Hylander. Alfresco Software Engineer. Docker Captain.

Zaragoza, España
Joined June 2011
Angel Borroy retweeted
🚀 ¿Sabías que ahora puedes depurar builds de Docker directamente en VS Code? Te explico cómo hacerlo paso a paso en mi nuevo vídeo 🎥👇 🔗 piped.video/PD1OYedbP1w
1
1
Angel Borroy retweeted
Segunda parte del tutorial de LocalStack ⚡️ Hoy te enseño cómo usar Terraform para desplegar infraestructura AWS en tu ordenador. 👉 Mira el vídeo completo aquí: piped.video/zaq_8TLzMkc #Terraform #LocalStack #AWS #DevOps #Cloud
1
2
The @Alfresco Community asked & we delivered! Explore the brand-new Alfresco Add-ons Catalog: alfrescolabs.github.io/alfre… Discover & share open extensions for Alfresco. Built "by the community, for the community" 💙 #Alfresco #Hyland #OpenSource
2
1
Angel Borroy retweeted
Flexible GraphRAG github.com/stevereiner/flexi… 1. React, Vue, Angular, Backend now work on Windows, Mac, Linux (standalone or in docker) 2. Amazon S3 Data Source working 3. Just got Amazon Neptune graph database working (not checked in) 4. Memgraph graph database working Flexible GraphRAG is an open source python platform supporting Docling document processing, Knowledge Graph auto-building, schemas, 13 datasources, 10 Vector databases, 7 Graph databases, Elasticsearch/OpenSearch, RAG and GraphRAG, hybrid search , and AI query / chat. Also can be a MCP server
2
1
The real @johnnewton at #HylandCommunityLIVE Munich drew parallels between Claude Shannon information theory and the evolution of Content Service Platforms, unveiling the upcoming AI-ready, open-source Cloud Content Repository, set for release in early 2026. Inspirational!
1
2
Angel Borroy retweeted
Flexible GraphRAG: a configurable open source framework for GraphRAG Flexible GraphRAG is an open source python platform supporting document processing, Knowledge Graph auto-building, Schema support, RAG and GraphRAG setup, hybrid search (fulltext, vector, graph), and AI Q&A query capabilities. It has a MCP Server, fast API Backend, Docker support, Angular, React, and Vue UI clients. Built with LlamaIndex which provides abstractions for allowing multiple vector, search graph databases, LLMs to be supported. It currently supports: Graph Databases: Neo4j ArcadeDB FalkorDB Kuzu NebulaGraph, powered by Vesoft (coming Memgraph and Amazon Neptune) Vector Databases: Qdrant, Elastic, OpenSearch Project, Neo4j, Milvus, (coming Weaviate, Chroma, Pinecone, PostgreSQL, LanceDB) Search Databases/Engines: Elasticsearch, OpenSearch, LlamaIndex built-in BM25 LLMs: LlamaIndex (OpenAI, Ollama, Claude, Gemini, etc.) Data Sources (using LlamaIndex readers): working: Web Pages, Wikipedia, Youtube, untested: Google Drive, Msft OneDrive, S3, Azure Blob, GCS, Box, SharePoint, previous: filesystem, Alfresco, CMIS. A configurable hybrid search system that optionally combines vector similarity search, full-text search, and knowledge graph GraphRAG on document processed (Docling) from multiple data sources (filesystem, Alfresco, CMIS, etc.). It has both a FastAPI backend with REST endpoints and a Model Context Protocol (MCP) server for MCP clients like Claude Desktop, etc. Also has simple Angular, React, and Vue UI clients (which use the REST APIs of the FastAPI backend) for using interacting with the system. Hybrid Search: Combines vector embeddings, BM25 full-text search, and graph traversal for comprehensive document retrieval Knowledge Graph GraphRAG: Extracts entities and relationships from documents to create graphs in graph databases for graph-based reasoning Configurable Architecture: LlamaIndex provides abstractions for vector databases, graph databases, search engines, and LLM providers Multi-Source Ingestion: Processes documents from filesystems, CMIS repositories, and Alfresco systems FastAPI Server with REST API: FastAPI server with REST API for document ingesting, hybrid search, and AI Q&A query MCP Server: MCP server that provides MCP Clients like Claude Desktop, etc. tools for document and text ingesting, hybrid search and AI Q&A query. UI Clients: Angular, React, and Vue UI clients support choosing the data source (filesystem, Alfresco, CMIS, etc.), ingesting documents, performing hybrid searches and AI Q&A Queries. Deployment Flexibility: Supports both standalone and Docker deployment modes. Docker infrastructure provides modular database selection via docker-compose includes – vector, graph, and search databases can be included or excluded with a single comment. Choose between hybrid deployment (databases in Docker, backend and UIs standalone) or full containerization. github.com/stevereiner/flexi… #GraphRAG #GraphDB #OpenSource #EmergingTech #LLMs #VectorDB #Python -- The Year of the Graph's Autumn 2025 newsletter issue on all things #KnowledgeGraph, #GraphDB, Graph #Analytics / #DataScience / #AI and #SemTech is out. Subscribe and follow to be in the know. Reach out if you'd like to be featured 👇 yearofthegraph.xyz/newslette…
9
27
Site Status Update for community.hyland.com: @Hyland is aware of some disruptions impacting access/performance. Our engineering team is actively working to restore full service. We’ll share updates as soon as we can. Thanks for your patience. #Hyland
1
The new @Alfresco Developer Series is live! aborroy.github.io/alfresco-d… Based on @jeffpotts01 classic work, started with Suresh Joshee at the @Hyland CL Hack-a-thon 2025. Not yet ready for Alfresco 25, but updates coming soon! #Alfresco #Hyland #OpenSource #Developers
1
Privacy + @Alfresco users: need to redact PII in PDFs automatically? Meet alf-tengine-pii Uses Microsoft Presidio to detect & remove names, emails, credit cards,... outputs clean PDFs. Open source, container-ready, configurable. github.com/aborroy/alf-tengi… #Alfresco #OpenSource
1
3