Flexible GraphRAG v0.7.1 is out: Visual Langflow integration, LiteParse support, and Microsoft Graph delta query (SharePoint, OneDrive)

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner  LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from July 23, 2026 (original LinkedIn post)

Flexible GraphRAG v0.7.1 is out: Visual Langflow integration, LiteParse support, and Msft Graph delta query (SharePoint, OneDrive). v0.8.0, with optional CocoIndex support, is coming soon. Details in article:

Details

From my LinkedIn article (original article)

Flexible GraphRAG v0.7.1 released : Visual Langflow integration, added LiteParse support, and Microsoft Graph delta query (efficient incremental update for SharePoint, OneDrive). Also for v0.8.0, have optional initial support for CocoIndex coming soon.

Github: https://github.com/stevereiner/flexible-graphrag

1. Optional visual Langflow flows to customize the ingest pipeline and search flows used “under the covers” of the UI (OpenRAG like). Also have configurable “Flexible" Langflow components to use in other apps. Langflow+components can be used “standalone” running in a separate venv from the main Flexible GraphRAG backend venv, or with a new docker with the flexible components, available on https://hub.docker.com/u/integratedsemantics (along with the previous optional dockers for backend, react, vue, and angular frontends)

2. A Previous post mentioned that if Langflow mode is enabled, incremental updating will also flow thru the customizable pipeline. Now all 13 data sources will flow thru it and some fixes were made. App UI , MCP, and REST all will use the visual flows when the ENABLE_LANGFLOW_FLOWS is true.

3. Added support for the open source LiteParse from LlamaIndex in addition to previous support for Docling and LlamaParse (LiteParse can be configured to send to other parsers for a list of complexity reasons) LiteParse github https://github.com/run-llama/liteparse

4. Added support for Microsoft delta query for efficient incremental change updating for SharePoint and OneDrive data sources.

5. For v0.8.0 (not checked in) have an optional CocoIndex pipeline working inside the Flexible GraphRAG app. CocoIndex github https://github.com/cocoindex-io/cocoindex This pipeline supports mixing CocoIndex things and "Flexible LlamaIndex / LangChain things” from Flexible GraphRAG. Things = connectors (sources, targets), functions ( document processor supporting Docling, LlamaParse, and Liteparse, chunking / splitting, and KG extraction). These are separate from the Langflow “Flexible” components. With this pipeline, CocoIndex deals with incremental handling instead of the existing Flexible GraphRAG Python based incremental update system with Postgres for state management. Still can use it to keep track of multiple datasource_configs, setup in the app UI, and optional monitoring logging.

6. This CocoIndex pipeline app can be used outside of the Flexible GraphRAG app for custom mixed apps.

7. Thus Flexible GraphRAG things can be used : 13 data sources (9 auto syncing with Alfresco ActiveMQ, S3 SQS, Azure change feed, GCS pub/sub, MS Graph delta query, watchdog filesystem change detectors), DBs: 15 property graphs, 4 RDF stores, 10 vector stores, 3 search engines) in addition to CocoIndex "native" things. In the .env config, for each backend ( source, property graph , search, vector, chunker/spitter) in framework config section, you can setup to use llamaindex, langchain or cocoindex. RDF is langchain only, KG extraction is currently only llamaindex or langchain. What particular database to use is separately configured.

8. Screenshot shows Flexible GraphRAG running in Langflow pipeline mode, with an auto sync data source setup with SharePoint (using MS delta query), PDF file was parsed by LiteParse, with Qdrant vector, Elastic search, Neo4j property graph, and Graphwise Ontotext GraphDB RDF graph all getting initial sync, add, delete, modify changes. Flexible GraphRAG processing tab shows initial sync status, chat is being used to ask “Who works for Acme” and “How is Acme organized” using context in all 4 dbs from the ingestion of company-ontology-test.txt (Flexible GraphRAG was setup in ontology mode with 3 ttl turtle files)

Flexible GraphRAG now supports optional visual Langflow flows for ingest and search / AI query, plus configurable Flexible Langflow components

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner  LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from July 6, 2026 (original LinkedIn post)

