Seamlessly Embed Notion Content into Your Vector Database
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Automate the process of extracting content from Notion, converting it into embeddings, and storing it in a Pinecone vector database. This workflow ensures your Notion data is readily available for AI-powered applications and intelligent search.
About This Workflow
This n8n workflow streamlines the ingestion of your Notion knowledge base into a powerful vector store, specifically Pinecone. It triggers on new page additions in a designated Notion database, retrieves the page content, filters out non-textual elements, and intelligently concatenates the relevant text. Utilizing Google Gemini for embeddings, it then creates metadata (like page ID, creation time, and title) before efficiently loading the processed data and its embeddings into your Pinecone index. This creates a robust foundation for advanced search, semantic understanding, and AI-driven applications leveraging your Notion content with a specific embedding dimension of 768.
Key Features
- Automated Notion Content Ingestion: Automatically captures new or updated content from your Notion pages.
- Intelligent Text Extraction & Filtering: Processes page content, removing images and videos to focus on textual data.
- Smart Content Summarization: Concatenates and structures content from multiple Notion blocks for efficient processing.
- Metadata Enrichment: Attaches crucial metadata like page ID, creation time, and title to each data point.
- Google Gemini Embeddings: Leverages state-of-the-art embeddings for high-quality semantic representation.
- Pinecone Vector Store Integration: Seamlessly loads data and embeddings into a Pinecone index for scalable search and retrieval.
How To Use
- Configure Notion Trigger: Connect your Notion account and specify the
databaseIdfor the Notion database you want to monitor. - Retrieve Page Content: The workflow automatically fetches the content of newly added pages.
- Filter Content: Configure the filter node to exclude non-textual content types (e.g., images, videos).
- Summarize Content: Use the Summarize node to concatenate the relevant text content from Notion blocks.
- Generate Embeddings: Connect your Google Cloud credentials and select the desired embedding model (e.g.,
models/text-embedding-004). - Create Metadata: Define custom metadata fields (page ID, creation time, page title) to associate with your embeddings.
- Configure Pinecone Vector Store: Connect your Pinecone API credentials and specify the target
pineconeIndex(e.g., 'notion-pages'). Ensure the index is configured for the correct dimension (768). - Activate Workflow: Ensure the workflow is active to begin automated data ingestion.
Apps Used
Workflow JSON
{
"id": "263d43a8-fcaf-4e2c-8364-d6847d065000",
"name": "Seamlessly Embed Notion Content into Your Vector Database",
"nodes": 27,
"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: 263d43a8-fcaf...
About the Author
Crypto_Watcher
Web3 Developer
Automated trading bots and blockchain monitoring workflows.
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