This Hybrid RAG Trick Makes Your AI Agents More Reliable (n8n) скачать в хорошем качестве

This Hybrid RAG Trick Makes Your AI Agents More Reliable (n8n)

👉 Get all of our n8n workflows and learn how to customize them https://www.theaiautomators.com/?utm_... Tired of vague or irrelevant answers from your AI agents? The problem might not be your LLM—it’s your search strategy. In this video, I’ll show you how to upgrade your RAG setup with Hybrid Search using both semantic (vector) and keyword (sparse) search. We’ll walk through real working implementations of Hybrid RAG using Supabase and Pinecone, and I’ll show you how to integrate them directly into your N8N AI agent workflows. This approach solves a major pain point in RAG systems: semantic search struggles with exact terms like product codes, acronyms, or technical specs. Hybrid search fixes that—combining the meaning-matching power of vectors with the precision of keyword search. 🔗 Related Links & Resources: Check out my n8n RAG Masterclass:    • n8n RAG Masterclass - Build AI Agents + Sy...   n8n: http://theaiautomators.com/go/n8n Supabase: https://supabase.com/ Supabase Hybrid Search Docs: https://supabase.com/docs/guides/ai/h... Pinecone: https://www.pinecone.io/ Pinecone Hybrid Search Setup: https://docs.pinecone.io/docs/hybrid-... 💡 What You’ll Learn: Why vector search fails with specific queries How to implement hybrid search using Supabase’s tsvector and embeddings How to set up Pinecone’s hybrid search with dense + sparse vectors Don’t forget to like, subscribe, and hit the bell for more AI automation tutorials! 📌 Timestamps 00:00 Hybrid RAG 06:19 Supabase Build 18:41 Demo on Supabase 21:34 Pinecone Workflow