This project implements a Retrieval-Augmented Generation (RAG) based chatbot designed to handle university-related queries using natural language understanding. It combines semantic search with generative AI to provide precise, context-aware answers to students, faculty, and visitors.

RAGent Chatbot is a smart AI assistant that combines Retrieval-Augmented Generation (RAG) with a tool-using LLM agent. It can answer user queries using uploaded documents, perform web searches, summarize text, solve math expressions, check weather, and more — all powered by LangChain, Qdrant, and Gemini.

A simple web app based on Streamlit, designed to interact with research papers using the ArXiv API and Langchain based LLM model.

Ecommerce chatbot enhances the shopping experience by offering personalized recommendations, and seamless customer support.

ecommerce ai chatbot enhances the shopping experience by offering personalized recommendations, and seamless customer support.

Langchain Tutorial

A RAG application for PDF data using the LaMini-T5-738M language model, Langchain and FAISS.