Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram

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Important notice

This workflow is provided as-is. Please review and test before using in production.

1. Workflow Overview

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 f...

Best for

Personal Productivity automation workflows
AI RAG automation workflows
advanced n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatgooglegemini, n8n-nodes-base.openweathermaptool, @n8n/n8n-nodes-langchain.agent, n8n-nodes-base.telegramtrigger, n8n-nodes-base.telegram, @n8n/n8n-nodes-langchain.toolthink, @n8n/n8n-nodes-langchain.embeddingsgooglegemini, @n8n/n8n-nodes-langchain.documentdefaultdataloader

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Mohammad Ghaffarifar.

Original n8n.io source

1.1 Workflow description

Title: Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram
Workflow name: Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram

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 table.
Users then ask questions to the bot.
The workflow performs a vector search in Supabase to find relevant document chunks based on the user's query.
Google Gemini uses the retrieved relevant chunks to generate an intelligent answer.
The bot sends the formatted answer back to the user on Telegram, utilizing HTML markup for enhanced presentation.

Set up steps:

Setup should take approximately 15-20 minutes.

Import the workflow into your n8n instance.
Configure credentials for Telegram, Google Gemini, and Supabase.
Set up your Supabase vector table using the provided SQL script.
Activate the workflow.

Detailed setup instructions, including how to get API keys and configure nodes, are available in the sticky notes within the workflow itself.

1.2 Logical Blocks

This catalog entry is organized from the workflow JSON. The node-level section below shows the executable blocks available for review before importing the template.

2. Block-by-Block Analysis

Block 1 - Google Gemini Chat Model

Type / Role: @n8n/n8n-nodes-langchain.lmChatGoogleGemini - lmChatGoogleGemini
Config choices: Version 1

Block 2 - OpenWeatherMap

Type / Role: n8n-nodes-base.openWeatherMapTool - openWeatherMapTool
Config choices: Version 1

Block 3 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 1.9

Block 4 - Telegram Trigger

Type / Role: n8n-nodes-base.telegramTrigger - telegramTrigger
Config choices: Version 1.2

Block 5 - Telegram

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 6 - Think

Type / Role: @n8n/n8n-nodes-langchain.toolThink - toolThink
Config choices: Version 1

Block 7 - Embeddings Google Gemini

Type / Role: @n8n/n8n-nodes-langchain.embeddingsGoogleGemini - embeddingsGoogleGemini
Config choices: Version 1

Block 8 - Default Data Loader

Type / Role: @n8n/n8n-nodes-langchain.documentDefaultDataLoader - documentDefaultDataLoader
Config choices: Version 1

Block 9 - Recursive Character Text Splitter

Type / Role: @n8n/n8n-nodes-langchain.textSplitterRecursiveCharacterTextSplitter - textSplitterRecursiveCharacterTextSplitter
Config choices: Version 1

Block 10 - Extract from File

Type / Role: n8n-nodes-base.extractFromFile - extractFromFile
Config choices: Version 1

Block 11 - Answer questions with a vector store

Type / Role: @n8n/n8n-nodes-langchain.toolVectorStore - toolVectorStore
Config choices: Version 1.1

Block 12 - Supabase Vector Store

Type / Role: @n8n/n8n-nodes-langchain.vectorStoreSupabase - vectorStoreSupabase
Config choices: Version 1.1

Block 13 - Sticky Note10

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 14 - Sticky Note11

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Block 15 - Telegram - Embedding Complete

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 16 - Supabase - Save Embeddings

Type / Role: @n8n/n8n-nodes-langchain.vectorStoreSupabase - vectorStoreSupabase
Config choices: Version 1.1

