Memory control plane for AI Agents in 6 lines of code

Neo4j graph construction from unstructured data using LLMs

A Graph RAG System for Evidenced-based Medical Information Retrieval [ACL 2025]

Logic Language for LLMs 🌱🐋🌍 Build Neuro-Symbolic AI for Learning and Reasoning

Nornicdb is a distributed low-latency, Graph+Vector, Temporal MVCC with all sub-ms HNSW search, graph traversal, and writes. Using Neo4j Bolt/Cypher and qdrant's gRPC means you can switch with no changes. Then, adding intelligent features like schemas, managed embeddings, LLM reranking+inferrence, GPU accel, Auto-TLP, Memory Decay, and MCP server.

《动手学SpringAI》包含SSE流/Agent智能体/知识图谱RAG/FunctionCall/历史消息/图片生成/图片理解/Embedding/VectorDatabase/RAG

A SQLite extension that adds graph database capabilities with Cypher query language support and built-in graph algorithms.

"Hyper-RAG: Combating LLM Hallucinations using Hypergraph-Driven Retrieval-Augmented Generation" by Yifan Feng, Hao Hu, Shihui Ying, Xingliang Hou, Shiquan Liu, Mingyuan Yang, Junchang Li, Shaoyi Du, Nanning Zheng, Han Hu, and Yue Gao.

VeritasGraph — open-source Knowledge Graph & GraphRAG framework on GitHub. Build multi-hop reasoning, ontology-aware retrieval, and verifiable attribution over your own data. Nodes, edges, RDF, linked-data — runs locally or in the cloud.

Graph RAG with pure vector search, achieving SOTA performance in multi-hop reasoning scenarios.

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.

[WWW 2025] Paths-over-Graph: Knowledge Graph Empowered Large Language Model Reasoning

A modular Python framework implementing the Model Context Protocol (MCP). It features a standardized client-server architecture over StdIO, integrating LLMs with external tools, real-time weather data fetching, and an advanced RAG (Retrieval-Augmented Generation) system.

Xmem is a India's First multi-modal, multi-agentic long‑term memory layer for AI agents.

Active WIP for experimenting with GraphRAG and Knowledge Graphs

Demo of knowledge graph creation and Graph RAG with BAML and Kuzu

Ask questions across your Markdown notes using a fully local Graph RAG engine. Built for Obsidian vaults, works with any folder of Markdown files. Extracts entity-relation triples from wikilinks & YAML frontmatter, retrieves answers via hybrid search (vector + BM25 + temporal). Multilingual. No cloud. Runs on Ollama.

构建一个医疗知识图谱并基于此实现 RAG，并以此实现医学试题的生成

Graph-vector database that queried 1 billion edges for $2.50. Rust, OpenCypher, vector search, 14 graph algorithms. 74M nodes / 1B edges on a single machine.

A minimal implementation of GraphRAG, designed to quickly prototype whether you're able to get good sense-making out of a large dataset with creation of a knowledge graph.