Roaming RAG offers a fresh take on Retrieval-Augmented Generation, letting LLMs navigate well-structured documents like a human—exploring outlines and diving into sections to find answers. Forget complex retrieval setups and vector databases; this streamlined approach delivers rich context and reliable answers with less hassle. It’s perfect for structured content like technical manuals, product guides, or the innovative llms.txt format designed to make websites LLM-friendly.
If your RAG application is serving documentation, then there might be an easy alternative. Rather than setting up a traditional RAG pipeline, put the LLM assistant to work. Let it navigate through the documentation and find the answers. I call this "Roaming" RAG, and in this post I’ll show you how it’s done.
via: https://arcturus-labs.com/blog/2024/11/21/roaming-rag–make-_the-model_-find-the-answers/