this post was submitted on 03 Aug 2025
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[–] DarkDarkHouse@lemmy.sdf.org 3 points 3 days ago

Retrieval-augmented generation (RAG) is a technique that enables large language models (LLMs) to retrieve and incorporate new information. With RAG, LLMs do not respond to user queries until they refer to a specified set of documents. These documents supplement information from the LLM's pre-existing training data. This allows LLMs to use domain-specific and/or updated information that is not available in the training data. For example, this helps LLM-based chatbots access internal company data or generate responses based on authoritative sources.

From Retrieval-augmented generation.

Specifically here, I imagine the idea is to talk to the chatbot about what's in your documents.