Breaking up is hard to do: Chunking in RAG applications

Chunking is an important aspect in retrieval-augmented generation (RAG) systems. The size of the chunked data affects the specificity and context of the information retrieved. Common chunking strategies include fixed sizes, random chunk sizes, sliding windows, context-aware chunking, and adaptive chunking.