Watch on YouTube: [RAG Explained – n8n Chatbot Demo with Sources](https://youtu.be/Ox26-mRSsvg)
In this video, I explain what Retrieval Augmented Generation (RAG) is and show you a live demo of a RAG chatbot app in action. You’ll see how a chatbot can answer questions directly from your documents, with accurate references to the source files. What you’ll learn:
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Simple explanation of RAG (easy to understand)
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Why RAG improves accuracy, recency, and control vs. using LLMs alone
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How documents are split into chunks, embedded, and stored in a vector database
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Live demo: asking questions with and without RAG
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Example: AI usage report & HR policy Q&A with cited sources
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Best practices for building RAG pipelines (chunking, retrieval, prompting, evaluation)
This is perfect if you want to understand how RAG works and how to apply it in your own AI chatbot projects.
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n8n JSON workflow in the demo video: https://s3.ap-southeast-1.amazonaws.c…
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PDF presentation: https://s3.ap-southeast-1.amazonaws.c…
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