The term “RAG” is used a lot in today’s technical landscape, but what does it actually mean? Here are a few definitions from various sources:
“Retrieval-Augmented Generation (RAG) is the process of optimizing the output of a large language model, so it references an authoritative knowledge base outside of its training data sources before generating a response.” — Amazon Web Services “Retrieval-augmented generation (RAG) is a technique for enhancing the accuracy and reliability of generative ...
Read it: Implementing RAG: How to Write a Graph Retrieval Query in LangChain