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RAG

flexible-graphrag

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Python, LlamaIndex, LangChain, 15 Property Graph, 4 RDF , 10 Vector, OpenSearch, Elasticsearch, Alfresco, Nuxeo DBs. 14 data sources (10 auto-sync), KG auto-building, Ontologies, LLMs, Docling, LlamaParse, LiteParse, GraphRAG, RAG, Hybrid Search, AI Chat. TypeScript React, Vue, Angular frontends, REST, MCP Server. Options: Langflow, CocoIndex

★ 18836 forksPythonApache-2.0stevereiner

A Python GraphRAG and RAG platform that ingests documents from enterprise sources, builds knowledge graphs, and supports hybrid search across vector, property-graph, RDF, and full-text stores. Includes REST and MCP APIs, AI chat, and optional LlamaIndex, LangChain, Langflow, or CocoIndex pipelines.

Use Cases

Build knowledge graphs from documentsCreate ontology-guided GraphRAG applicationsSearch across vector, full-text, graph, and RDF storesKeep knowledge bases synchronized with enterprise data sourcesProvide AI chat over documents and connected dataExpose retrieval and query capabilities through REST and MCP

Built With

Language
Python
Frameworks
LlamaIndex · LangChain · Langflow · CocoIndex · FastAPI · FastMCP · React · Vue · Angular

Tags

GraphRAG · RAG · knowledge graphs · hybrid search · RDF · ontologies · document ingestion · incremental sync · MCP server · AI chat · vector search · enterprise data