AI Rate My Professor

AI Rate My Professor is an AI-powered web application that leverages Retrieval-Augmented Generation (RAG) to provide insightful and personalized reviews of professors. This application uses Pinecone for vector search, LangChain for chaining language models, and is built with Next.js and React.

Table of Contents

1. Live Demo
2. Features
3. Technology Stack
4. Future Improvements
5. Contact

Live Demo

Check out the live demo of the AI Rate My Professor application here.

Features

• AI-Driven Reviews: Get AI-generated reviews and ratings based on the latest and most relevant data.
• RAG Methodology: Utilizes Retrieval-Augmented Generation to provide accurate and contextually rich responses.
• Pinecone Integration: Fast and scalable vector search to ensure the most relevant information is retrieved.
• LangChain: Efficiently chains various language models for complex and nuanced review generation.
• User-Friendly Interface: Built with Next.js and React for a seamless and interactive user experience.

Technology Stack

• Frontend: Next.js, React
• Backend: Node.js, LangChain
• Database: Pinecone (for vector search)
• AI Models: OpenAI's GPT (integrated with RAG methodology)
• Hosting: Vercel (for deployment)

Future Improvements

• Enhanced Review Analysis: Implement sentiment analysis to provide more detailed insights into each review.
• User Customization: Allow users to input specific preferences for personalized reviews.
• Multi-language Support: Expand the application to support multiple languages.
• Mobile Optimization: Improve mobile responsiveness for a better user experience on smartphones and tablets.
• Analytics Dashboard: Add an analytics feature for tracking review trends and professor ratings over time.

Contributors

• [Christopher Sidarous]: Deployment and help with User Interface.
• [Isaac Shaker]: Backend; implementing Open AI with RAG and Picone.
• [Nicholas Lorenzi]: Designed Frontend and helped with User Interface.