Overlapping text chunker for RAG pipelines

crg@crg.eti.br (Cesar Gimenes) — Sat, 06 Jun 2026 11:57:59 -0300

In a RAG (Retrieval-Augmented Generation) pipeline the first step is almost always the same: take a large text and break it into pieces before vectorizing. The pieces can’t be too big, because the model has a context limit, nor too small, because then the embedding loses semantics. And neighbors need to overlap, otherwise an answer that lands right on the boundary gets squeezed between two chunks and the retriever misses.

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Overlapping text chunker for RAG pipelines