Build a GLPI Knowledge Base RAG Pipeline with Google Gemini and PostgreSQL

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Description This workflow automates the creation of a Retrieval-Augmented Generation (RAG) pipeline using content from the GLPI Knowledge Base. It retrieves and processes FAQ articles directly via the GLPI API, cleans and vectorizes the content using pgvector in PostgreSQL, and prepares the data for use by LLM-powered AI agents. What Problem Does This Solve? Manually building a RAG pipeline from a GLPI knowledge base requires integrating multiple tools, cleaning data, and managing embeddings—ta