University of Cincinnati Chatbot ( Unibot)

Description

This chatbot assists students at the University of Cincinnati by providing accurate, real-time answers to their queries. Built with the Retrieval-Augmented Generation (RAG) framework, the chatbot pulls data from university knowledge bases and uses advanced natural language processing (NLP) through LLAMA-3 for intelligent responses. The system is designed for scalability and ease of use, combining a serverless architecture with Cloudflare Workers for the backend.

Features

• Real-time, accurate responses using RAG and LLAMA-3 models.
• Serverless backend using Cloudflare Workers.
• Scalable and fast queries with Pinecone as the vector database.
• PostgreSQL for storing persistent data such as FAQs and logs.
• React-based frontend for a responsive user interface.

Technologies

• Backend: Serverless architecture powered by Cloudflare Workers.
• Frontend: React.js.
• Database: PostgreSQL (for data storage) and Pinecone (as a vector database for semantic search).
• Machine Learning: LLAMA-3 model integrated with the RAG framework for NLP.

Installation

Prerequisites

• Node.js v14+
• PostgreSQL
• Cloudflare Workers CLI (wrangler)
• Pinecone API access

Clone the Repository

git clone https://github.com/username/university-chatbot.git