
Splits a String into a [String] of sentences with a learned segment-any-text (SaT) model. Robust to missing or unusual punctuation and language-agnostic across major scripts, it prepares text for per-sentence downstream processing such as retrieval or generation.
Split a transcript into sentences for per-sentence generation.
Split text and serialise the sentence list for logging.
threshold for fewer, longer sentences and lower it for more, shorter ones.
device is ``cpu``, which splits a typical message in tens of milliseconds, so no GPU is required. The SaT-3L-SM weights and the XLM-RoBERTa subword tokenizer they wrap are staged offline from platform files and loaded locally, so there is no runtime download and no HuggingFace token.
device is captured once at startup; changing it requires a redeploy. threshold and strip_whitespace are re-read every message.
Automated release