LLMs (Large Language Models) are all the rage, but they have a major flaw: they hallucinate. That means they make things up as they go along. Not ideal when you’re trying to build a chatbot that answers questions strictly from your own documentation. Enter RAG (Retrieval-Augmented Generation), a game-changing technique that fixes this problem. In this post, I’ll break down how to chunk a PDF, create embeddings, and query them in n8n to build a chatbot that answers from your own knowledge base. Get the full tutorial on building a Vector Store with Pinecone and n8n.
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