Build a Chatbot with Reinforced Learning Human Feedback (RLHF) and RAG
n8n template #4689Summary
Use templateWho 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
Hand off to your agent
Prompt
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.
Paste into Claude Code and it will do the rest.
Apps and nodes
TelegramGoogle DocsCodeAI AgentEmbeddings OpenAIOpenAI Chat ModelRecursive Character Text SplitterDefault Data LoaderMongoDB Chat MemoryMongoDB Atlas Vector Store
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