ALucek/RAG-Overview

An intuitive approach towards understanding how Retrieval Augmented Generation (RAG) systems work, for the curious yet daunted reader

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This resource helps anyone curious about how Retrieval Augmented Generation (RAG) systems function, especially if you've felt intimidated by the technical details. It explains how providing relevant, current, or specialized information alongside a question can dramatically improve the accuracy of large language model responses. The target audience is non-technical professionals who want to grasp the core concepts of RAG without diving into code.

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Use this if you want an intuitive, high-level understanding of what Retrieval Augmented Generation (RAG) is and why it's crucial for getting accurate, domain-specific answers from AI.

Not ideal if you are a developer looking for code examples or implementation details to build your own RAG system.

AI-explainability LLM-understanding business-intelligence knowledge-management AI-strategy

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Jupyter Notebook

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