Registration Info RAG

Overview

This project is a Flask-based server designed to handle a registration information retrieval system using Retrieval-Augmented Generation (RAG). The primary functionality of this server is to answer queries related to registration information by leveraging a combination of retrieval and generative AI techniques.

Features

• Handles user queries related to registration information.
• Utilizes a retrieval-augmented generation approach to provide accurate and relevant answers.
• Provides a Flask-based API for easy integration with other applications.
• Includes an ngrok setup for exposing the local server to the internet.

Setup

Prerequisites

Before you begin, ensure you have the following installed:

• Python 3.7 or higher
• Flask
• Flask-CORS
• ngrok

Installation

1. Clone the repository:

   git clone https://github.com/Kaushik0126/Registration_Info_LLM_Backend.git
   cd Registration_Info_LLM_Backend

2. Install dependencies:

   pip install -r requirements.txt

3. Start the Flask server:

   python app.py

4. Start ngrok:

   ngrok http 5000

   This will provide a public URL to access the Flask server.

Usage

API Endpoints

• Home Endpoint

  GET /

  Returns a welcome message indicating the server is running.

• Query Endpoint

  POST /query

  Expects a JSON payload with the following structure:

  {
      "question": "Your question here"
  }

  Example:

  curl -X POST http://localhost:5000/query -H "Content-Type: application/json" -d '{"question":"What is the registration deadline?"}'

  Response:

  {
      "response": "The registration deadline is July 31st."
  }

Frontend

View on GitHub

The frontend part of this application is available on GitHub. You can clone the repository and run it locally to see the frontend in action.

1. Clone the frontend repository:

   git clone https://github.com/Kaushik0126/Registration_Info_LLM.git
   cd Registration_Info_LLM

2. Install dependencies:

   npm install

3. Start the frontend server:

   npm start

Live Demo

You can also view the live demo of the frontend here.

Contributing

Contributions are welcome! Please follow these steps:

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

Acknowledgements

This project was created using the Flask framework and leverages ngrok for local development. Special thanks to the open-source community for their contributions and support.