Flexible GraphRAG 0.6.3 adds open-source AI context tools
Flexible GraphRAG 0.6.3 is an open-source platform for turning documents and connected data into searchable context for AI systems. It can process documents with Docling or LlamaParse, build automatically, and organize information with ontologies and schemas. It supports many providers, GraphRAG, RAG, vector search, , property graph search, and RDF/SPARQL search.
The backend uses Python, with LlamaIndex and LangChain available as peer frameworks; LlamaIndex is the default, and LangChain can be chosen for specific pipeline stages through environment settings. It includes a FastAPI REST API, TypeScript frontends for Angular, React, and Vue, and an MCP server. The stack connects to 13 data sources, with incremental auto-sync for 9 of them.
It also supports 15 property , 4 RDF triple stores, 10 , OpenSearch, Elasticsearch, BM25 search, and Alfresco. Docker Compose files can turn on database services and dashboards.
Key points
- It is an Apache 2.0 open-source platform for AI context, search, and chat.
- It combines GraphRAG, RAG, vector search, , property graph search, and RDF/SPARQL search.
- LlamaIndex is the default framework, while LangChain can be selected for specific stages.
- It includes a REST API, Angular, React, and Vue frontends, plus an MCP server.
- It supports many data sources, , RDF stores, , and search engines.