Prototype SDK for RAG development.

AnythingLLM Embed widget submodule for the main AnythingLLM application

pdfLLM is a completely open source, proof of concept RAG app. Laravel + Python + Postgre and pgVector.

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.

Terraform-based Infrastructure as Code (IaC) for deploying complete AWS backend services, integrated with Google's free-tier Gemini Pro and Gemini Embedding models for AI powered document querying including Remote Streamable HTTP based Web Search MCP Server,streamlit UI..

Welcome to some case study of data science projects - (Personal Projects).

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

AI-powered chatbot that provides guidance using YouTube video content as a knowledge base. Built with RAG architecture using LangChain, Qdrant, and Google Gemini AI, ElevenLabs and Streamlit.

An Interactive Infinite Story Generation Framework Based on Multi-Agent

A Retrieval-Augmented Generation (RAG) Chat Bot that provides accurate responses based on available documents. This application uses PostgreSQL with pgvector extension for storing and searching vector embeddings, and OpenAI for generating embeddings and responses.

A RAG agent using Google's ADK & Vertex AI that lets set up semantic search across documents in under 2 minutes. Features GCS integration and natural language querying

Fullstack RAG as a service template

IAttorney is an intelligent legal assistant built using Flask, LangChain, FAISS, OpenAI, and a RAG (Retrieval-Augmented Generation) pipeline.

MediNotes: SOAP Note Generation through Ambient Listening, Large Language Model Fine-Tuning, and RAG

Retrieval-Augmented Generation (RAG) Explained, covering its working principles, components, benefits, applications, challenges, and future prospects.

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 Assistant for FMBench (foundation model benchmarking tool)

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.

A Retrieval-Augmented Generation (RAG) system that leverages Google's Agent Development Kit (ADK) and Qdrant vector database via MCP server.

Okos is a Telegram AI Assistant built with TypeScript, LangGraph, and multiple AI model providers. It maintains conversation context and provides summaries of interactions.