Automated RAG Pipelines: Google Drive to Supabase with OpenAI Embeddings
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This workflow automates the creation and updating of Retrieval Augmented Generation (RAG) pipelines. It uses Google Drive triggers to monitor document changes, Supabase for vector storage, and OpenAI for embeddings.
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About This Workflow
Overview
This n8n workflow is designed to build and manage Retrieval Augmented Generation (RAG) pipelines efficiently. It leverages Google Drive as the source for documents, Supabase as the vector database to store and query embeddings, and OpenAI for generating those embeddings. The workflow automatically detects new or updated files in a specified Google Drive folder, processes them, stores their embeddings in Supabase, and handles deletions if files are moved to a 'Recycling Bin' folder. This provides a robust system for managing a dynamic knowledge base for AI applications.
Key Features
- Automated Document Ingestion: Triggers automatically when new or updated files are detected in a designated Google Drive folder.
- RAG Pipeline Management: Creates and updates vector embeddings in Supabase for use in RAG systems.
- Smart Deletion: Automatically removes document embeddings from Supabase when files are moved to a 'Recycling Bin' folder.
- Flexible Document Conversion: Supports converting Google Docs to PDF for consistent processing.
- OpenAI Embeddings Integration: Utilizes OpenAI's powerful models to generate semantic embeddings.
How To Use
- Set up Google Drive Triggers: Configure the 'Google Drive Trigger' nodes to monitor specific folders for file creations and updates.
- Connect Supabase: Ensure your Supabase credentials are correctly set up for the 'Supabase Vector Store' nodes to interact with your database.
- Configure OpenAI Embeddings: Link your OpenAI API credentials to the 'Embeddings OpenAI' nodes.
- Define Document Processing: The workflow downloads files from Google Drive, converts them to PDF if necessary, and loads them using the 'Default Data Loader'.
- Vector Storage: The processed documents are then embedded and stored in your Supabase vector store.
- Handle Deletions: Set up the 'Recycling Bin' Google Drive trigger and the associated 'Delete a row' Supabase node to remove embeddings when files are no longer needed.
Apps Used
Workflow JSON
{
"id": "ce38f2b2-a08c-43db-b309-7efbe18bf8e8",
"name": "Automated RAG Pipelines: Google Drive to Supabase with OpenAI Embeddings",
"nodes": 0,
"category": "AI Automation & Data Management",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
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ID: ce38f2b2-a08c...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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