Workflow updated on 17/06/2024:

Added ‘Summarize’ node to avoid creating a row for each Notion content block in the Supabase table.

Store Notion’s Pages as Vector Documents into Supabase

This workflow automates the process of storing Notion pages as vector documents in a Supabase database with a vector column. The steps are as follows:

Notion Page Added Trigger:

Monitors a specified Notion database for newly added pages. You can create a specific Notion database where you copy the pages you want to store in Supabase.

Retrieve Page Content:

Fetches all block content from the newly added Notion page.

Filter Non-Text Content:

Excludes blocks of type “image” and “video” to focus on textual content.

Summarize Content:

Concatenates the Notion blocks content to create a single text for embedding.

Store in Supabase:

Stores the processed documents and their embeddings into a Supabase table with a vector column.

Generate Embeddings:

Utilizes OpenAI’s API to generate embeddings for the textual content.

Create Metadata and Load Content:

Loads the block content and creates associated metadata, such as page ID and block ID.

Split Content into Chunks:

Divides the text into smaller chunks for easier processing and embedding generation.