Document Chunking for RAG (Retrieval Augmented Generation)

It's an interesting topic i'm working on at the moment. Given the ones you shared, I figured out additional challenges. Especially for PDF and Office documents, it's really important to consider the original layout. You shouldn't split the text on a fixed word count based on the maximum length admitted by your embedding model. At preprocess.co we split documents considering sections, paragraphs, tables, images, lists, slides, and content semantics. The goal of a chunking method should be to generate text that increases the performance of a RAG not only to make it suitable for any text and file.