Retrieval-Augmented Generation (RAG) is an approach that allows large language models to leverage external knowledge sources by tightly integrating information retrieval and natural language generation capabilities. Let’s learn more about it!

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Retrieval-Augmented Generation (RAG) is an approach that integrates large language models with external knowledge sources for more accurate and substantive responses. It has various use cases and follows a multi-step retrieval and generation process.

Issue #56 - Retrieval-Augmented Generation