RAGs

Building a RAG (short for Retrieval Augmented Generation) to “chat together with your data” is straightforward: install a well-liked LLM orchestrator like LangChain or LlamaIndex, turn your data into vectors, index those in a...

An LLM can handle general routing. Semantic search can handle private data higher. Which one would you choose?A single prompt cannot handle the whole lot, and a single data source will not be suitable...

GenAIA guide to Retrieval-Augmented Generation design selections.20 min read·15 hours agoConstructing Retrieval-Augmented Generation systems, or RAGs, is simple. With tools like LamaIndex or LangChain, you'll be able to get your RAG-based Large Language Model...