Applications in LLM Models and RAG Method

Large language models (LLMs) demonstrated impressive capabilities in natural language processing tasks. They depend heavily though on pre-trained knowledge, they are not always able to access and use up-to-date information. Retrieval-augmented generation (RAG) helps to overcome this limitation by integrating external knowledge sources into the LLM's generation process. This chapter provides a comprehensive overview of RAG, exploring its underlying mechanisms and applications.