AI-powered customer support email automation system built with Langchain & Langgraph

This python powered AI based RAG Scraper allows you to ask question based on PDF/URL provided to the software using local Ollama powered LLMs

pdfKotha.AI - Interact with PDFs using AI! Upload, ask questions, and get instant answers from Google's Gemini model. Streamline your research and information retrieval tasks effortlessly

ML Bot is a RAG Application built using google/gemma-2b-it local LLM

A supportive server to handle telegram messages using telegram bot API, return back the response to the user with RAG application techniques

Have a chat with your documents, research papers and textbooks (RAG)

A simple Retrieval-Augmented Generation (RAG) web application chatbot called Raggy 🤖

Learn Retrieval-Augmented Generation (RAG) from Scratch using LLMs from Hugging Face and Langchain or Python

A basic RAG application for inventory management. Provides real-time stock updates, checks availability, suggests similar products, and generates responses to both customer and manager queries .

LLM based rag application that embed given web page to vector db and answer given query using vector similarity cosine.

A Customizable RAG (Retrieval Augmented Generation) App

A dynamic web application made using MERN stack

This project utilizes advanced Large Language Models (LLMs) and vector database technologies to extract structured information about characters from literary texts. It is designed to analyze a given text, identify key characters, and determine their summaries, relationships, and roles (e.g., Protagonist, Antagonist, or Side character)