Showing 1-17 of 17 projects
RAGFlow is an open-source RAG engine with agent capabilities for LLM context layering
GraphRAG is a modular system for enhancing LLM outputs using knowledge graphs from unstructured text.
LightRAG is a fast and simple Retrieval-Augmented Generation (RAG) framework for efficient knowledge retrieval and generation.
An open-source Python library that provides a simple, efficient way to add memory and context to AI agents.
Builds a Neo4j graph from unstructured data using LLMs
An intelligent and adaptable RAG (Retrieval Augmented Generation) library for AI-powered applications.
A simple, easy-to-hack implementation of GraphRAG, a tool for building AI-powered applications.
A fast, open-source graph database built using GraphBLAS for use in large-scale knowledge graph applications.
A conversational knowledge base tool built with TiDB Serverless Vector Storage for AI-powered workflows.
One-click deploy of a Knowledge Graph powered RAG (GraphRAG) in Azure for vibe coders.
A comprehensive guide and resources for developing AI agents and working with large language models (LLMs).
An integrated solution for building and evaluating knowledge graphs using AI tools like GraphRAG and LightRAG.
A Java-based framework for building AI-powered productivity tools, including chatbots, drawing, knowledge management, and more.
A SQL-driven RAG engine that automatically builds a knowledge graph during querying, enabling knowledge-enhanced applications.
Local support for Microsoft's graphrag using ollama (llama3, mistral, gemma2 phi3) - LLM & Embedding extraction
A Python library that boosts cost efficiency, inference accuracy, and cross-domain adaptability for complex QA systems.
A production-ready GraphRAG platform with multi-modal indexing, AI agents, and scalable Kubernetes deployment.
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