Your RAG agent is confidently unreliable because its data is stale. A great RAG agent isn't just about the chat; it's about the pipeline that feeds it. 🚀 We're revealing the complete guide to building an automated, no-code RAG pipeline.
We’ll talk about:
- A step-by-step guide to building an automated RAG data pipeline in n8n that syncs with Google Drive and Supabase.
- The 3-pipeline system (Create, Update, Delete) that ensures your vector database is a perfect mirror of your source files.
- The "Digital Recycling Bin" method for handling file deletions when Google Drive triggers don't support it.
- Why Metadata is the true "digital dog tag" and the non-negotiable key to managing, updating, and deleting your vectors.
- Plus, a "Smart Router" architecture for scaling your pipeline to handle multiple different file types (PDFs, DOCX, TXT) automatically.
Keywords: RAG Pipeline, n8n, Supabase, Google Drive, Data Pipeline, RAG (Retrieval-Axugmented Generation), Vector Database, No-Code AI, AI Agents, Metadata, Data Synchronization
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정보
- 프로그램
- 발행일2025년 10월 27일 오전 10:20 UTC
- 길이15분
- 등급전체 연령 사용가
