Awesome GitHub RepositoriesKnowledge Graph Retrieval

Embedchain is an LLM memory management framework and RAG orchestration engine designed to provide AI agents with a persistent storage layer. It functions as a long-term memory pipeline that extracts facts from unstructured interactions and stores them as permanent knowledge base entries to retain user preferences and interaction history across sessions. The system employs a hybrid vector database interface that combines semantic embeddings with traditional keyword search. It utilizes an entity-linking knowledge graph to connect related information points and applies temporal ranking to distin

LightRAG is a graph-based retrieval framework designed to build retrieval-augmented generation pipelines. It structures unstructured text into knowledge graphs, enabling multi-hop reasoning and complex query synthesis across large document collections. By integrating dense vector embeddings with structured knowledge graphs, the system facilitates both similarity-based and relationship-aware information retrieval. The framework distinguishes itself through a dual-level retrieval strategy that combines low-level keyword matching with high-level semantic graph traversal to capture both specific

Cognee is an agentic memory management platform designed to provide autonomous agents with long-term semantic recall and structured knowledge. It functions as a framework for building persistent memory systems that connect large language models to graph-based knowledge and vector storage, enabling agents to maintain context across complex tasks and multiple sessions. The platform distinguishes itself through a hybrid approach that combines semantic similarity search with structural graph traversal, allowing for context-aware information retrieval. It features a modular architecture that orche

Neo4j is a native graph database management system designed to store and query highly connected data using a property-graph model. It provides an ACID-compliant transaction engine that ensures data integrity, supported by a distributed cluster architecture that maintains causal consistency across nodes. Users interact with the system through a declarative query language, which allows for complex pattern matching and path traversal without requiring manual traversal logic. The platform distinguishes itself through its hybrid approach to data retrieval, combining traditional graph-based queries

Planning with files is an enterprise knowledge graph platform designed to transform unstructured organizational data into a searchable, interconnected network. By utilizing a graph-based retrieval-augmented generation engine, the system grounds language model outputs in verified internal data, ensuring that responses are explainable, traceable, and free from hallucinations. The platform distinguishes itself through a focus on data sovereignty and secure, private infrastructure deployment. It enables organizations to maintain full control over sensitive information by processing data locally o

This project is a multi-model database system designed to store and manage information as documents, graphs, and key-value pairs within a single engine. It functions as a graph database and knowledge graph platform, providing the infrastructure to build, query, and visualize structured data models. By integrating vector search capabilities, the system serves as a vector database that supports retrieval-augmented generation for artificial intelligence applications. The platform distinguishes itself through a unified query language that allows users to perform document lookups, graph traversals

jcode ist ein Framework für die Entwicklung autonomer KI-Coding-Agenten, die Softwareentwicklungsaufgaben automatisieren. Es fungiert als Agenten-Orchestrator, Tool-Laufzeitumgebung und semantische Speicher-Engine und ermöglicht die Erstellung von Agenten, die Code modifizieren, Tests ausführen und ihre eigene Funktionalität iterieren können. Das Projekt zeichnet sich durch die Verwendung von rekursivem Agenten-Swarming aus, bei dem eine Hierarchie zusammenarbeitender Agenten untergeordnete Agenten hervorbringen kann, um komplexe Aufgaben zu zerlegen. Es implementiert ein semantisches Speichersystem, das vektorbasierte Abfrage mit graphenbasierter Beziehungszuordnung kombiniert, um den Kontext über Sitzungen hinweg zu wahren. Um Risiken zu verwalten, verwendet das System eine gestaffelte Aktions-Governance, die für sensible Operationen eine menschliche Genehmigung erfordert und Agentenaktivitäten innerhalb separater Git-Worktrees isoliert. Das Framework enthält ein umfassendes Browser-Automatisierungs-Toolkit für die Interaktion mit Webseiten, das Extrahieren von DOM-Snapshots und das Erfassen von Screenshots. Es implementiert zudem das Model Context Protocol zur Integration externer Tools und Daten und unterstützt binäres Hot-Reloading, um den Server zu aktualisieren, ohne aktive Netzwerkverbindungen zu verlieren. Das System bietet eine Befehlszeilenschnittstelle zur Verwaltung von Agenten-Speichern und enthält Audit-Tools, um den Fortschritt von Plänen zu verfolgen und die Topologie des Agenten-Schwarms zu visualisieren.

