Implementing RAG in Multimodal Architectures for Image Generation

RAG (Retrieval-Augmented Generation) has become a mainstream method for enhancing responses from large language models. In recent years, multimodal LLM has been developing increasingly well, and similar approaches in multimodal LLM application scenarios and implementation methods are worth exploring. This presentation will discuss the implementation of multimodal LLM in the RAG process, and share practical applications using image generation as a case study.