AI Agents

Extract Google Drive Documents and Build an Intelligent Knowledge Base in Supabase

21 nodes 315 151 Automatic trigger
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Workflow Description

This automation retrieves documents from Google Drive, splits content into manageable text chunks, generates AI-powered embeddings via OpenAI, and stores them in Supabase for precise retrieval through a chat interface.

How it works

  1. 1.Monitor Google Drive folders and automatically extract new documents
  2. 2.Split document content into coherent text segments using recursive character splitter
  3. 3.Generate intelligent embeddings for segments via OpenAI and store in Supabase Vector Store
  4. 4.Answer user queries through a chat interface based on the stored knowledge base

Use cases

  • Create an intelligent assistant that answers employee questions based on company documents stored in Google Drive
  • Automate extraction from contracts and reports, converting them into a searchable knowledge base

Requirements

  • Google Drive account with documents to be processed
  • OpenAI API key for generating embeddings and answering queries
  • Supabase database configured to store intelligent embeddings

Service Value

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

Apps Used

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

Details

Trigger Automatic trigger
Nodes 21
Apps 8
Views 315
Downloads 151

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 (21)

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Google Drive

Google Drive

#1

Default Data Loader

Document Default Data Loader

#2

Sticky Note

Sticky Note

#3

Sticky Note1

Sticky Note

#4

Sticky Note2

Sticky Note

#5

Sticky Note3

Sticky Note

#6

Question and Answer Chain

Chain Retrieval Qa

#7

OpenAI Chat Model

OpenAI

#8

Vector Store Retriever

Retriever Vector Store

#9

Recursive Character Text Splitter1

Text Splitter Recursive Character Text Splitter

#10

Customize Response

Set

#11

When chat message received

Chat Trigger

#12

Retrieve by Query

Vector Store Supabase

#13

Embeddings OpenAI Retrieval

OpenAI

#14

Embeddings OpenAI Insertion

OpenAI

#15

Placeholder (File/Content to Upsert)

Set

#16

Embeddings OpenAI Upserting

OpenAI

#17

Insert Documents

Vector Store Supabase

#18

Retrieve Rows from Table

Supabase

#19

Sticky Note4

Sticky Note

#20

Update Documents

Vector Store Supabase

#21