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Library / RAG & Knowledge Bases

RAG & Knowledge Bases

Store Notion Pages in a Vector Store (768 Dimensions)

When a page is added in Notion, it retrieves the content, splits it into tokens and stores embeddings in a 768-dimension vector store.

What it does

# Prod: Notion to Vector Store - Dimension 768 ## Overview Automated workflow: Prod: Notion to Vector Store - Dimension 768. This workflow processes data and performs automated tasks. ## Workflow Details - Total Nodes: 10 - Node Types: 10 - Error Handling: ✅ Implemented - Security: ✅ Hardened (no sensitive data) - Documentation: ✅ Complete ## Node Breakdown - Token Splitter: textSplitterTokenSplitter - Notion - Page Added Trigger: notionTrigger - Notion - Retrieve Page Content: notion - Filter Non-Text Content: filter - Summarize - Concatenate Notion's blocks content: summarize - Create metadata and load content: documentDefaultDataLoader - Embeddings Google Gemini: embeddingsGoogleGemini - Pinecone Vector Store: vectorStorePinecone - Workflow Documentation: stickyNote - Error Handler for 1f93c3e6: stopAndError ## Usage Instructions 1. Configure Credentials: Set up all required API keys and credentials 2. Update Variables: Replace any placeholder values with actual data 3. Test Workflow: Run in test mode to verify functionality 4. Deploy: Activate the workflow for production use ## Security Notes - All sensitive data has been removed or replaced with placeholders - Error handling is implemented for reliability - Follow security best practices when configuring credentials ## Troubleshooting - Check error logs if workflow fails - Verify all credentials are properly configured - Ensure all required services are accessible

The steps

  1. Token Splitter
  2. Notion - Page Added Trigger
  3. Notion - Retrieve Page Content
  4. Filter Non-Text Content
  5. Summarize - Concatenate Notion's blocks content
  6. Create metadata and load content
  7. Embeddings Google Gemini
  8. Pinecone Vector Store
  9. Error Handler for 1f93c3e6
  10. Error Handler

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