Skip to main content

Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge

Workflow preview

Workflow preview
100%
Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge preview
Open on n8n.io

Important notice

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

1. Workflow Overview

AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI) This no code workflow turns your Telegram bot into an intelligent, always on AI support agent that references your busine...

Best for

  • Support Chatbot automation workflows
  • AI RAG automation workflows
  • intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.googledocstool, n8n-nodes-base.telegramtrigger, n8n-nodes-base.telegram, n8n-nodes-base.stickynote, @n8n/n8n-nodes-langchain.agent

Source and attribution

This workflow is cataloged by N8N Workflows and links back to its original n8n.io source page by Automate With Marc.

Original n8n.io source

1.1 Workflow description

Title
Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge
Workflow name
Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge

🤖 AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI)

This no-code workflow turns your Telegram bot into an intelligent, always-on AI support agent that references your business documentation in Google Docs to respond to customer queries—instantly and accurately.

Watch full step-by-step video tutorial of the build here: https://youtu.be/Mlv7CjGO7wI

🔧 How it works: Telegram Trigger – Captures incoming messages from users on your Telegram bot

Langchain AI Agent (OpenAI GPT) – Interprets the message and uses RAG (retrieval-augmented generation) techniques to craft an answer

Google Docs Tool – Connects to and retrieves context from your specified Google Doc (e.g. FAQ, SOPs, policies)

Memory Buffer – Keeps track of recent chat history for more human-like conversations

Telegram Reply Node – Sends the AI-generated response back to the user

đź’ˇ Use Cases: E-commerce customer service

SaaS product onboarding

Internal helpdesk bot for teams

WhatsApp-style support for digital businesses

đź§  What makes this powerful: Supports complex questions by referencing a live Google Doc knowledge base

Works in plain conversational language (no buttons or forms needed)

Runs 24/7 with zero code

Easily extendable to Slack, WhatsApp, or email support

🛠️ Tools used: Telegram Node (trigger + send)

Langchain Agent with OpenAI GPT

Google Docs Tool

Memory Buffer

Sticky Notes for easy understanding

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 - OpenAI Chat Model

Type / Role
@n8n/n8n-nodes-langchain.lmChatOpenAi - lmChatOpenAi
Config choices
Version 1.2

Block 2 - Simple Memory

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

Block 3 - Google Docs

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

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 - Sticky Note

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

Block 7 - Sticky Note1

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

Block 8 - Sticky Note2

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

Block 9 - Customer Support AI Agent

Type / Role
@n8n/n8n-nodes-langchain.agent - agent
Config choices
Version 2

Block 10 - Sticky Note6

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

3. Summary Table

Workflow Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge
Complexity intermediate
Nodes 10
Categories Support Chatbot, AI RAG
Author Automate With Marc
Published 11 Jun 2025

4. Reproducing the Workflow from Scratch

  1. 1. Download the workflow JSON

    Use the JSON export at /data/workflows/4875/4875.json as the source template for this automation.

  2. 2. Import the template into n8n

    Open n8n, import the downloaded JSON, and review each node before activating the workflow.

  3. 3. Configure credentials and variables

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

  4. 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. 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.

Frequently asked questions

What does Create a Telegram customer support bot with GPT4-mini and Google Docs knowledge do?

AI Customer Support Agent with Google Docs Knowledge (Telegram + OpenAI) This no code workflow turns your Telegram bot into an intelligent, always on AI support agent that references your busine...

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 Support Chatbot, AI RAG use case.