WARP-Amazon

🎓 Course Recommender System – Web App

This is a smart and user-friendly web application that recommends courses based on your interests. It combines a React frontend with a FastAPI backend and uses AI models like BERT and large language models (LLMs) to give personalized course suggestions.

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🧩 What It Does

• Stores user information in a secure database
• Uses a variety of courses from Coursera
• Recommends the best-fit courses using AI
• Personalized experience for every user

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🌟 Key Features

• 📚 Course listings with categories and ratings
• 🤖 Personalized course recommendations powered by AI
• 🔐 Secure data handling
• 🌐 Built with modern web technologies

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🛠️ Tech Stack

Frontend (React)

• React (JavaScript)
• Styled with Tailwind CSS

Backend (FastAPI)

• Python with FastAPI and Pydantic
• BERT model for understanding course/user data and user requirements
• LLM (Qwen2.5-14B-Instruct-W8A8-Dynamic-Per-Token) for smart recommendations

Database

• PostgreSQL
• SQLAlchemy

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🚀 How to Run the Project

1. Clone the repository

git clone https://github.com/AISocietyIITJ/WARP-Amazon.git
cd WARP-Amazon

2. Download the model

• Qwen 2.5-14B Instruct: https://huggingface.co/mohitdeharkar/warp_Qwen2.5-14B-Instruct/tree/main
• BERT fine-tuned model: https://huggingface.co/mohitdeharkar/warp_fine_tuned_bge_m3/tree/main

3. Run the Backend (FastAPI)

cd backend
python -m venv venv
source venv/bin/activate  # For Windows: venv\Scripts\activate
pip install -r requirements.txt
uvicorn main:app --reload

4. Run the Frontend (React JS)

cd frontend
npm install
npm start