LadybugDB – Open Source Integrated AI and Semantic Tech

A redone KG Spaces (Flexible GraphRAG) for the Alfresco Content App (ACA) 8.0.0 is now available

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

Repost of my LinkedIn post from October 3, 2026 (original LinkedIn post)

A redone KG Spaces (Flexible GraphRAG) for the Alfresco Content App (ACA) 8.0.0 is now available.
kg-spaces-aca Github: https://github.com/stevereiner/kg-spaces-aca

Knowledge graphs auto-generated from your documents, alongside vector and fulltext indexes, provide the context for hybrid search, AI query and AI chat. It works over Alfresco content and other data sources, right inside ACA.

AI context DBs (choose 0 or 1 of each kind): 15 Property Graph (including Neo4j, ArcadeDB, FalkorDB, LadybugDB), 4 RDF, 10 Vector, and OpenSearch or Elasticsearch. Data sources: use any of 14 together, 10 with auto sync.

Highlights:
• Built as a separate ACA extension under the Apache 2.0 license
• Multi-select any mix of Alfresco files and folders from ACA’s regular file list views
• New data sources tab (labeled “Other Sources”) for choosing any other data source Flexible GraphRAG supports
• AI context can stay up to date through auto change sync from Alfresco, Nuxeo, SharePoint, Box, Amazon S3, Azure Blob Storage, Google Cloud Storage, Google Drive and OneDrive. File Upload, CMIS, Web Pages, Wikipedia and YouTube can be ingested without auto sync.
• Shares the Flexible GraphRAG Angular UI through a public npm package
• Can build a Docker image with ACA + kg-spaces-aca

The backend is Flexible GraphRAG v0.8.2+ (flexible-graphrag GitHub: https://github.com/stevereiner/flexible-graphrag), an open source AI context platform. It includes:
• Document processing with Docling, LlamaParse or LiteParse
• Knowledge graph auto-building, ontologies and schemas
• Many LLM providers
• GraphRAG and RAG
• Hybrid search (fulltext, vector, property graph, RDF/SPARQL)
• AI query and AI chat

Coming next: optional support for Hyland OpenArch (Hyland Open AI Ready Content Hub) in both kg-spaces-aca and the Flexible GraphRAG backend.

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 v0.5.1 now supports LadybugDB, hybrid_system modularized

Flexible GraphRAG on GitHub

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

Repost of my LinkedIn post from April 8, 2026 (original LinkedIn post)

Flexible GraphRAG v0.5.1 now supports LadybugDB and hybrid_system was modularized. In v0.5.0 , support for RDF-based ontologies for both property graph databases and RDF graph databases (Graphwise Ontotext GraphDB, Fuseki, and Oxigraph) was added. Also, document ingestion with KG extraction, auto incremental data source change detection, and search UI (hybrid search, AI query, and AI chat) are all supported with both database types. For RDF search, install with the additional LangChain option. Next version will be able to use everything in LlamaIndex, or LlamaIndex with 6 additional LangChain property graph databases, or everything in LangChain (graph,vector,search).
Note: until GitHub support fixes an automated flag on my account, you need to login to GitHub to see my repos:
flexible-graphrag: https://github.com/stevereiner/flexible-graphrag
llama-index-ladybug: https://github.com/stevereiner/llama-index-ladybug

Flexible GraphRAG or RAG is flexing to the max: 8 Graph databases, 10 Vector databases, 3 search engines working (can docker compose all including dashboards), 13 data sources

Flexible GraphRAG on GitHub

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

Flexible GraphRAG or Flexible RAG, an Apache 2.0 open source python platform, is now flexing to the max using LlamaIndex, in terms of supporting more databases and data sources: supports 8 graph databases, 10 vector databases, 3 search engines, and 13 data sources,. Also supports knowledge graph auto-building, schemas, LlamaIndex LLMs, Docling doc processing (LlamaParse coming soon), GraphRAG mode, RAG only mode, Hybrid search, and AI query / chat. Has React, Vue, and Angular frontends, and a FastAPI backend. React, Vue, Angular, Backend now work on Windows, Mac, Linux (standalone or in docker). 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.

(Flexible GraphRAG AI chat shown with Hyland products web page(s) used with web pages data source to auto-generated a Neo4j graph).

Convenient docker compose: you can choose to include from all supported 10 vector and 8 graph databases, Elasticsearch, OpenSearch, and Hyland Alfresco Community. Include in the docker-compose.yaml by just removing the # comment in front of their includes. Dashboards / Consoles for these databases, as much as possible are also included in the docker compose choices (either in the yaml file for the database or for some a separate yaml file include).

You can run the docker with the databases with the backend and frontends (React, Angular, Vue) running stand alone in separate terminal windows. In addition to running the databases in docker, you can include the backend and frontends in the dock compose by including the app-stack.yaml and proxy.yaml includes. Now have no config duplication for standalone backend+frontends vs full docker mode: previously had to repeat all config in app-stack.yaml now use env_file: include standalone backend .env and overrides with include of docker.env (for configs that need host.docker.internal)

All 8 Graph database working: Neo4j, ArcadeDB, FalkorDB, archived Kuzu (LadybugDB fork todo), NebulaGraph, Memgraph, Amazon Neptune, Amazon Neptune Analytics

All 10 Vector databases working: Qdrant, Elasticsearch vector, OpenSearch vector, Neo4j vector, Milvus, Weaviate, Chroma (both http, embedded), Pinecone, PostgreSQL + pgvector, LanceDB

All 3 Search engines working: Elasticsearch, OpenSearch, LlamaIndex built-in BM25

New Data Sources: using LlamaIndex readers: 1. working ones that don’t use document processing: Web Pages, Wikipedia, Youtube, 2. working using document processing: S3, 3. ones using document processing still to test: Google Drive, Microsoft OneDrive, Azure Blob, GCS, Box, SharePoint.

Support for Docling document processing is currently available. Being able configure to use LlamaParse coming soon.

Original data sources with document processing that don’t use LlamaIndex readers: filesystem, Alfresco, CMIS. Hyland Alfresco Community can be included in the docker compose by taking the “#” comment off the beginning of its include.

LLMs: LlamaIndex LLMs (LlamaIndex has support for very many), Flexible GraphRAG currently has config for 1. tested, working: OpenAI, Ollama, 2. untested: Anthropic Claude, Google Gemini, Azure OpenAI.

Previous Flexible GraphRAG posts:

See Flexible GraphRAG Initial Version Blog Post

See New Tabbed UI for Flexible GraphRAG (and Flexible RAG)

See Flexible GraphRAG: Performance improvements, FalkorDB graph database support added

See Flexible GraphRAG: Supports ArcadeDB Graph Database with new LlamaIndex Integration

See Flexible GraphRAG: Amazon Neptune, Neptune Analytics, and Graph Explorer support added