Monitors a Google Drive folder for new or modified files, chunks the text, generates OpenAI embeddings.
Verified 2026-07-07
Developer-Engineering
What it does
You get instant access to your Google Drive documents by having them automatically indexed as searchable knowledge. The system pulls new or updated files from your folder, breaks them into manageable pieces, creates OpenAI embeddings, and saves the results in Supabase for fast retrieval.
How it works
When it runs
Triggered by an event · Event · on new or modified file in Google Drive
How hands-off
Assists you, you do the final step
Setup
An afternoon · about an afternoon
Works with
Google Drive, OpenAI, Supabase, n8n
Tools that fit
Services
Google Drive : Trigger and read document files
Supabase : Store and retrieve contextualized vector data
LLM
OpenAI : Generate text embeddings for vector search
api
n8n : Orchestrate the workflow automation pipeline
Watch out for
⚠ Google Drive API quotas are strict so add retry logic with exponential backoff to avoid 429 errors.
⚠ Large binary files like PDFs may fail silent extraction if you do not explicitly configure a PDF parser tool before the text split step.
⚠ Supabase vector search performance degrades without an index, so create a hnsw or ivfflat index on the embedding column after initial load.
⚠ Embedding costs can spiral with unbounded file sizes, add a size filter to skip files larger than 10MB before processing.
This is what I do. I design and build AI agents like this one, and keep them running. If you want it set up for your team instead of doing it yourself, get in touch.