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Build a RAG Pipeline in n8n: Query 3,000 Pages in 5 Seconds
Three weeks ago I needed a way to query a large document corpus without sending everything to an LLM every time. The answer was a RAG (Retrieval-Augmented Generation) pipeline — but I wanted to build it inside n8n, not a Python script that I'd have to maintain separately. Here's the architecture I l
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