An LLM-powered knowledge curation system that researches a topic and generates a full-length report with citations.
10 Lessons to Get Started Building AI Agents
Open Source Deep Research Alternative to Reason and Search on Private Data. Written in Python.
Everything you need to know to build your own RAG application
Agentic-RAG explores advanced Retrieval-Augmented Generation systems enhanced with AI LLM agents.
YT Navigator: AI-powered YouTube content explorer that lets you search and chat with channel videos using AI agents. Extract insights from hours of content in seconds with semantic search and precise timestamps.
The Autonomous Knowledge Operations Platform turning AI agents into continuous and reliable operations. Deploy automated RAG pipelines (KG+VectorDB), unified access to any LLM, and manage it all with enterprise-grade infrastructure and observability.
Connect to your customer data using any LLM and gain actionable insights. IdentityRAG creates a single comprehensive customer 360 view (golden record) by unifying, consolidating, disambiguating and deduplicating data across multiple sources through identity resolution.
A python library for creating AI assistants with Vectara, using Agentic RAG
🔥🔥🔥 Simple way to create composable AI agents
Developing powerful AI assistants and agents using Genesis and Agentic-RAG.
Repositorio-Tutorial para desarrollo de chatbots, aplicaciones con LLMs y Agentes IA
Comprehensive resources on Generative AI, including a detailed Codebase and tutorials
A clean and extensible agentic RAG system with modular implementation.
RAGLight is a lightweight and modular Python library for implementing Retrieval-Augmented Generation (RAG), Agentic RAG and RAT (Retrieval augmented thinking)..
Agents and RAG workflows with little to no code
Agentic RAG to help you build a startup🚀
Interactive LLM Chatbot that constructs direct and transitive software dependencies as a knowledge graph and answers user's questions leveraging RAG and critic-agent approach
This repository provides the building blocks for integrating LangChain, LangGraph, and the Tilores entity resolution system.
It shows how to realize agentic RAG.
Add a description, image, and links to the agentic-rag topic page so that developers can more easily learn about it.
To associate your repository with the agentic-rag topic, visit your repo's landing page and select "manage topics."