Batteries included SDK for RAG development.

AnythingLLM Embed widget submodule for the main AnythingLLM application

x0-GPT is an advanced AI-powered tool that enables you to interact seamlessly with any website or document (including PDFs) using natural language. Whether you're looking to extract specific data, automate tasks, or gain insights, x0-GPT makes it possible with ease. Best of all, it's free and accessible to everyone.

An open-source template for building a RAG chatbot for your company 🤖

End-to-end deployment of a scalable RAG chatbot utilizing LangChain for retrieval-based QnA. The project leverages robust CI/CD practices integrating MLFlow with emphasizes on cost analysis.

AI-Rag-ChatBot is a complete project example with RAGChat and Next.js 14, using Upstash Vector Database, Upstash Qstash, Upstash Redis, Dynamic Webpage Folder, Middleware, Typescript, Vercel AI SDK for the Client side Hook, Lucide-React for Icon, Shadcn-UI, Next-UI Library Plugin to modify TailwindCSS and deploy on Vercel.

Your One-Stop Gateway to the Ultimate Unified AI Assistant for All Your Needs.

A full-stack, microservices-based application for secure document management, enabling users to upload, parse, index, and query various file types through advanced NLP and RAG agents. Built with Docker and Kubernetes for scalability, and integrates Elasticsearch, Redis, and AWS S3 for efficient storage and search capabilities.

SOC Analyst Automation using a RAG model integrates a knowledge retrieval system with generative AI to automate SOC Level-1 tasks. It processes server logs, retrieves relevant security insights, and generates accurate responses, enhancing incident analysis, reducing response times, and improving efficiency in handling cybersecurity threats through

This project implements a Retrieval-Augmented Generation (RAG) model that uses a directory containing text files as documents for information retrieval and generation. The model combines retrieval and generation capabilities to answer questions based on the provided documents.

An AI-driven solution for optimizing patient scheduling and resource allocation in healthcare facilities. This project features a predictive analytics dashboard powered by Prophet for forecasting patient inflows, real-time staffing recommendations, and an interactive chatbot using LangChain and Neo4j for data-driven insights.

Use RAG with Langchain to chat with your data and display the retrieved source(s)

Hybrid Search RAG Pipeline integrating BM25 and vector search techniques using LangChain

basic-rag

A chatbot to chat with content of any website with RAG implemention.

This web application allows users to interact with a chatbot that can answer questions about any website. Simply enter the URL of the site you’re interested in, and the chatbot will provide insights and answer questions related to the content of that site.

A Retrieval-Augmented Generation (RAG) Chatbot built on top of ChatGPT. Just upload your document and ask DocuMate anything about it.

A chatbot assistant that provides tailored products guidance to customers, using custom RAG from custom data.

Building a PDF Chatbot with Google Gemma 7B LLM using Groq API and Chainlit

RAG chatbot which can be trained on any website! made using Upstash vector database, redis, and NEXTJS