Local Document Question Answering with Ollama AI, Agentic RAG & PGVector

🚀 n8n Local AI Agentic RAG Template Author: Jadai kongolo What is this? This template provides an entirely local implementation of an Agentic RAG (Retrieval Augmented Generation) system in n8n that can be extended easily for your specific use case and knowledge base. Unlike standard RAG which only performs simple lookups, this agent can reason about your knowledge base, self-improve retrieval, and dynamically switch between different tools based on the specific question. Why Agentic RAG? Standard RAG has significant limitations: Poor analysis of numerical/tabular data Missing context due to document chunking Inability to connect information across documents No dynamic tool selection based o

Help me set up the n8n workflow "Local Document Question Answering with Ollama AI, Agentic RAG & PGVector" (https://n8n.io/workflows/10157). It uses: Postgres, AI Agent, OpenAI Chat Model, Recursive Character Text Splitter, Default Data Loader, Embeddings Ollama, Postgres Chat Memory, Postgres PGVector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.