QASystemOnMedicalKG is a medical knowledge graph question answering system designed to retrieve disease-centered information from a structured data store. It functions as both a constructor for building medical knowledge graphs and a retrieval system that extracts answers regarding symptoms, causes, and treatments. The system employs a pipeline that converts unstructured medical web data into a graph database using dictionary-based entity segmentation. It utilizes query-based intent classification to parse natural language inputs and maps these queries to specific nodes and edges within the g

Potpie is an LLM codebase analysis platform and multi-agent orchestration framework designed to act as an AI software engineer. It parses repositories into a structured code knowledge graph, enabling AI agents to perform multi-hop reasoning, dependency tracing, and grounded technical analysis across large codebases. The system distinguishes itself through a spec-driven development framework where agents generate detailed technical specifications and architecture plans before implementing multi-file code changes. It utilizes a durable execution engine to coordinate specialized AI personas for

Memgraph is an in-memory, distributed graph database designed for high-performance labeled property graph management. It utilizes a Cypher query engine for declarative data retrieval and manipulation, providing a scalable knowledge graph backend that integrates vector search and graph traversals. The system distinguishes itself as a real-time graph analytics platform, employing native C++ and CUDA implementations to execute complex network analysis and dynamic community detection on streaming data. It provides specialized support for AI integration, including GraphRAG capabilities, the constr

Cartography ist ein graphbasiertes Framework zur Infrastrukturvisualisierung und Sicherheitsanalyse. Es erfasst Daten von verschiedenen Cloud-, Identitäts- und Software-as-a-Service-Anbietern, um komplexe Beziehungen zwischen Ressourcen, Benutzern und Sicherheitsergebnissen in einer zentralen Graphdatenbank zu modellieren. Durch die Abbildung dieser Abhängigkeiten ermöglicht die Plattform Unternehmen, Transparenz über ihre Umgebung zu gewinnen und potenzielle Sicherheitsrisiken durch Graph-Traversal-Abfragen zu identifizieren. Die Plattform zeichnet sich durch ihre ontologiebasierte Normalisierung und plattformübergreifende Entitätskorrelation aus, die heterogene Daten aus mehreren Quellen in ein einheitliches, konsistentes Modell überführen. Sie verwendet modulare Ingestions-Pipelines und schema-basierte Filterung, um diesen Graphen zu pflegen und sicherzustellen, dass Infrastrukturdaten durch automatisiertes, zustandsbasiertes Bereinigen veralteter Knoten korrekt bleiben. Dieser Ansatz ermöglicht die Entdeckung komplexer Angriffspfade und Sicherheitsfehlkonfigurationen, die sich über disparate Cloud-, Geräte- und Identitätsmanagementsysteme erstrecken. Über die Kernmodellierung hinaus bietet das System umfangreiche Funktionen für Asset-Inventarisierung, Identitäts-Governance und Software-Supply-Chain-Analyse. Es unterstützt eine breite Palette von Integrationen, einschließlich Cloud-nativer Compute- und Netzwerkressourcen, Endpunkt-Management-Telemetrie und Metadaten des Entwicklungslebenszyklus. Benutzer können die Funktionalität der Plattform erweitern, indem sie benutzerdefinierte Sicherheitsregeln definieren, spezialisierte Datenanalyse-Jobs hinzufügen oder neue Intelligenzquellen über das modulare Framework integrieren. Das Projekt ist in Python implementiert und bietet Dokumentation für die Konfiguration von Ingestionsmodulen und die Definition benutzerdefinierter Graph-Abfragen.

FalkorDB is a high-performance graph database management system and vector graph database. It serves as a knowledge graph construction tool and a GraphRAG knowledge store, integrating structured property graphs with vector search to provide grounded context for large language models. The engine is designed as a multi-tenant graph engine, capable of hosting thousands of isolated datasets within a single instance. The system distinguishes itself by using linear algebra for query execution, treating relationship tensors as matrix multiplications to achieve low-latency multi-hop traversals. It ut

Memary is a memory-augmented agent framework that stores and retrieves contextual information from a knowledge graph to personalize responses and maintain long-term memory across interactions. It automatically captures all agent interactions and stores them as structured memories without requiring explicit instrumentation, then injects top-ranked user entities and themes into the active context window to tailor agent responses dynamically. The framework distinguishes itself through a multi-retriever memory search that combines COLBERT reranking with recursive graph queries across databases, e