Files & Documents

Extract and analyze Google Drive documents with AI

20 nodes 285 133 Automatic trigger
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Workflow Description

Automation receives chat queries, loads documents from Google Drive, splits text into chunks, converts them to OpenAI embeddings, stores vectors in Pinecone for intelligent search, then extracts and delivers relevant information to users.

How it works

  1. 1.Receive user question via chat interface
  2. 2.Load documents from specified Google Drive folders
  3. 3.Split text into processable chunks
  4. 4.Generate OpenAI embeddings and store in Pinecone
  5. 5.Search for chunks most relevant to the query
  6. 6.Extract answer and send to user

Use cases

  • Answer questions about content stored in Google Drive files
  • Perform intelligent search across thousands of documents
  • Index and summarize large file archives efficiently

Requirements

  • Google account with Google Drive access permissions
  • OpenAI API key for embedding generation
  • Pinecone account for vector storage and retrieval
  • Documents in processable formats (PDF, DOCX, TXT)

Service Value

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

Apps Used

Vector Store Chat Trigger OpenAI Google Drive Document Default Data Loader Text Splitter Twitter/X

Details

Trigger Automatic trigger
Nodes 20
Apps 7
Views 285
Downloads 133

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 (20)

/

When clicking "Execute Workflow"

Manual Trigger

#1

Sticky Note

Sticky Note

#2

Sticky Note2

Sticky Note

#3

Sticky Note1

Sticky Note

#4

Sticky Note4

Sticky Note

#5

Pinecone Vector Store

Vector Store Pinecone

#6

When chat message received

Chat Trigger

#7

OpenAI Chat Model1

OpenAI

#8

Set file URL in Google Drive

Set

#9

Download file

Google Drive

#10

Default Data Loader

Document Default Data Loader

#11

Embeddings OpenAI2

OpenAI

#12

Embeddings OpenAI

OpenAI

#13

Recursive Character Text Splitter

Text Splitter Recursive Character Text Splitter

#14

Set max chunks to send to model

Set

#15

Get top chunks matching query

Vector Store Pinecone

#16

Prepare chunks

Code

#17

Answer the query based on chunks

Information Extractor

#18

Compose citations

Set

#19

Generate response

Set

#20