RAG-Anything: All-in-One RAG Framework

Zirui Guo, Xubin Ren, Lingrui Xu +2

Retrieval-Augmented Generation (RAG) has emerged as a fundamental paradigm for expanding Large Language Models beyond their static training limitations. However, a critical misalig…