HyperLogic AI ChatBot

A powerful, fast, and feature-rich AI chatbot application with Python FastAPI backend and React frontend, featuring multi-provider LLM support, real-time messaging, conversation memory, and a beautiful responsive interface.

✨ Features

🚀 Core Features

Multi-Provider LLM Support: Google Gemini and more
Real-time Chat: WebSocket-based instant messaging
Conversation Memory: Context-aware conversations with persistent memory
Fast Performance: Optimized for speed and responsiveness
Beautiful UI: Modern, responsive design with Tailwind CSS

🎨 User Interface

Responsive Design: Works perfectly on desktop, tablet, and mobile
Dark/Light Theme: Customizable appearance
Smooth Animations: Framer Motion powered interactions
Real-time Typing Indicators: See when AI is responding
Message Actions: Copy, like, regenerate, and more

🧠 AI Capabilities

Context Awareness: Remembers conversation history
Provider Switching: Switch between different AI models
Fallback Support: Automatic fallback if primary provider fails
Response Streaming: Real-time response generation
Memory Management: Intelligent conversation summarization

📊 Conversation Management

Conversation History: Browse and search past conversations
Export/Import: Backup and restore conversations
Bulk Operations: Delete multiple conversations
Search & Filter: Find conversations quickly
Auto-save: Automatic conversation persistence

🛠️ Technology Stack

Frontend

React 18: Modern React with hooks and context
TypeScript: Type-safe JavaScript development
Node.js: JavaScript runtime for development
Vite: Fast build tool and dev server
Tailwind CSS: Utility-first CSS framework
Framer Motion: Smooth animations and transitions
Socket.io Client: Real-time communication
Axios: HTTP client for API calls
React Router: Client-side routing
React Hot Toast: Beautiful notifications

Backend (Python)

FastAPI: Modern web framework for building APIs
Uvicorn: ASGI server for FastAPI
WebSockets: Real-time communication
Google API: Gemini models integration
Pydantic: Data validation and serialization
Python-dotenv: Environment variable management
SlowAPI: Rate limiting
Socket.IO: Additional WebSocket support

Database

MongoDB: NoSQL database with localhost-only access
SQLite: Fallback database for development
Dual Support: Automatic database detection and switching
Local Storage: All data stored locally, no external connections

Docker & Deployment

Docker Compose: Multi-container orchestration
MongoDB Container: Local database with initialization
Nginx: Reverse proxy for production

🚀 Quick Start

Prerequisites

Python v3.14+ and pip (for backend)
Node.js v25+ and npm (for frontend development)
TypeScript knowledge (recommended)
Docker Desktop (for containerized deployment)
API keys for your preferred LLM providers

Installation

Clone the repository

git clone https://github.com/sudo-de/HyperLogic_AI_ChatBot.git
cd HyperLogic_AI_ChatBot

Install dependencies
```
npm run install-all
```
This will:
- Install frontend dependencies (React)
- Create Python virtual environment
- Install Python backend dependencies

Environment Setup

cp env.example .env

Edit .env and add your API keys:

GOOGLE_API_KEY=your_google_api_key_here
PORT=5000
CORS_ORIGIN=http://localhost:3000

Start with Docker (Recommended)

# Start MongoDB and backend
docker compose up -d mongodb hyperlogic-ai

# Start frontend locally
cd web && npm run dev

Start without Docker (Development)
```
./start.sh
```
This will start both the Python backend server (port 5000) and React frontend (port 3000).

Development Commands

# Docker Commands
docker compose up -d                    # Start all services
docker compose up -d mongodb            # Start only MongoDB
docker compose up -d hyperlogic-ai      # Start only backend
docker compose down                     # Stop all services
docker compose logs                     # View logs

# Frontend Development
cd web
npm install                            # Install dependencies
npm run dev                            # Start development server
npm run build                          # Build for production
npm run preview                        # Preview production build

# Backend Development
cd server
python -m venv venv                    # Create virtual environment
source venv/bin/activate               # Activate virtual environment
pip install -r requirements.txt       # Install dependencies
python run.py                          # Start backend server

