Telegram AI Chatbot Agent with InfraNodus GraphRAG Knowledge Base

Using the knowledge graphs instead of RAG vector stores This workflow creates a Telegram 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 and update (no complex data import workflows or vector stores needed) A knowledge graph has a holistic view of your knowledge base and knows what it's about Better retrieval of relations between the document c

Help me set up the n8n workflow "Telegram AI Chatbot Agent with InfraNodus GraphRAG Knowledge Base" (https://n8n.io/workflows/4485). It uses: Telegram, 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.