An intelligent AI-powered chat assistant built with React, Vite, and modern web technologies.
| Hemendra Harsh | Developer | Geeky Nomads |
Creating a powerful, user-friendly AI chat interface that combines modern UI design with intelligent assistance capabilities.
- Context: Users need an accessible platform for interacting with AI while maintaining a clean, responsive interface.
- Impact: Provides a seamless experience for users seeking AI-powered assistance in their daily tasks.
Zenith AI Assistant delivers a modern chat interface with:
- Smart Chat Interface: Real-time message processing with markdown support for rich content display.
- Customizable Settings: Theme support (light/dark mode) and configurable AI parameters for personalized experience.
- Responsive Design: Mobile-first approach with Tailwind CSS ensuring excellent UX across all devices.
| Category | Technologies Used |
|---|---|
| Frontend | React 18, TypeScript, Tailwind CSS, Vite |
| UI Library | Lucide Icons, React Markdown |
| Tools | ESLint, PostCSS, Autoprefixer |
| Utilities | nanoid (unique ID generation) |
- Chat Interface: Full-featured message input and display with markdown rendering
- Dark/Light Theme: Toggle between themes for comfortable viewing
- Sidebar Navigation: Organized conversation history and quick access to settings
- Settings Modal: Customizable AI parameters and preferences
- Prompt Templates: Pre-built templates for common queries
- Responsive Layout: Mobile-friendly design using Tailwind CSS Getting Started
# Install dependencies
npm install
# Run development server
npm run dev
# Build for production
npm run build
# Lint code
npm lintsrc/
├── components/ # React components (ChatInput, Header, MessageList, etc.)
├── context/ # React Context providers (ThemeContext, ZenithContext)
├── utils/ # Utility functions and constants
├── App.tsx # Main application component
├── main.tsx # Application entry point
└── index.css # Global styles
``
> **Testing Credentials**
> * **User:** `user@demo.com`
> * **Pass:** `hack2026`
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### 🏆 Acknowledgements
This project was developed during **TechSprint Hackathon 2026**, organized by **GDG on Campus Galgotias University**.