Create Personal Data Vector Store from Google Sheets with OpenAI & Gemini AI

Go to Workflow
0 views
Built by Mustafa Polat Mustafa Polat
Created on August 12, 2025

Description

This workflow integrates Google Sheets with Supabase Vector Store for storing personal data as vectors. It utilizes OpenAI and Google Gemini AI models for enhanced data processing and querying.

The workflow performs the following tasks:
Extracts personal data** from Google Sheets.
Processes the data using AI tools like OpenAI and Google Gemini for intelligent insights.
Inserts the data* into *Supabase** as vectors, enabling efficient storage and fast querying.
Includes seamless integration with Postgres for memory management.
Supports data loading, embedding, and management.

This template is ideal for:
Personal data storage with AI-driven querying and analysis.
Building intelligent agents that interact with your data.
Efficient vector-based storage for personal information.

Perfect for those looking to integrate AI into their personal data workflows.

This workflow was created by Mustafa Polat and shared publicly on the n8n community template library. n8nFind indexes it for discovery — the workflow remains the property of its original creator.

Nodes Used (7)

AI Agent
@n8n/n8n-nodes-langchain.agent
Default Data Loader
@n8n/n8n-nodes-langchain.documentDefaultDataLoader
Embeddings OpenAI
@n8n/n8n-nodes-langchain.embeddingsOpenAi
Google Gemini Chat Model
@n8n/n8n-nodes-langchain.lmChatGoogleGemini
Google Sheets
n8n-nodes-base.googleSheets
Postgres Chat Memory
@n8n/n8n-nodes-langchain.memoryPostgresChat
Supabase Vector Store
@n8n/n8n-nodes-langchain.vectorStoreSupabase