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Easily use and train state of the art late-interaction retrieval methods (ColBERT) in any RAG pipeline. Designed for modularity and ease-of-use, backed by research.
Open-source tool to visualise your RAG 🔮
The open-source visual AI programming environment and TypeScript library
ExtractThinker is a Document Intelligence library for LLMs, offering ORM-style interaction for flexible and powerful document workflows.
The Rule-based Retrieval package is a Python package that enables you to create and manage Retrieval Augmented Generation (RAG) applications with advanced filtering capabilities. It seamlessly inte…
The all-in-one Desktop & Docker AI application with built-in RAG, AI agents, No-code agent builder, MCP compatibility, and more.
SoTA production-ready AI retrieval system. Agentic Retrieval-Augmented Generation (RAG) with a RESTful API.
An application for running LLMs locally on your device, with your documents, facilitating detailed citations in generated responses.
A modular graph-based Retrieval-Augmented Generation (RAG) system
Multi-lingual large voice generation model, providing inference, training and deployment full-stack ability.
RAG that intelligently adapts to your use case, data, and queries
pingcap/autoflow is a Graph RAG based and conversational knowledge base tool built with TiDB Serverless Vector Storage. Demo: https://tidb.ai
This repository contains various advanced techniques for Retrieval-Augmented Generation (RAG) systems.
Production-ready platform for agentic workflow development.
Integrating knowledge graphs (KG) with large language models (LLM)
This repository provides an advanced Retrieval-Augmented Generation (RAG) solution for complex question answering. It uses sophisticated graph based algorithm to handle the tasks.
Understand and code every important component of RAG architecture
"DeepTutor: AI-Powered Personalized Learning Assistant"
A curated catalogue of awesome agentic AI patterns