Document Q&A Chatbot with Gemini AI and Supabase Vector Search for Telegram

n8n template #3940

Summary

This template creates a Telegram AI Assistant that answers questions based on your documents, powered by Google Gemini and Supabase. Key features include Intelligent HTML Post-processing for rich formatting in Telegram and Adaptive Message Chunking to handle long text responses. 📹 Watch the Bot in Action ▶️ Click the image above to watch a live demo on YouTube. This video provides a live demonstration of the bot's core features and how it interacts. See a quick walkthrough of its capabilities and user flow. How it works: User uploads a PDF document to a Telegram bot. The workflow processes the PDF, creates embeddings using Google Gemini, and stores these embeddings in a Supabase vector tabl

How to set it up

Open template #3940 on n8n.io and click Use for free, or copy the template JSON and paste it onto an empty canvas in n8n.
Create 4 credentials under Credentials → Add credential: Telegram, Supabase Vector Store, Embeddings Google Gemini, Google Gemini Chat Model. Then open each of those nodes and pick the credential.
Check the model in the AI Agent node. The template may point at a model your account can't use; swap it for one you have access to.
Click Execute workflow and step through each node's output to confirm the data looks right.
Toggle the workflow to Active so its trigger runs on its own.

Hand off to your agent

Prompt

Help me set up the n8n workflow "Document Q&A Chatbot with Gemini AI and Supabase Vector Search for Telegram" (https://n8n.io/workflows/3940). It uses: Telegram, Code, AI Agent, Simple Memory, Recursive Character Text Splitter, Supabase Vector Store, Default Data Loader, Embeddings Google Gemini, Google Gemini Chat Model, Vector Store Question Answer Tool, Think Tool. 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

Telegram Code AI Agent Simple Memory Recursive Character Text Splitter Supabase Vector Store Default Data Loader Embeddings Google Gemini Google Gemini Chat Model Vector Store Question Answer Tool Think Tool

Questions

Yes. Mohammad Ghaffarifar published it free on n8n.io, and it has 17K views. It runs on n8n Cloud or a self-hosted n8n instance.

Telegram, Supabase Vector Store, Embeddings Google Gemini, Google Gemini Chat Model. The other 7 nodes are built into n8n.

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