AI Agents

AI-powered chatbot RAG for your Google Drive documents...

50 nodes 246 161 Automatic trigger
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Workflow Description

Build an intelligent agent that extracts files from Google Drive, transforms them into a searchable knowledge base, and answers user queries via Telegram or X based on document content using retrieval-augmented generation.

How it works

  1. 1.Load documents from Google Drive and split them into processable text chunks
  2. 2.Convert text segments into vectors stored in Qdrant for semantic search capability
  3. 3.Receive user queries through Telegram or X and route them to an AI agent powered by Gemini or OpenAI
  4. 4.Search the knowledge base and retrieve the most relevant document segments
  5. 5.Generate intelligent responses with contextual memory and deliver them back to the user

Use cases

  • Create an intelligent assistant that answers employee questions based on company policies and stored documents
  • Convert a file repository into a knowledge engine delivering accurate answers in real time
  • Build an AI-powered customer support system grounded in your organization's knowledge base

Requirements

  • Active Google Drive account with organized documents ready for processing
  • API keys from Gemini, OpenAI, and Telegram or X for complete integration
  • Running Qdrant vector database instance or configured cloud deployment

Service Value

Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.

Apps Used

Document Default Data Loader Text Splitter Vector Store Split In Batches Gemini Twitter/X Google Drive OpenAI Telegram AI Agent Memory Chat Trigger Google Docs

Details

Trigger Automatic trigger
Nodes 50
Apps 13
Views 246
Downloads 161

How to Use

  1. 1.Click "Download Template"
  2. 2.Open your n8n dashboard
  3. 3.Go to Workflows > Import from File
  4. 4.Select downloaded file and configure credentials

Nodes Used (50)

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Data Loader

Document Default Data Loader

#1

Token Splitter

Text Splitter Token Splitter

#2

Qdrant Vector Store

Vector Store Qdrant

#3

Loop Over Items

Split In Batches

#4

Wait

Wait

#5

When clicking ‘Test workflow’

Manual Trigger

#6

Google Gemini Chat Model

Gemini Model

#7

Merge

Merge

#8

Extract Meta Data

Information Extractor

#9

Get File Contents

Extract From File

#10

Download File From Google Drive

Google Drive

#11

Find File Ids in Google Drive Folder

Google Drive

#12

text-embeddings-3-large

OpenAI

#13

Google Folder ID

Set

#14

gpt-4o-mini1

OpenAI

#15

Delete Qdrant Points by File ID

Code

#16

Qdrant Collection Name

Set

#17

File Id List

Summarize

#18

Merge1

Merge

#19

Merge2

Merge

#20

Sticky Note

Sticky Note

#21

Confirm Qdrant Delete Points

Set

#22

If

If

#23

Sticky Note1

Sticky Note

#24

Send Declined Message

Set

#25

Sticky Note2

Sticky Note

#26

Sticky Note3

Sticky Note

#27

Sticky Note4

Sticky Note

#28

Sticky Note5

Sticky Note

#29

Sticky Note6

Sticky Note

#30

Sticky Note7

Sticky Note

#31

Sticky Note8

Sticky Note

#32

Webhook

Webhook

#33

AI Agent

Agent

#34

Window Buffer Memory

Memory Buffer Window

#35

When chat message received

Chat Trigger

#36

Google Gemini Chat Model1

Gemini Model

#37

text-embeddings-3-large1

OpenAI

#38

Sticky Note9

Sticky Note

#39

Sticky Note10

Sticky Note

#40

Sticky Note11

Sticky Note

#41

Sticky Note12

Sticky Note

#42

Google Drive

Google Drive

#43

Respond to User

Set

#44

Sticky Note13

Sticky Note

#45

Update Chat History

Google Docs

#46

Qdrant Vector Store Tool

Vector Store Qdrant

#47

OpenAI Chat Model

OpenAI

#48

Send Completed Message

Set

#49

Sticky Note14

Sticky Note

#50

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