Graphify-Labs/graphify
Graphify turns any codebase, including documentation and other files, into a queryable knowledge graph using local AST parsing, without relying on vector stores or embeddings.
Awesome AI Agents › Knowledge Graph Orchestration
TencentCloudADP/youtu-graphrag
Youtu-GraphRAG from Tencent Cloud ADP is a Python framework that unifies graph construction and retrieval under a single graph schema, presented in a paper accepted at ICLR 2026. Construction is schema guided: a seed schema defines targeted entity types, relations and attribute types that bound the automatic extraction agents, and the schema expands continuously so unseen domains can be covered with little manual work. The resulting hierarchical knowledge tree has four levels, holding entity attributes, relation triples, keyword indexes and hierarchical communities. Communities are found by an algorithm that fuses structural topology with subgraph semantics, which the authors report as better suited than Leiden or Louvain for this structure, and communities receive LLM-generated summaries that add a higher level of abstraction; the tree supports both top-down filtering and bottom-up reasoning. Retrieval is agentic: a decomposer reads the same schema to split a complex question into tractable sub-queries that run in parallel, and iterative reflection through IRCoT builds the answer step by step with visible reasoning traces. All components are configured from one YAML file with runtime parameter overrides and multi-environment support. Generated four-level graphs are written under an output directory and can be imported into Neo4j for visualisation of reasoning paths. The project also publishes AnonyRAG, an anonymised benchmark dataset on Hugging Face in Chinese and English designed to avoid knowledge leakage from model pretraining and to measure real retrieval performance. Across six benchmarks including GraphRAG-Bench, HotpotQA and MuSiQue the authors report 33.6 percent lower token cost and 16.62 percent higher accuracy than the baselines they compare against. It targets multi-hop reasoning, summarisation and knowledge-intensive questions over large structured, private or domain-specific corpora, and an enterprise edition runs on Tencent Cloud.
https://github.com/TencentCloudADP/youtu-graphrag
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