AI Agents

Extract Google Drive Documents and Build Knowledge Base in Supabase

21 nodes 323 148 Automatic trigger
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Workflow Description

Automation that loads documents from Google Drive automatically, splits them into text chunks, converts them to semantic vectors via OpenAI, and stores them in Supabase to answer intelligent questions powered by AI retrieval.

How it works

  1. 1.Trigger automatic document loading from specified Google Drive folder
  2. 2.Split text content into manageable chunks for processing
  3. 3.Convert text chunks into semantic vectors using OpenAI embeddings
  4. 4.Store vectors in Supabase vector database for semantic search
  5. 5.Receive user questions through chat interface
  6. 6.Retrieve and respond with answers based on stored document content

Use cases

  • Build an intelligent assistant that answers employee questions about company policies and procedures from stored documents
  • Search and extract precise information from legal documents, compliance reports, or extensive knowledge bases instantly

Requirements

  • Google Drive account with full access permissions to target documents
  • OpenAI API keys for generating semantic embeddings
  • Supabase database configured and ready for vector storage operations

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 323
Downloads 148

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