Category: OneDrive

Big News: Flexible GraphRAG now supports Incremental Update Auto Sync from Data Sources

Flexible GraphRAG on GitHub

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

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

Flexible GraphRAG incremental update auto sync: Postgres document state, Sources and Processing tabs, and the Neo4j knowledge graph

Big News: Flexible GraphRAG now supports Incremental Update Auto Sync from Data Sources
Huge New Feature: Flexible GraphRAG check-in: Added Incremental Update Auto Sync from 9 data sources to all supported vector, search, and graph databases. Added Postgres state management.
🌟 Github: https://github.com/stevereiner/flexible-graphrag

• All auto syncing data sources working: S3 (SQS events), Hyland Alfresco (ActiveMQ events), Azure Blob, GCS (Pub/Sub), Google Drive, Box, OneDrive, SharePoint, Filesystem (watchdog).

• All 10 vector databases working with this (Qdrant, LanceDB, Elastic, OpenSearch Project, Chroma, Milvus, created by Zilliz, Weaviate, Pinecone, PostgreSQL pgvector, Neo4j)

• All 3 full text search engines working with this (Elasticsearch, OpenSearch, built-in LlamaIndex BM25)

• Graph databases working with this: Neo4j, FalkorDB, ArcadeDB (fix to delete coming), MemGraph. More testing needed with Kuzu, NebulaGraph, Amazon Neptunes.

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source Python platform, uses LlamaIndex , supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources (9 auto-sync) Also supports knowledge graph auto-building, schemas, 9 LlamaIndex LLMs, Docling or LlamaParse doc processing, GraphRAG mode, RAG only mode, Hybrid search, AI query, AI chat. Has React, Vue, and Angular TypeScript frontends, a FastAPI backend, and a REST API. Also has a FastMCP MCP server. Has a convenient docker compose that can include any of the databases (Vector, Graph, Search, Alfresco) and Dashboards / Consoles.
Blog: https://integratedsemantics.org/
X.com: https://x.com/stevereiner

Flexible GraphRAG: Observability support, SharePoint and OneDrive data sources working, 9 LLM providers, “Skip graph” checkbox

Flexible GraphRAG on GitHub

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

Repost of my LinkedIn post from January 5, 2026 (original LinkedIn post)

Flexible GraphRAG with Neo4j and Grafana observability dashboards

Shown: updated Flexible GraphRAG with Neo4j, Observability with Grafana Labs , GitHub 🌟 https://github.com/stevereiner/flexible-graphrag , updates:
1. Observability support added with OpenTelemetry, Prometheus, Grafana, Jaeger, and OpenLIT
2. SharePoint and OneDrive data sources fixed and now working (13 data sources: filesystem, Alfresco, SharePoint, Box, CMIS, S3, GCS, Azure Blob, OneDrive, Google Drive, web sources)
3. Added LLM Providers (now 9 total) : OpenAI, Azure OpenAI, Google Gemini, Vertex AI, Anthropic Claude, Amazon Bedrock, Ollama, Grog, Fireworks AI, and Ollama. Uses LlamaIndex.
4. Embedding providers can be used independently..
5. Like KG Spaces (Github 🌟 https://github.com/stevereiner/kg-spaces-aca) for Hyland Alfresco ACA, added a “Skip graph” checkbox for per ingest control. Skip graph allows on each ingest to have fast RAG ingest speed (vector+full-text) or a full GraphRAG ingest (vector+full-text+graph). Hybrid search and AI query / AI chat works with all that is available from mixed kinds of ingests.
6. Flexible GraphRAG MCP server: added support for all 13 data sources, per ingest skip_graph option , data source config options, full REST API parity.
7. Backend REST API (also supports all 13 data sources), added support for per ingest skip graph, also for KG Spaces: multi-file ingest NodeDetails list with nodeids, get by path for regular Flexible GraphRAG with updated Python Alfresco API package (Github 🌟https://github.com/stevereiner/python-alfresco-api)
8. Added Python backend pyproject.toml, llama-core (no llama-index) and integrations only, to avoid package version issues.

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source Python platform, uses LlamaIndex , supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources, Also supports knowledge graph auto-building, schemas, 9 LlamaIndex LLMs, Docling or LlamaParse doc processing, GraphRAG mode, RAG only mode, Hybrid search, AI query, AI chat. Has React, Vue, and Angular frontends, and a FastAPI backend. Also has a FastMCP MCP server. Has a convenient docker compose that can include any of the databases (Vector, Graph, Search, Alfresco) and Dashboards / Consoles.

X.com Post on updates
https://x.com/stevereiner/status/2007534742908846552
Integrated Semantics Blog:
https://integratedsemantics.org/