Templates / Index Google Drive files into a Supabase vector store with OpenAI embeddings

Index Google Drive files into a Supabase vector store with OpenAI embeddings

Ready for 3.0

by Allan Vaccarizi ✓ · 1,882 views · created 2025-09-25 · AI RAG

Ready for 3.0. This template uses no nodes that n8n 3.0 removes. No removed nodes, versions or helpers found. Static check, last run 2026-10-19.

What this workflow does

This AI workflow has 26 nodes and runs when a chat message arrives (plus 2 other triggers). Along the way it connects Embeddings OpenAI, Google Drive, Supabase and Supabase Vector Store and 1 more.

How it runs

Trigger: When a chat message arrives (plus 2 other triggers).

  1. Create Docs Table and Match Fn (Postgres): run a query
  2. Loop Over Drive Files (Loop Over Items (Split in Batches)): loops over the items in batches
  3. Create Document Metadata Table (Postgres): run a query
  4. Set File Metadata Fields (Edit Fields (Set)): sets 4 fields: file_id, file_type, file_title…
  5. Create Document Rows Table (Postgres): run a query
  6. Delete Old Doc Rows in Supabase (Supabase): delete
  7. Delete Old Data Rows in Supabase (Supabase): delete
  8. Insert Document Metadata to DB (Postgres): create or update
  9. Download File from Drive (Google Drive): download
  10. Route by File Type (Switch): routes items into 4 branches

…plus 10 more steps. See the full node list below.

Services it uses

Embeddings OpenAIGoogle DriveSupabaseSupabase Vector StorePostgres

Before you upgrade to n8n 3.0

Nothing in this workflow is removed in n8n 3.0, so it should import and run after the upgrade.

Nodes used (15)

From the author

📺 Full walkthrough video: https://youtu.be/r5kNla0O7I Author: Cole Medin Who it's for This workflow is for developers, data engineers, and knowledge management teams who need to automatically ingest documents stored in Google Drive into a searchable vector…

Excerpt from Allan Vaccarizi's description on n8n.io.

View the original on n8n.io → Check your own copy

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