# Full Stack Development
./start.sh                             # Start both frontend and backend

🔧 Configuration

Environment Variables

Variable	Description	Default
`PORT`	Server port	5000
`NODE_ENV`	Environment	development
`GOOGLE_API_KEY`	Google API key	-
`CORS_ORIGIN`	Frontend URL	http://localhost:3000
`MONGODB_URL`	MongoDB connection	mongodb://127.0.0.1:27017/hyperlogic_ai
`DATABASE_URL`	SQLite fallback	sqlite:///./hyperlogic_ai.db

Database Configuration

MongoDB (Production):

MONGODB_URL=mongodb://hyperlogic:password@127.0.0.1:27017/hyperlogic_ai?authSource=admin

SQLite (Development):

DATABASE_URL=sqlite:///./hyperlogic_ai.db

Automatic Detection:

If MONGODB_URL is set → Uses MongoDB
If not set → Falls back to SQLite

Adding New LLM Providers

Install the provider SDK
```
npm install provider-sdk
```

Add to LLMProvider service

// In server/services/llmProvider.js
addProvider('new-provider', newProviderInstance);

Update frontend provider list

// In web/src/components/Settings.js
const providers = ['google', 'new-provider'];

📱 Usage

Starting a Conversation

Click "New Conversation" in the sidebar
Type your message in the input field
Press Enter or click Send
Watch the AI respond in real-time

Managing Conversations

Search: Use the search bar to find specific conversations
Filter: Sort by date, title, or message count
Export: Download conversations as JSON files
Delete: Remove individual or multiple conversations

Settings

AI Provider: Switch between different AI models
Theme: Choose light, dark, or auto theme
Font Size: Adjust text size for better readability
Notifications: Enable/disable notifications

🏗️ Architecture

Backend Architecture (Python)

server/
├── main.py                  # FastAPI application
├── run.py                   # Application runner
├── requirements.txt         # Python dependencies
├── models/
│   └── schemas.py          # Pydantic models
└── services/
    ├── llm_provider.py     # Multi-provider LLM integration
    ├── conversation_manager.py # Conversation management
    ├── memory_manager.py   # Memory and context management
    └── websocket_manager.py # WebSocket handling

Frontend Architecture

web/src/
├── components/              # React components
│   ├── ChatInterface.js     # Main chat interface
│   ├── MessageBubble.js     # Individual message component
│   ├── Sidebar.js          # Conversation sidebar
│   ├── Settings.js         # Settings panel
│   └── Header.js           # App header
├── context/
│   └── AppContext.js       # Global state management
├── services/
│   ├── socketService.js    # WebSocket communication
│   └── apiService.js       # HTTP API calls
└── App.js                  # Main app component

🔒 Security Features

Rate Limiting: Prevents API abuse
CORS Protection: Secure cross-origin requests
Helmet: Security headers
Input Validation: Sanitized user inputs
Error Handling: Graceful error management

🚀 Deployment

Docker Deployment (Localhost-Only)

# Start all services with localhost-only access
docker compose up -d

# Start specific services
docker compose up -d mongodb hyperlogic-ai

# View logs
docker compose logs -f

# Stop all services
docker compose down

Environment Variables for Production

NODE_ENV=production
PORT=5000
GOOGLE_API_KEY=your_production_key
CORS_ORIGIN=https://yourdomain.com

Cloud Deployment

The application is ready for deployment on:

Vercel: Frontend deployment
Railway: Full-stack deployment
Heroku: Backend deployment
AWS or GCP: Scalable cloud deployment

🤝 Contributing

Fork the repository
Create a feature branch
Make your changes
Add tests if applicable
Submit a pull request

📄 License

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

🆘 Support

For support and questions:

Create an issue on GitHub
Check the documentation
Review the troubleshooting guide

🔮 Roadmap

Built with ❤️ by HyperLogic AI Team

Name		Name	Last commit message	Last commit date
Latest commit History 9 Commits
server		server
web		web
.dockerignore		.dockerignore
.gitignore		.gitignore
Dockerfile		Dockerfile
LICENSE		LICENSE
README.md		README.md
docker-compose.yml		docker-compose.yml
init-db.sql		init-db.sql
init-mongo.js		init-mongo.js
start.sh		start.sh
test.html		test.html

License

sudo-de/hyperlogic_ai_chatbot

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