Block 17 - Command Router

Type / Role: n8n-nodes-base.switch - switch
Config choices: Version 3.2

Block 18 - Telegram - Download file

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 19 - Aggregate

Type / Role: n8n-nodes-base.aggregate - aggregate
Config choices: Version 1

Block 20 - Fallback- No formatting

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.2

Block 21 - Split Out

Type / Role: n8n-nodes-base.splitOut - splitOut
Config choices: Version 1

Block 22 - Simple Memory

Type / Role: @n8n/n8n-nodes-langchain.memoryBufferWindow - memoryBufferWindow
Config choices: Version 1.3

Block 23 - Handle formatting and split

Type / Role: n8n-nodes-base.code - code
Config choices: Version 2

Block 24 - Sticky Note

Type / Role: n8n-nodes-base.stickyNote - stickyNote
Config choices: Version 1

Showing the first 24 of 28 workflow blocks. Download the JSON for the full node graph.

3. Summary Table

Workflow	Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram
Complexity	advanced
Nodes	28
Categories	Personal Productivity, AI RAG
Author	Mohammad Ghaffarifar
Published	08 May 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/3940/3940.json as the source template for this automation.
2. Import the template into n8n

Open n8n, import the downloaded JSON, and review each node before activating the workflow.
3. Configure credentials and variables

Replace placeholder credentials, API keys, webhook URLs, account IDs, and environment-specific values with your own settings.
4. Test with sample data

Run the workflow manually or in a staging workspace, inspect node output, and confirm downstream systems receive the expected data.
5. Activate and monitor

Enable the workflow only after testing, then monitor executions, errors, and rate limits during the first production runs.

5. General Notes & Resources

Review imported nodes carefully before activation. This catalog entry is intended to help you inspect the workflow structure, understand required services, and find related templates faster.

Node names, credentials, schedules, webhook paths, and external service limits may need adjustment for your workspace.

Download workflow JSON Original n8n.io source Personal Productivity workflows AI RAG workflows

Frequently asked questions

What does Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram do?

What do I need before importing this workflow?

Review the workflow JSON, configure any required credentials in n8n, and test the automation in a safe workspace before using it in production.

Can I customize this workflow?

Yes. Use the block-by-block analysis and the downloadable JSON to inspect each node, then adjust credentials, prompts, schedules, filters, or destinations for your Personal Productivity, AI RAG use case.

Mohammad Ghaffarifar

1 workflow

Nodes

@n8n/n8n-nodes-langchain.lmchatgooglegemini n8n-nodes-base.openweathermaptool @n8n/n8n-nodes-langchain.agent n8n-nodes-base.telegramtrigger n8n-nodes-base.telegram @n8n/n8n-nodes-langchain.toolthink @n8n/n8n-nodes-langchain.embeddingsgooglegemini @n8n/n8n-nodes-langchain.documentdefaultdataloader

Complexity

advanced

Published 08 May 2025

Likes 0

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Install path: /data/workflows/3940/3940.json

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Document Q&A chatbot with Gemini AI and Supabase vector search for Telegram

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

📹 Watch the Bot in Action

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Google Gemini Chat Model

Block 2 - OpenWeatherMap

Block 3 - AI Agent

Block 4 - Telegram Trigger

Block 5 - Telegram

Block 6 - Think

Block 7 - Embeddings Google Gemini

Block 8 - Default Data Loader

Block 9 - Recursive Character Text Splitter

Block 10 - Extract from File

Block 11 - Answer questions with a vector store

Block 12 - Supabase Vector Store

Block 13 - Sticky Note10

Block 14 - Sticky Note11

Block 15 - Telegram - Embedding Complete

Block 16 - Supabase - Save Embeddings

Block 17 - Command Router

Block 18 - Telegram - Download file

Block 19 - Aggregate

Block 20 - Fallback- No formatting

Block 21 - Split Out

Block 22 - Simple Memory

Block 23 - Handle formatting and split

Block 24 - Sticky Note

3. Summary Table

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

2. Import the template into n8n

3. Configure credentials and variables

4. Test with sample data

5. Activate and monitor

5. General Notes & Resources

Frequently asked questions