GraphRAG?

Retrieval-Augmented GenerationFetching relevant context from an external data source as additional context to inform a language model's response. (RAG) is an approach that enhances the responses of LLMsA model trained on text to predict the next token, and so to generate language. by providing them with relevant, up-to-date information retrieved from external sources.

RAG helps generate more accurate and tailored answers, especially when the required information is not present in the model’s training data.