Build a Chatbot with Reinforced Learning Human Feedback (RLHF) and RAG

Who is this for? This template is designed for internal support teams, product specialists, and knowledge managers who want to build an AI-powered knowledge assistant with retrieval-augmented generation (RAG) and reinforcement learning from human feedback (RLHF) via Telegram. What problem is this workflow solving? Manual knowledge management and answering support queries can be time-consuming and error-prone. This solution automates importing and indexing official documentation into MongoDB vector search and enhances AI responses with Telegram-based user feedback to continuously improve answer quality. What these workflows do Workflow 1: Document ingestion & indexing Manually triggered workf

Help me set up the n8n workflow "Build a Chatbot with Reinforced Learning Human Feedback (RLHF) and RAG" (https://n8n.io/workflows/4689). It uses: Telegram, Google Docs, Code, AI Agent, Embeddings OpenAI, OpenAI Chat Model, Recursive Character Text Splitter, Default Data Loader, MongoDB Chat Memory, MongoDB Atlas Vector Store. Import the template JSON into my n8n instance, list every credential I need to create, and walk me through testing it.