Chonkie tackles messy medical chunking

Chunking is still more of a workflow problem than a model problem: you usually need a parser, a strategy per document type, and an evaluation loop.

• –Chonkie is positioned as a lightweight chunking library for RAG, not a one-click app that solves every corpus.
• –LateChunker is interesting for long academic text because it uses full-document context before splitting, which can preserve meaning better than naive fixed-size chunks.
• –For medical articles, structure-aware extraction matters first: headings, abstracts, methods, tables, references, and OCR cleanup all change chunk quality.
• –The right answer is usually to benchmark a few strategies on retrieval quality, not just eyeball chunk boundaries.
• –If the corpus is inconsistent, metadata-rich chunks and document-aware preprocessing will matter as much as the splitter itself.