AutomationFlows › AI & RAG › Upsert Huge Documents in a Vector Store with Supabase and Notion (embeddings…

Upsert Huge Documents in a Vector Store with Supabase and Notion (embeddings…

Original n8n title: Upsert Huge Documents in a Vector Store with Supabase and Notion (embeddings Open Ai)

ByMario @octionic✓ on n8n.io

This workflow adds the capability to build a RAG on living data. In this case Notion is used as a Knowledge Base. Whenever a page is updated, the embeddings get upserted in a Supabase Vector Store.

Chat trigger trigger★★★★★ complexityAI-powered34 nodesOpenAI EmbeddingsText Splitter Token SplitterChain Retrieval QaRetriever Vector StoreOpenAI ChatChat TriggerSupabaseNotion
AI & RAG Trigger: Chat trigger Nodes: 34 Complexity: ★★★★★ AI nodes: yes Added:

This workflow corresponds to n8n.io template #2568 — we link there as the canonical source.

This workflow follows the Chainretrievalqa → Retrievervectorstore recipe pattern — see all workflows that pair these two integrations.

The workflow JSON

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About this workflow

    
This workflow adds the capability to build a RAG on living data. In this case Notion is used as a Knowledge Base. Whenever a page is updated, the embeddings get upserted in a Supabase Vector Store.

    
Source: https://n8n.io/workflows/2568/ — original creator credit. Request a take-down →

    
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