Answer webhook voice queries from Google Drive docs using GPT-4o-mini and Supabase

Quick overview

This workflow indexes Google Drive documents into a Supabase vector store using OpenAI embeddings, then exposes a webhook that uses a GPT-4o-mini RAG agent to answer incoming questions with short, voice-friendly responses grounded in the stored documents.

How it works

1. Runs on a daily schedule at 02:00 or via manual start to reindex documents.
2. Lists files from a specified Google Drive folder and iterates through each file.
3. Downloads each Google Drive file, loads its text content, creates embeddings with OpenAI, and stores the resulting chunks in a Supabase vector table.
4. Receives a question via a POST webhook with a JSON body containing chatInput.
5. Generates an answer with GPT-4o-mini by semantically retrieving relevant passages from the Supabase vector store using the same OpenAI embeddings model.
6. Returns the generated, source-cited response to the webhook caller for voice output.

Setup

1. Add Google Drive OAuth2 credentials and replace DEINE_ORDNER_ID in the Drive query with the folder you want to index.
2. Add an OpenAI API credential and ensure the same embeddings model/settings are used for both indexing and querying.
3. Create/configure a Supabase project with a documents table and the match_documents RPC/query used for vector search, then add your Supabase credentials.
4. Copy the webhook URL from the webhook trigger and configure your calling system to POST { "chatInput": "..." } to it.