Create a Telegram bot that answers questions using Retrieval-Augmented Generation (RAG) powered by Lookio and an LLM agent (GPT-4.1). This template handles both text and voice messages (voice transcribed via a Mistral model by default), routes queries through an agent that can call a Lookio tool to fetch knowledge from your uploaded documents, and returns concise, Telegram-friendly replies. A security switch lets you restrict use to a single Telegram username for private testing, or remove the filter to make the bot public. Who is this for? Internal teams & knowledge workers : Turn your internal docs into an interactive Telegram assistant for quick knowledge lookups. Support & ops : Provide on-demand answers from your internal knowledge base without exposing full documentation. Developers & automation engineers : Use this as a reference for integrating agents, transcription, and RAG inside n8n. No-code builders : Quickly deploy a chat interface that uses Lookio for accurate, source-backed answers. What it does / What problem does this solve? Provides accurate, source-backed answers : Routes queries to Lookio so replies are grounded in your documents instead of generic web knowledge. Handles voice & text transparently : Accepts Telegram voice messages, transcribes them (via the Mistral API node by default), and treats transcripts the same as typed text. Simple agent + tool architecture : Uses a LangChain AI Agent with a Query knowledge base tool to separate reasoning from retrieval. Privacy control : Includes a Myself? filter to restrict access to a specific Telegram username for safe testing. How it works Trigger : Telegram Trigger receives incoming messages (text or voice). Route : Message Router detects voice vs text. Voice files are fetched with Get Audio File . Transcribe : Mistral transcribe receives the audio file and returns a transcript; the transcript or text is normalized into preset_user_message and consolidated in Consolidate user message . Agent : AI Agent (GPT-4.1-mini configured) runs with a system prompt that instructs it to call the Query knowledge base tool when domain knowledge is required. Respond : The agent output is sent back to the user via Telegram answer . How to set up Create a Lookio assistant : Sign up at https://www.lookio.app/ , upload documents, and create an assistant. Add credentials in n8n : Configure Telegram API , OpenAI (or your LLM provider), and Mistral Cloud credentials in n8n. Configure Lookio tool : In the Query knowledge base node, replace <your-lookio-api-key> and <your-assistant-id> placeholders with your Lookio API Key and Assistant ID. Set Telegram privacy (optional) : Edit the Myself? If node and replace <Replace with your Telegram username> with your username to restrict access. Remove the node to allow public use. Adjust transcription (optional) : Swap the Mistral transcribe HTTP node for another provider (OpenAI, Whisper, etc.) and update its prompt to include your jargon list. Connect LLM : In OpenAI Chat Model node, add your OpenAI API key (or configure another LLM node) and ensure the AI Agent node references this model. Activate workflow : Activate the workflow and test by messaging your bot in Telegram. Requirements An n8n instance (cloud or self-hosted) A Telegram Bot token added in n8n credentials A Lookio account, API Key , and Assistant ID An LLM provider account (OpenAI or equivalent) for the OpenAI Chat Model node A Mistral API key (or other transcription provider) for voice transcription How to take it further Add provenance & sources : Parse Lookio responses and include short citations or source links in the agent replies. Rich replies : Use Telegram media (images, files) or inline keyboards to create follow-up actions (open docs, request feedback, escalate to humans). Multi-user access control : Replace the single-username filter with a list or role-based access system (Airtable or Google Sheets lookup) to allow multiple trusted users. Logging & analytics : Save queries and agent responses to Airtable or Google Sheets for monitoring, quality checks, and prompt improvement.