Multi AI agents for customer support email automation built with Langchain & Langgraph

Multi Generative AI agents for customer support email automation built with Golang, Google-GenAi and Customgraph solution

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

🛡️ Web3 Guardian is a comprehensive security suite for Web3 that combines browser extension and backend services to provide real-time transaction analysis, smart contract auditing, and risk assessment for decentralized applications (dApps).

RAG-API: A production-ready Retrieval Augmented Generation API leveraging LLMs, vector databases, and hybrid search for accurate, context-aware responses with citation support.

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

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.

BetterRAG: Powerful RAG evaluation toolkit for LLMs. Measure, analyze, and optimize how your AI processes text chunks with precision metrics. Perfect for RAG systems, document processing, and embedding quality assessment.

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 .

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

🤖 NoCapGenAI is a Retrieval-Augmented Generation (RAG) chatbot built with Streamlit, Ollama, MongoDB, and ChromaDB. It features a clean, modern UI and persistent vector memory for context-aware conversations. Easily integrates with Ollama-supported models like phi3:mini, llama3, mistral, and more. Designed to support customizable assistant modes

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

AI-powered platform that turns study notes into podcast episodes with two hosts and lets you chat with documents.

This project processes and retrieves information from PDF file or PDF collection. It leverages Qdrant as a vector database for similarity searches and employs a Retrieval-Augmented Generation (RAG).

A custom Agentic Retrieval-Augmented Generation (RAG) model that is an expert in cell culture techniques and knowledge.

The Coursera QA Assistant is a browser extension that helps learners get answers to their questions about Coursera course content directly from the course page they're viewing. The extension uses AI to analyze the course content and provide relevant answers.

Ask questions. Get answers. Unlock insights from SEC 10-K filings with Generative AI.

🚀 VIDGENIUS AI — An open-source RAG-powered app that transforms YouTube videos into interactive chat experiences and smart, structured notes. Paste any video link with language code, translate instantly, extract insights, and chat with the content — all in one click.

A Customizable RAG (Retrieval Augmented Generation) App