AI Agents

Automate Google Drive

22 nodes 230 123 Automatic trigger
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Workflow Description

An intelligent automation template integrating OpenAI with Google Drive for automated document processing. Extracts and analyzes text using advanced language models, then stores embeddings in a vector database for fast semantic search and retrieval.

How it works

  1. 1.Trigger the workflow manually or via chat interface to start document processing
  2. 2.Extract content from Google Drive files and split text into manageable chunks
  3. 3.Convert text into numerical embeddings using OpenAI models
  4. 4.Store vector data in Pinecone for semantic search capability
  5. 5.Process user queries through LLM chains and return contextually relevant results

Use cases

  • Intelligent search across large company document repositories using natural language
  • Build an automated Q&A system based on Google Drive content
  • Continuously classify and index administrative documents with semantic understanding

Requirements

  • Valid API keys for OpenAI, Google Drive, and Pinecone services
  • Sufficient permissions to access and read folders and files in Google Drive
  • Stable and secure connection to processing and storage infrastructure

Service Value

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

Apps Used

OpenAI Document Default Data Loader Google Drive Chat Trigger Output Parser LLM Chain Vector Store Text Splitter

Details

Trigger Automatic trigger
Nodes 22
Apps 8
Views 230
Downloads 123

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 (22)

/

When clicking "Execute Workflow"

Manual Trigger

#1

Embeddings OpenAI

OpenAI

#2

Sticky Note

Sticky Note

#3

Default Data Loader

Document Default Data Loader

#4

Set file URL in Google Drive

Set

#5

Sticky Note2

Sticky Note

#6

Add in metadata

Code

#7

Download file

Google Drive

#8

Chat Trigger

Chat Trigger

#9

Prepare chunks

Code

#10

Embeddings OpenAI2

OpenAI

#11

OpenAI Chat Model

OpenAI

#12

Set max chunks to send to model

Set

#13

Structured Output Parser

Output Parser Structured

#14

Compose citations

Set

#15

Generate response

Set

#16

Sticky Note1

Sticky Note

#17

Answer the query based on chunks

LLM Chain

#18

Sticky Note4

Sticky Note

#19

Get top chunks matching query

Vector Store Pinecone

#20

Add to Pinecone vector store

Vector Store Pinecone

#21

Recursive Character Text Splitter

Text Splitter Recursive Character Text Splitter

#22