Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system)

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Important notice

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

1. Workflow Overview

Description Overview This workflow creates a chat based Retrieval Augmented Generation (RAG) agent that lets you upload documents to Google Drive and then query them directly through Telegram. I...

Best for

Internal Wiki automation workflows
AI RAG automation workflows
intermediate n8n builders looking for reusable templates

Tools used

@n8n/n8n-nodes-langchain.documentdefaultdataloader, n8n-nodes-base.googledrive, @n8n/n8n-nodes-langchain.embeddingsopenai, @n8n/n8n-nodes-langchain.agent, @n8n/n8n-nodes-langchain.lmchatopenai, @n8n/n8n-nodes-langchain.memorybufferwindow, n8n-nodes-base.googledrivetrigger, n8n-nodes-base.stickynote

Source and attribution

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

Original n8n.io source

1.1 Workflow description

Title: Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system)
Workflow name: Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system)

Description 📌 Overview

This workflow creates a chat-based Retrieval-Augmented Generation (RAG) agent that lets you upload documents to Google Drive and then query them directly through Telegram. It uses embeddings, vector storage, and an AI agent to retrieve, analyze, and answer user questions with context-aware responses.

🧩 Key Features

📂 Google Drive Integration

Watches a folder for new file uploads.

Downloads and loads documents automatically into the system.

🔎 Vector Embeddings & Storage

Uses OpenAI embeddings to transform documents into vectors.

Stores them in an in-memory vector store for retrieval.

🤖 AI Agent with Memory

Built on LangChain Agent + GPT-4.1-mini.

Performs similarity search in the vector store.

Provides contextual answers with citations from the uploaded documents.

Maintains short-term conversation memory for better continuity.

💬 Telegram Bot Integration

Users can send questions directly to the bot.

AI agent retrieves relevant information and replies with clear answers.

⚙️ How It Works

Trigger: Upload a file into the Google Drive folder.

Processing: Workflow downloads the file → loads → embeds → stores in vector memory.

Query: User sends a question via Telegram.

Retrieval & Response: AI agent searches stored documents → analyzes results → returns summarized answer in Telegram.

🔐 Requirements

Google Drive OAuth credentials.

OpenAI API key (for embeddings + LLM).

Telegram Bot API token.

📥 Use Cases

📑 Knowledge base assistant – Upload internal docs and query them in chat.

🏫 Learning support – Students upload study materials and ask questions.

📊 Business intelligence – Teams upload reports and get instant summaries.

More templet: https://auton8n.pw/

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 - Default Data Loader

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

Block 2 - Download file

Type / Role: n8n-nodes-base.googleDrive - googleDrive
Config choices: Version 3

Block 3 - Embedding model

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

Block 4 - AI Agent

Type / Role: @n8n/n8n-nodes-langchain.agent - agent
Config choices: Version 2.2

Block 5 - Model

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

Block 6 - Simple Memory

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

Block 7 - File uploaded

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

Block 8 - Sticky Note

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

Block 9 - Sticky Note3

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

Block 10 - Insert documents

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

Block 11 - Retrieve documents

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

Block 12 - Listen for incoming events

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

Block 13 - Telegram

Type / Role: n8n-nodes-base.telegram - telegram
Config choices: Version 1.1

3. Summary Table

Workflow	Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system)
Complexity	intermediate
Nodes	13
Categories	Internal Wiki, AI RAG
Author	DuyTran
Published	02 Sept 2025

4. Reproducing the Workflow from Scratch

1. Download the workflow JSON

Use the JSON export at /data/workflows/8147/8147.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 Internal Wiki workflows AI RAG workflows

Frequently asked questions

What does Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system) do?

Description Overview This workflow creates a chat based Retrieval Augmented Generation (RAG) agent that lets you upload documents to Google Drive and then query them directly through Telegram. I...

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 Internal Wiki, AI RAG use case.

DuyTran

4 workflows

Nodes

@n8n/n8n-nodes-langchain.documentdefaultdataloader n8n-nodes-base.googledrive @n8n/n8n-nodes-langchain.embeddingsopenai @n8n/n8n-nodes-langchain.agent @n8n/n8n-nodes-langchain.lmchatopenai @n8n/n8n-nodes-langchain.memorybufferwindow n8n-nodes-base.googledrivetrigger n8n-nodes-base.stickynote

Complexity

intermediate

Published 02 Sept 2025

Likes 0

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Install path: /data/workflows/8147/8147.json

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Document Q&A chatbot with Google Drive, GPT-4-mini & Telegram (RAG system)

Workflow preview

Important notice

1. Workflow Overview

Best for

Tools used

Source and attribution

1.1 Workflow description

1.2 Logical Blocks

2. Block-by-Block Analysis

Block 1 - Default Data Loader

Block 2 - Download file

Block 3 - Embedding model

Block 4 - AI Agent

Block 5 - Model

Block 6 - Simple Memory

Block 7 - File uploaded

Block 8 - Sticky Note

Block 9 - Sticky Note3

Block 10 - Insert documents

Block 11 - Retrieve documents

Block 12 - Listen for incoming events

Block 13 - Telegram

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