n8n intermediate course Module 2: Embeddings & Vector DBs in n8n (Supabase + Gemini)
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Stop keyword search—build semantic search. In this module, we turn text into embeddings and store them in a vector database so your AI Agent can answer with meaning, not just matching words. 🚀
What you’ll learn:
- Embeddings 101: how vectors capture meaning
- Supabase + pgvector setup (copy‑paste SQL included)
- n8n pipeline: Google Drive ➜ Gemini embeddings ➜ Supabase
- Query via an AI Agent using semantic search/RAG
Perfect for automation builders who want fast, accurate answers from their knowledge base. Works with OpenAI or Gemini embedding models—set vector size to your model’s dimensions.
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#n8n #Supabase #pgvector #VectorDatabase #Embeddings #RAG #SemanticSearch #AIWorkflow #GeminiAI #Automation
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