gifts-shopping-store

Gift Shopping Store 🎁

A modern, full-stack e-commerce web application specialized in gift shopping. This project features a responsive user interface, complete cart and checkout flows, and a custom Machine Learning recommendation system.

🌟 Features

• Modern UI/UX: Responsive and premium design using HTML, CSS, and Vanilla JavaScript/React.
• Product Catalog: Browse a wide variety of gifts with categories and details.
• Shopping Cart: Session-based cart system to add, remove, and update quantities.
• Order Management: Complete checkout process and order history.
• AI Recommendations: Python-powered machine learning engine that suggests personalized gift recommendations for users.

🛠️ Tech Stack

• Frontend: Custom HTML/CSS/JS, React UI components (React Router DOM, Lucide Icons)
• Backend Server: Node.js & Express.js architecture
• Database: MongoDB for user data, products, and order histories
• Machine Learning: Python-based recommendation system (ml-model directory)

📁 Project Structure

gift-shopping-store/
├── client/         # React/Vanilla Frontend Code & UI components
├── server/         # Node.js/Express Backend API & routes
├── ml-model/       # Python Machine Learning recommendation engine
└── package.json    # Project dependencies and details

🚀 Getting Started

Prerequisites

• Node.js (for frontend and backend)
• MongoDB instance (local or Atlas)
• Python 3.x (for ML recommendation engine)

Setup Instructions

1. Clone the repository:

   git clone <repository-url>
   cd gift-shopping-store
   

2. Install Root/Client Dependencies:

   npm install
   cd client && npm install
   

3. Install Backend Dependencies:

   cd server && npm install
   

4. Install ML dependencies (if applicable):

   cd ml-model && pip install -r requirements.txt
   

5. Environment Variables: Make sure to configure your .env files in both the server and client directories with the appropriate database connection strings and environment variables.

Running the App Locally

To start the development servers, use the following commands from their respective directories:

Frontend Development Server:

cd client
npm start # or npm run dev

Backend Server:

cd server
npm start # or node server.js

ML Recommendation Service:

cd ml-model
python main.py # (or run according to the specific entry point)

💡 Acknowledgements

Built as a comprehensive full-stack showcase to integrate modern web technologies with machine learning.