4 مستودعات
Tools for extracting insights from structured knowledge graphs via search commands.
Distinguishing note: Focuses on querying existing knowledge graphs rather than building them.
Explore 4 awesome GitHub repositories matching data & databases · Graph Query Interfaces. Refine with filters or upvote what's useful.
Understand-Anything is a codebase architecture visualization tool that transforms source code and documentation into interactive knowledge graphs. It maps files, functions, and classes into a node-edge model to visualize architectural dependencies and project structures. The project provides specialized workflows for impact analysis, tracing connectivity paths from code modifications to identify affected downstream components. It also enables technical onboarding through automated architecture tours and the conversion of technical documentation into navigable networks of interconnected ideas.
Provides interfaces for extracting insights and analyzing codebase organization via knowledge graph queries.
GraphRAG is a data processing pipeline and retrieval engine designed to transform unstructured text into interconnected knowledge graphs. By utilizing language models to extract entities and relationships, it builds structured representations of information that enable context-aware retrieval for downstream applications. The system distinguishes itself through hierarchical graph clustering and large-scale data synthesis, which organize massive document corpora into multi-level structures. This approach allows for both vector-based semantic searches and graph-based traversals, providing a comp
Extracts specific insights from knowledge graphs by executing search commands.
Memori is an AI agent memory middleware platform designed to provide persistent, context-aware recall for language models. It functions as a non-intrusive layer that intercepts outbound model requests to automatically capture interaction history and execution traces, ensuring that agents maintain continuity across sessions without requiring modifications to existing application logic. The platform distinguishes itself through a dual-model storage architecture that maintains information as both structured relational primitives for precise fact retrieval and rolling narrative summaries for situ
Accesses stored semantic relationships directly via standard database queries to support debugging, analytics, and data exploration.
Cayley is a graph database engine designed for storing and querying interconnected data using a quad-based data model. It functions as an RDF quad store, managing information through subjects, predicates, objects, and labels. The system features a modular graph store architecture with pluggable backends, allowing it to swap between in-memory storage and various external persistent databases. It includes a GraphQL-inspired API and a dedicated data visualizer for the interactive exploration of nodes and edges. Query capabilities cover bidirectional path traversal and multi-syntax execution usi
Provides a GraphQL-inspired interface to retrieve nodes, properties, and nested relationships from the graph.