Create a Voice & Text Telegram Assistant with Lookio RAG and GPT-4.1
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.
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