AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge

Using the knowledge graphs instead of RAG vector stores This workflow creates an AI chatbot agent that has access to several knowledge bases at the same time (used as "experts"). These knowledge bases are provided using the InfraNodus GraphRAG using the knowledge graphs and providing high-quality responses without the need to set up complex RAG vector store workflows. The advantages of using GraphRAG instead of the standard vector stores for knowledge are: Easy and quick to set up (no complex data import workflows needed) A knowledge graph has a holistic view of your knowledge base Better retrieval of relations between the document chunks = higher quality responses How it works This template

Help me set up the n8n workflow "AI Chatbot Agent with a Panel of Experts using InfraNodus GraphRAG Knowledge" (https://n8n.io/workflows/4402). It uses: AI Agent, OpenAI Chat Model, Simple Memory. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.