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🎁 GiftGenius - AI Powered Gift Recommendation System

GiftGenius is an AI-powered, RAG-based gift recommendation system designed to help users find the perfect gift based on interests, budget, and occasion. Built for a 24-hour hackathon, this project leverages Retrieval-Augmented Generation (RAG), MySQL and a modern web stack to deliver personalized gift suggestions.


🚀 Tech Stack

  • Frontend: HTML, CSS, JavaScript
  • Backend: Node.js, Express.js
  • Database: MySQL (Hosted on Railway.app)
  • AI Model: Retrieval-Augmented Generation (RAG)

🎯 Features

✅ Smart AI-based gift recommendations
✅ Filters based on budget, interests, and occasion
✅ Responsive & user-friendly UI
✅ Hosted on GitHub Pages (Frontend) & Railway (Database & Backend)


🛠️ Setup & Installation

1️⃣ Clone the Repository

git clone https://github.com/your-username/GiftGenius.git
cd GiftGenius

2️⃣ Run the Frontend (Static Website)

Simply open index.html in a browser or deploy using GitHub Pages.


🗄️ Database Setup (For Backend Devs)

Our MySQL database is hosted on Railway.app. Below are the connection details:

Host: gondola.proxy.rlwy.net
User: root
Password: **************
Database: railway
Port: ******

To check database tables, run:

SHOW TABLES;

🔗 API Endpoints (Backend Devs)

Method Endpoint Description
GET /categories Fetch all gift categories
GET /gifts/:categoryId Fetch gifts by category
POST /search Store user search queries

These API endpoints allow the frontend to fetch real-time gift recommendations.


🚀 Deployment

  • Frontend: Hosted on GitHub Pages
  • Backend: To be hosted on Railway.app or Render
  • Database: Hosted on Railway MySQL

👨‍💻 Contributors

  • Frontend Developer: Gyanendra Dubey
  • Backend Developer: Shashwat Shukla
  • AI/ML Developer: Avanish Mishra
  • Database & Deployment: Mobashshir Ahsan

📜 License

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


About

GiftGenius is an AI-powered, RAG-based gift recommendation system developed for Innovathon 2025. It helps users find the perfect gift based on interests, budget, and occasion, using Retrieval-Augmented Generation (RAG) with HTML, CSS, JavaScript, Node.js, and MySQL to deliver intelligent and personalized suggestions.

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