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Store Notion's Pages as Vector Documents into Supabase with OpenAI

Configured with Document Default Data Loader, Embeddings Open Ai, Filter, Notion, and additional nodes. Review the connections and setup before adapting this template.

Download workflow JSONView files on GitHub ↗8 nodes · MIT
Workflow preview
AI & modelsEmbeddings OpenAIEmbeddings Open AiTransformToken SplitterText Splitter Token Spli…TriggerNotion - Page AddedTriggerNotion TriggerIntegrationNotion - Retrieve PageContentNotionRoutingFilter Non-Text ContentFilterTransformSummarize - ConcatenateNotion's blocks contentSummarizeFiles / mediaCreate metadata andload contentDocument Default Data Lo…Data storeSupabase Vector StoreVector Store Supabase

Node categories in this workflow

  • AI & models
  • Transform
  • Trigger
  • Integration
  • Routing
  • Files / media
  • Data store

Icons describe general node roles, inferred from node types. Inspect the parameters for the configured action.

Drag to pan; use + and − to zoom. Reconstructed from the exported node positions; nothing runs here. Dashed lines represent non-main connections. Full node names and notes appear below.

How it works

The exported workflow contains the following configured nodes. Their connections are shown above; inspect the JSON for the complete logic, expressions, and external actions.

Workflow node names, types, and operations
NodeCategoryTypeOperation
Embeddings OpenAIAI & modelsEmbeddings Open AiSee node parameters
Token SplitterTransformText Splitter Token SplitterSee node parameters
Notion - Page Added TriggerTriggerNotion TriggerSee node parameters
Notion - Retrieve Page ContentIntegrationNotionblock / getAll
Filter Non-Text ContentRoutingFilterSee node parameters
Summarize - Concatenate Notion's blocks contentTransformSummarizeSee node parameters
Create metadata and load contentFiles / mediaDocument Default Data LoaderSee node parameters
Supabase Vector StoreData storeVector Store SupabaseSee node parameters

Setup

  1. Download the JSON and import it into an isolated n8n instance. Leave the workflow inactive.
  2. Connect your own credentials through n8n’s credential store. Replace REPLACE_WITH_* values with your resource identifiers.
  3. Inspect API destinations, Code nodes, database queries, file paths, and outbound actions.
  4. Run with synthetic data and harmless destinations. Enable triggers only after checking the actual outputs.

Requirements

An n8n instance with the listed node types and compatible versions. Service-connected workflows may require accounts, credentials, or paid APIs.

Credential types declared in the source

None declared. HTTP requests and Code nodes may still need configuration.

Workflow notes

Store Notion's Pages as Vector Documents into Supabase

Store Notion's Pages as Vector Documents into Supabase

This workflow assumes you have a Supabase project with a table that has a vector column. If you don't have it, follow the instructions here: Supabase Vector Columns Guide

Workflow Description

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:

  1. 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.
    • Node: Page Added in Notion Database

  2. Retrieve Page Content:

    • Fetches all block content from the newly added Notion page.
    • Node: Get Blocks Content

  3. Filter Non-Text Content:

    • Excludes blocks of type "image" and "video" to focus on textual content.
    • Node: Filter - Exclude Media Content

  4. Summarize Content:

    • Concatenates the Notion blocks content to create a single text for embedding.
    • Node: Summarize - Concatenate Notion's blocks content

  5. Store in Supabase:

    • Stores the processed documents and their embeddings into a Supabase table with a vector column.
    • Node: Store Documents in Supabase

  6. Generate Embeddings:

    • Utilizes OpenAI's API to generate embeddings for the textual content.
    • Node: Generate Text Embeddings

  7. Create Metadata and Load Content:

    • Loads the block content and creates associated metadata, such as page ID and block ID.
    • Node: Load Block Content & Create Metadata

  8. Split Content into Chunks:

    • Divides the text into smaller chunks for easier processing and embedding generation.
    • Node: Token Splitter
Store Notion's Pages as Vector Documents into Supabase with OpenAI

Store Notion's Pages as Vector Documents into Supabase with OpenAI

Purpose and structure

This folder contains the Store Notion's Pages as Vector Documents into Supabase with OpenAI workflow. Its executable nodes use documentDefaultDataLoader, embeddingsOpenAi, filter, notion, notionTrigger, summarize, textSplitterTokenSplitter, vectorStoreSupabase. The table and connection map below are derived from the JSON, not an inferred guarantee of behavior.

Setup

Import inactive. Configure your own credentials and replace REPLACE_WITH_* values. Review external destinations and Code nodes before running.

Entry points

Notion - Page Added Trigger

Verification

Sanitized source candidate; not runtime-tested. This overview is generated from node metadata. Read the folder README for the connection map, credential types, and license.

Attribution

https://github.com/Zie619/n8n-workflows/blob/94007c1445d9258a7da116646b79473e7c7c3282/workflows/Filter/1414_Filter_Summarize_Automation_Triggered.json MIT; preserve source notices.

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