AI Agents
Store Notion pages as vector documents in Supabase using OpenAI
9 nodes
255
134
Automatic trigger
Workflow Description
Automate the extraction of Notion pages and convert them into vector embeddings using OpenAI, then store them in Supabase for intelligent search and fast retrieval of knowledge.
How it works
- 1.Trigger automation when a page is added or modified in Notion
- 2.Split page content into manageable text segments using Token Splitter
- 3.Generate embedding vectors for text segments through OpenAI API
- 4.Store vectors and metadata in Supabase vector database
Use cases
- Build an intelligent search engine across your Notion knowledge base
- Create a semantic recommendation system that surfaces similar content and related pages
Requirements
- Valid OpenAI API key with embeddings model access
- Configured Supabase connection with properly structured vector tables
- Full access permissions to your Notion workspace
Service Value
Ideal as a smart automation service combining integrations and AI to produce ready-to-use results.
Apps Used
OpenAI
Text Splitter
Notion
Document Default Data Loader
Vector Store
Details
Trigger
Automatic trigger
Nodes
9
Apps
5
Views
255
Downloads
134
How to Use
- 1.Click "Download Template"
- 2.Open your n8n dashboard
- 3.Go to Workflows > Import from File
- 4.Select downloaded file and configure credentials
Nodes Used (9)
Sticky Note
Sticky Note
Embeddings OpenAI
OpenAI
Token Splitter
Text Splitter Token Splitter
Notion - Page Added Trigger
Notion
Notion - Retrieve Page Content
Notion
Filter Non-Text Content
Filter
Summarize - Concatenate Notion's blocks content
Summarize
Create metadata and load content
Document Default Data Loader
Supabase Vector Store
Vector Store Supabase