GitNexus: The Zero-Server Code Intelligence Engine - GitNexus is a client-side knowledge graph creator that runs entirely in your browser. Drop in a GitHub repo or ZIP file, and get an interactive knowledge graph wit a built in Graph RAG Agent. Perfect for code exploration

Hybrid RAG system combining vector search, knowledge graph (LightRAG), and cross-encoder reranking — with Docling document parsing, visual intelligence (image/table captioning), agentic streaming chat, and inline citations. Powered by Gemini or local Ollama models.

An Open Source, Claude Code Like Tool, With RAG + Graph RAG + MCP Integration, and Supports Most LLMs (Incomplete But Functional & Usable)Autonomous LLM agent: ChromaDB semantic RAG + Neo4j knowledge-graph sync + MCP tool-call gateway.

GRACE (Graph-RAG Anchored Code Engineering): open Agent Skills for contract-driven AI code generation with semantic markup, knowledge graphs, and support for Claude Code, Codex CLI, and Kilo Code.

Healthcare RAG agent with Neo4j knowledge graphs - Query medical data using LangChain, FastAPI & Streamlit

12-layer memory architecture for OpenClaw agents — knowledge graph (3K+ facts), semantic search (multilingual, 7ms GPU), continuity + stability + graph-memory plugins, activation/decay system, domain RAG. Agents reconstruct themselves from files on every boot.

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

AMG-RAG (Agentic Medical Graph-RAG) is a comprehensive framework that automates the construction and continuous updating of Medical Knowledge Graphs (MKGs), integrates reasoning, and retrieves current external evidence for medical Question Answering (QA).

GenAI Series - RAG, Fine tuning, Agents, Knowledge Graph

A RAG-based chatbot withmulti-tenant project support, where specialized agents collaborate over knowledge graphs to deliver accurate, context-aware answers.

도서 Building AI Agents with LLMs, RAG, and Knowledge Graphs, First Edition의 한글판의 깃허브 레포지토리입니다.

MCP server combining Qdrant vector search, Neo4j knowledge graphs, and Crawl4AI web intelligence with agentic RAG capabilities. FastMCP 2.0 architecture with enterprise security, monitoring, and Kubernetes deployment. AI/ML engineering powerhouse.

A high-performance agentic RAG system combining Graphiti's temporal knowledge graphs with LangGraph's multi-agent orchestration to achieve 100x faster retrieval speeds than traditional RAG through intelligent graph-based indexing and parallel agent processing.

GitNexus: The Zero-Server Code Intelligence Engine - GitNexus is a client-side knowledge graph creator that runs entirely in your browser. Drop in a GitHub repo or ZIP file, and get an interactive knowledge graph wit a built in Graph RAG Agent. Perfect for code exploration

Elixir RAG library with multi-LLM routing (Gemini, Claude, OpenAI, Ollama), GraphRAG, knowledge graphs, modular retrievers/rerankers, composable pipelines, pgvector integration, advanced chunking, and tool-using agents. Fork of bitcrowd/rag.

KG-RAG: Enhancing GUI Agent Decision-Making via Knowledge Graph-Driven Retrieval-Augmented Generation, EMNLP 2025

A comprehensive collection of RAG (Retrieval Augmented Generation) implementations 📚✨, from foundational concepts to advanced agentic 🤖 and knowledge graph 🌐 RAGs

Dynamic Intelligence Graph (DIG) MCP server for AI coding agents. Persistent code knowledge graph, a code RAG improvement, with hybrid Graph + Vector + BM25 retrieval, agent memory, multi-agent coordination, and impact-scoped test selection. Works with Claude Code, VS Code Copilot, and Cursor.

NexusAI: Zero-Server Code Intelligence — 100% in Your Browser Drop any GitHub repo or ZIP → instantly get an interactive knowledge graph + built-in Graph RAG agent. Explore dependencies, call chains, and architecture — privately, offline, no server ever needed. Perfect for deep code understanding.

A local Neuro-Symbolic RAG agent inspired by Apple's CLaRa. Built with the "2026 Stack" (DSPy, LangGraph, Ollama), it features Hybrid Memory (Vector + Knowledge Graph), HyDE retrieval, and self-correcting web search fallback.

No description available

Hybrid RAG system combining vector search with knowledge graphs, built on Pydantic AI agents, FastAPI, PostgreSQL+pgvector, Neo4j+Graphiti

Movie Graph RAG is an **agentic retrieval-augmented generation (RAG) system** that fuses a **knowledge graph** with **vector similarity search** to enable reasoning-driven queries in the movie domain.

Comparing structured (Knowledge Graph) vs unstructured (RAG) approaches to financial risk intelligence in multi-agent crisis simulations

A complete Agentic RAG system using LangGraph, a Knowledge Graph, multi-hop retrieval, and local LLMs (Ollama). Includes ingestion, graph builder, custom retriever, tools, and full CLI agent workflow.

The Self-Healing Knowledge Graph for RAG. An autonomous agent that scrapes websites, extracts structured knowledge using LLMs, and auto-updates stale data in Neo4j. Built with Python, AsyncIO, and Pydantic.

A Neuro-Symbolic RAG Agent combining a custom C++ search engine (Trie/Inverted Index) with Gemini API for automated fact verification and Knowledge Graph construction.

GraphRAG, Outperforms traditional RAG ( Retrieval-Augmented Generation ) for Query Focused Summarization. Opensource research of Knowledge Graph to improving the accuracy of data discovery, solving RAG pain points, solving Black-box hallucination, and to enhance LLMs. Knowledge Graph to GenAI. PDF AI Agent/Chatbot with Python, Neo4j and LangChain

A living journey into Climate AI Engineering — from prompt engineering to agentic systems, RAG, knowledge graphs, and model customization. Based on courses from Google, Anthropic, Stanford, MIT, Columbia, CalArts, and DeepLearning.AI.

Evidence-grounded, multi-agent research assistant that performs RAG over scientific papers, extracts structured claims, builds a Neo4j knowledge graph, and answers questions with verifiable citations and stateful session memory.