AI Chat Application

A sophisticated conversational AI platform leveraging OpenAI's GPT models to create dynamic, context-aware chat interactions for social skills development and assessment.

Technical Overview

Architecture

• Frontend: React 18 SPA with Vite build tooling
• Backend: Express.js REST API with MongoDB persistence
• AI Integration: OpenAI GPT-4 with custom prompt engineering and context management
• Real-time Features: Dynamic typing indicators, message queuing, and state management
• Styling: Tailwind CSS with custom theming and responsive design

Key Features

AI Conversation Engine

• Context-aware dialogue management with persona-specific conversation styles
• Real-time response generation with custom prompt templates
• Sophisticated conversation scoring algorithm using multiple evaluation criteria
• Adaptive conversation flow based on user interaction patterns

User Experience

• Real-time chat interface with typing indicators and message animations
• Dark/light theme support with seamless transitions
• Responsive design optimized for all device sizes
• Accessibility-focused component architecture

Backend Systems

• RESTful API with Express.js
• MongoDB integration with Mongoose ODM
• Custom middleware for authentication and request handling
• Conversation state management and persistence

Performance Optimizations

• Efficient React component rendering with proper hooks usage
• Optimized database queries with proper indexing
• Frontend bundle optimization with Vite
• Lazy loading and code splitting

Technical Stack

Frontend

{
  "framework": "React 18",
  "buildTool": "Vite",
  "styling": ["Tailwind CSS", "Material-UI"],
  "stateManagement": "React Hooks",
  "ui/uxLibraries": ["Lucide Icons", "React Hot Toast"]
}

Backend

{
  "runtime": "Node.js",
  "framework": "Express.js",
  "database": "MongoDB",
  "orm": "Mongoose",
  "aiIntegration": "OpenAI API"
}

Development Setup

1. Clone and install dependencies:

git clone https://github.com/yourusername/ai-chat-app.git
cd ai-chat-app
npm install

2. Configure environment variables:

OPENAI_API_KEY=your_api_key
MONGODB_URI=your_mongodb_uri

3. Start development servers:

# Frontend
npm run dev

# Backend
npm run server

API Documentation

Chat Endpoints

POST /chat/init
- Initialize chat session with selected persona
- Query params: opponentId, username, password

POST /chat/message
- Send message and receive AI response
- Query params: username, password
- Body: { newMessage: string }

POST /chat/clear
- End chat session and clear history
- Query params: username, password

System Architecture

├── Frontend (React + Vite)
│   ├── Components
│   │   ├── Chat Interface
│   │   ├── Scoring System
│   │   └── User Management
│   └── State Management
│       └── React Hooks
│
├── Backend (Express.js)
│   ├── API Routes
│   ├── Controllers
│   ├── Middleware
│   └── Models
│
└── Database (MongoDB)
    └── Conversation Storage

Engineering Highlights

• Scalable Architecture: Modular component design with clear separation of concerns
• AI Integration: Sophisticated prompt engineering and context management
• Performance: Optimized rendering and state management
• Security: Request validation, error handling, and secure data persistence
• Code Quality: TypeScript integration, ESLint configuration, and consistent coding standards

Future Enhancements

• WebSocket integration for real-time features
• Enhanced analytics and performance monitoring
• Additional AI model integration options
• Advanced conversation scoring algorithms
• User authentication system expansion

Contributing

1. Fork the repository
2. Create your feature branch: git checkout -b feature/amazing-feature
3. Commit your changes: git commit -m 'Add amazing feature'
4. Push to the branch: git push origin feature/amazing-feature
5. Open a Pull Request

License

MIT License - see LICENSE.md for details