The Flexible GraphRAG app now supports optional visual Langflow flows to customize the ingest pipeline and search / ai-query flows used “under the covers” of the UI (OpenRAG like). Also have configurable “Flexible” Langflow components to use in agentic apps or for RAG / GraphRAG. These include data source (13 sources ), document processor (Docling / LlamaParse), text splitter/chunking, KG extraction supporting ontologies for both pg and rdf dbs, vector (10 dbs), search (3 dbs), property graph (15 dbs). rdf graph (4 dbs), hybrid search, ai query / chat
Github: https://github.com/stevereiner/flexible-graphrag

Update: works with the incremental auto update sync

From my follow-up LinkedIn post from July 8, 2026 (original LinkedIn post)

I forgot to mention that the Flexible GraphRAG incremental auto update sync system works with the customizable visual ingestion pipeline flow (if ENABLE_LANGFLOW_FLOWS is configured). The flow is used for initial ingests, adds, and updates. The Langflow components are Python based and use the Flexible GraphRAG Python "framework“. Auto update sync with the Hyland Alfresco data source is tested and works with the ingest flow. These should work too: S3, Google Drive, OneDrive, SharePoint, Box, and Local Filesystem. For GCS and Azure Blob Storage, I have a fix coming soon. Postgres is used to manage the update system. Github: https://github.com/stevereiner/flexible-graphrag

Flexible GraphRAG documentation web site: UI Guide covering all 13 data source forms and all tabs

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner  LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from April 19, 2026 (original LinkedIn post)

The Flexible GraphRAG documentation website has a UI Guide covering all 13 data source forms (8 can auto sync) on the Sources tab, Processing tab, Hybrid Search / AI query tab, and AI Chat tab.
Data source forms: https://stevereiner.github.io/flexible-graphrag/UI-GUIDE/UI-TAB-SOURCES/
Has screenshots for the tabs with React, Angular, and Vue in dark and light themes
UI Guide: https://stevereiner.github.io/flexible-graphrag/UI-GUIDE/UI-SCREENSHOTS/
GitHub: https://github.com/stevereiner/flexible-graphrag

Flexible GraphRAG now has a Zensical documentation web site

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner  LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from April 17, 2026 (original LinkedIn post)

Flexible GraphRAG now has a zensical documentation web site https://stevereiner.github.io/flexible-graphrag/
Flexible GraphRAG can create a Knowledge Context from a combination of Alfresco (Hyland) , SharePoint , Box , S3, GCS, Azure Blob sources. Incremental update auto syncs multiple databases (search, property graph, rdf graph, and vector) used for hybrid search / ai query /ai chat , and agents.

Flexible GraphRAG GitHub repo:
https://github.com/stevereiner/flexible-graphrag

In 0.5.1, Flexible GraphRAG added LadybugDB support. Version 0.5.0 added RDF-based ontologies for both property graph dbs and RDF graph dbs (Graphwise, Ontotext GraphDB, Fuseki, Oxigraph), plus document ingestion with KG extraction, auto incremental change detection, and a search UI (hybrid search, AI query, AI chat) for RDF graph dbs in addition to previous property graph / vector / search db support.

Next version will expand flexible LangChain / LlamaIndex support: using everything in LlamaIndex, or LlamaIndex plus 6 additional LangChain new property graph databases, or everything in LangChain (graph, vector, search, llm).

x.com: https://x.com/stevereiner
integrated Semantics Blog: https://integratedsemantics.org/

Flexible GraphRAG now also supports embedded ArcadeDB in addition to remote ArcadeDB

Flexible GraphRAG on GitHub

X.com Steve Reiner @stevereiner  LinkedIn Steve Reiner LinkedIn Posts

Repost of my LinkedIn post from March 10, 2026 (original LinkedIn post)

Flexible GraphRAG now also supports ArcadeDB embedded in addition remote ArcadeDB. Both work with the optional incremental update auto sync from data sources. All supported databases (10 vector, 3 search, and 8 graph databases) now work with auto sync. Github https://github.com/stevereiner/flexible-graphrag. With a full hybrid setup (vector, search, graph) all get auto synced.
Finally have pypi built releases (0.4.0) of flexible-graphrag https://pypi.org/project/flexible-graphrag/ and flexible-graphrag-mcp https://pypi.org/project/flexible-graphrag-mcp/