Unlock Your Knowledge: Notion Pages to Vector Database with AI
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Seamlessly transform your Notion pages into intelligent vector documents stored in Supabase. Leverage AI to make your knowledge base searchable and actionable.
About This Workflow
This powerful n8n workflow automates the process of ingesting content from your Notion pages and storing it as vector embeddings in your Supabase database. By triggering on new Notion pages, fetching content, filtering out non-textual elements, and then generating embeddings with OpenAI, this workflow ensures your knowledge base is not only centralized but also intelligent. The content is chunked and enriched with metadata, making it ideal for advanced AI applications like semantic search and question answering. Setup is straightforward, requiring only a Supabase project with a vector column and your OpenAI API key.
Key Features
- Automated Notion Sync: Automatically process new Notion pages as they are added.
- Intelligent Content Processing: Filters out images and videos, focusing on actionable text.
- AI-Powered Embeddings: Utilizes OpenAI to create high-quality vector representations of your content.
- Supabase Vector Storage: Efficiently stores your text and embeddings in a Supabase vector database.
- Rich Metadata Inclusion: Attaches essential metadata like page ID, creation time, and title to each document.
How To Use
- Prerequisites: Ensure you have a Supabase project with a vector column configured. Refer to the Supabase Vector Columns Guide for setup.
- Trigger Setup: Configure the 'Notion - Page Added Trigger' node with your Notion database ID.
- Content Retrieval & Filtering: The 'Notion - Retrieve Page Content' and 'Filter Non-Text Content' nodes will automatically fetch and clean your page data.
- Content Summarization: The 'Summarize - Concatenate Notion's blocks content' node prepares your text for embedding.
- Embedding Generation: Connect your OpenAI API credentials to the 'Embeddings OpenAI' node.
- Data Preparation: Use the 'Create metadata and load content' node to add relevant metadata and specify your Supabase table name in the 'Supabase Vector Store' node.
- Content Chunking: The 'Token Splitter' node breaks down your content into manageable chunks for embedding.
- Supabase Storage: The 'Supabase Vector Store' node inserts your processed documents and their embeddings into your Supabase database.
Apps Used
Workflow JSON
{
"id": "a4b79281-7108-44a1-afc1-af7bd110f6e3",
"name": "Unlock Your Knowledge: Notion Pages to Vector Database with AI",
"nodes": 10,
"category": "DevOps",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: a4b79281-7108...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
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