F1GPT - RAG Chat Bot

A sophisticated RAG (Retrieval-Augmented Generation) chatbot built with Next.js, LangChain.js, and OpenAI. This application provides intelligent responses by combining retrieval of relevant information with generative AI capabilities.

🚀 Features

• RAG Architecture: Combines document retrieval with AI generation for accurate responses
• Modern UI: Clean, responsive interface built with Next.js and Tailwind CSS
• Real-time Chat: Interactive chat experience with streaming responses
• Document Processing: Intelligent document parsing and vector storage
• OpenAI Integration: Powered by OpenAI's GPT models

🛠️ Tech Stack

• Frontend: Next.js 14, React, TypeScript
• Styling: Tailwind CSS
• AI/ML: LangChain.js, OpenAI API
• Database: Vector database for document storage

📋 Prerequisites

Before running this project, make sure you have:

• Node.js 18+ installed
• npm or yarn package manager
• OpenAI API key
• Git (for cloning the repository)

🚀 Getting Started

1. Clone the Repository

git clone https://github.com/yourusername/rag-chat-bot.git
cd rag-chat-bot/nextjs-f1gpt

2. Install Dependencies

npm install
# or
yarn install
# or
pnpm install

3. Environment Setup

Create a .env.local file in the root directory and add your environment variables:

OPENAI_API_KEY=your_openai_api_key_here
# Add other required environment variables

4. Run the Development Server

npm run dev
# or
yarn dev
# or
pnpm dev
# or
bun dev

Open http://localhost:3000 with your browser to see the result.

Screenshots

📁 Project Structure

nextjs-f1gpt/
├── app/
│   ├── api/
│   │   └── chat/
│   │       └── route.ts          # Chat API endpoint
│   ├── components/
│   │   ├── Bubble.tsx           # Chat bubble component
│   │   ├── LoadingBubble.tsx    # Loading animation
│   │   ├── PromptSuggestionButton.tsx
│   │   └── PromptSuggestionsRow.tsx
│   ├── assets/                   # Static assets
│   ├── global.css               # Global styles
│   ├── layout.tsx               # Root layout
│   └── page.tsx                 # Home page
├── scripts/
│   └── loadDb.ts                # Database loading script
└── README.md

🔧 API Routes

The application includes the following API endpoints:

• /api/chat - Main chat endpoint for processing user messages and generating responses

🚀 Deployment

Deploy on Vercel

The easiest way to deploy your Next.js app is to use the Vercel Platform from the creators of Next.js.

1. Push your code to GitHub
2. Connect your repository to Vercel
3. Add your environment variables in Vercel dashboard
4. Deploy!

Manual Deployment

npm run build
npm start

🤝 Contributing

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

📝 License

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

🙏 Acknowledgments

• Next.js for the amazing React framework
• LangChain.js for the AI orchestration
• OpenAI for the powerful AI models

📞 Support

If you have any questions or need help, please:

1. Check the Issues page
2. Create a new issue if your problem isn't already reported
3. Contact the maintainers --> widushanp@gmail.com

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Repository: https://github.com/widushan/RAG-Chat-Bot.git