o 0i_@sdZddlmZddlZddlZddlZddlZddlmZe e Z dZ d'd(d d Z ed)d*ddZd+ddZd,ddZd-ddZd.d!d"Zd/d0d%d&ZdS)1zUtility functions for Supertonic TTS. This module provides various helper functions for text processing, file operations, and timing operations used throughout the Supertonic TTS package. ) annotationsN)contextmanagerz(?sz.validate_voice_style_format..FdimsdataT)all)r, required_keysr/rr0rvalidate_voice_style_formats r6, list[str]c Cs|dkr td|dddtd|D}g}|D]L}|}|s&qtt|}d}|D]+}|}|s9q0t|t|d|krP||rJd nd|7}q0|rY|||}q0|ri|ri||q|S) az Split text into chunks by paragraphs and sentences. This function intelligently splits long text into smaller chunks suitable for TTS processing, respecting paragraph and sentence boundaries. Args: text: Input text to chunk max_len: Maximum length of each chunk in characters (default: 300) Returns: List of text chunks Example: ```python text = "This is a long paragraph. It has multiple sentences. " * 10 chunks = chunk_text(text, max_len=100) for chunk in chunks: print(f"Chunk ({len(chunk)} chars): {chunk[:50]}...") ``` z!max_len must be at least 10, got z4. Very small chunks may produce poor quality speech.cSsg|] }|r|qSr)strip)r.prrr szchunk_text..z\n\s*\n+ ) ValueErrorr splitr:_COMMON_ABBREVIATIONS_PATTERNlenappend) rrZ paragraphschunksZ paragraphZ sentencesZ current_chunkZsentenceZsentence_strippedrrr chunk_texts2   rF)r)rrrrr r)T)rrrr)rrr r)r#rr$rr r)r&rr r)r,r-r r)r7)rrrrr r8)__doc__ __future__rloggingr(r r contextlibr getLogger__name__rrBrrr"r%r+r6rFrrrrs$