
│   │   ├── SupabaseDashboard.tsx
│   │   └── ...
│   ├── pages/              # Page components
│   │   ├── Home.tsx
│   │   ├── Index.tsx
│   │   └── Chat.tsx
│   ├── services/           # API & database services
│   │   └── supabaseService.ts
│   └── lib/                # Utilities
│       ├── supabase.ts
│       └── utils.ts
├── public/                 # Static assets
├── supabase-schema.sql    # Database schema
└── .env.example           # Environment variables template

🚀 Getting Started

Prerequisites

Installation

  1. Clone the repository

    git clone https://github.com/Rathore-Rajpal/Superbot-Demo.git
    cd Superbot-Demo
  2. Install dependencies

    npm install
  3. Set up environment variables

    cp .env.example .env

    Edit .env and add your Supabase credentials:

    VITE_SUPABASE_URL=your_supabase_url_here
    VITE_SUPABASE_ANON_KEY=your_supabase_anon_key_here
  4. Set up Supabase database

    • Go to your Supabase project dashboard
    • Navigate to SQL Editor
    • Copy and paste the contents of supabase-schema.sql
    • Run the SQL to create tables and sample data
  5. Start the development server

    npm run dev

    The app will be available at http://localhost:5173

📦 Build for Production

npm run build

The production-ready files will be in the dist/ directory.

🗄️ Database Schema

The application uses the following main tables:

  • tasks - Project tasks with status tracking
  • members - Team member profiles
  • projects - Project management data
  • leaves - Leave requests and approvals
  • daily_tasks - Daily task tracking

See supabase-schema.sql for complete schema and RLS policies.

🎯 Key Features Explained

Chat Interface

  • Clean, modern chat UI
  • Powered by AI capabilities
  • Real-time message handling

Database Dashboard

  • Live data from Supabase
  • Statistics overview cards
  • Tabbed interface for different data views
  • Sortable tables with status badges
  • Real-time updates

UI/UX Highlights

  • Animated gradient backgrounds
  • Floating particles effect
  • Smooth hover animations
  • Responsive design
  • Glass morphism effects

🔐 Environment Variables

Variable Description Required
VITE_SUPABASE_URL Your Supabase project URL Yes
VITE_SUPABASE_ANON_KEY Your Supabase anonymous/public key Yes

🤝 Contributing

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

👨‍💻 Author

Rajpal Rathore

📄 License

This project is open source and available under the MIT License.

🙏 Acknowledgments


⭐ If you find this project useful, please consider giving it a star!

About

Superbot is an AI-powered automation assistant designed to plug into business workflows and act as the brain between users, databases, and systems. It understands natural language, converts intent into actions (like SQL queries, task insights, or summaries), and returns clean, human-friendly responses

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