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Text Processing Module for PodXplainClone.
Handles text cleanup, chunking, and chunk-count estimation for Kokoro TTS.
"""
import re
from typing import List
MAX_CHUNK_CHARS = 420
SENTENCE_SPLIT = re.compile(r"(?<=[.!?])\s+(?=[\"'A-Z0-9])")
CLAUSE_SPLIT = re.compile(r"(?<=[,;:])\s+|\s+(?=(?:and|but|or|so|because)\b)", re.IGNORECASE)
SPACE_RE = re.compile(r"[ \t]+")
LINE_RE = re.compile(r"\n{3,}")
def normalize_text(text: str) -> str:
"""Normalize whitespace while preserving paragraph boundaries."""
text = text.replace("\r\n", "\n").replace("\r", "\n")
text = SPACE_RE.sub(" ", text)
text = LINE_RE.sub("\n\n", text)
return text.strip()
def chunk_text(text: str, max_chars: int = MAX_CHUNK_CHARS) -> List[str]:
"""Split text into TTS-sized chunks, preferring sentence and clause boundaries."""
text = normalize_text(text)
if not text:
return []
if len(text) <= max_chars:
return [text]
chunks = []
sentences = SENTENCE_SPLIT.split(text)
current_chunk = ""
for sentence in sentences:
sentence = sentence.strip()
if not sentence:
continue
if len(current_chunk) + len(sentence) + 1 <= max_chars:
current_chunk = f"{current_chunk} {sentence}".strip()
continue
if current_chunk:
chunks.append(current_chunk)
current_chunk = ""
if len(sentence) <= max_chars:
current_chunk = sentence
else:
clause_chunks = _split_at_clauses(sentence, max_chars)
chunks.extend(clause_chunks[:-1])
current_chunk = clause_chunks[-1] if clause_chunks else ""
if current_chunk:
chunks.append(current_chunk)
return chunks
def _split_at_clauses(text: str, max_chars: int) -> List[str]:
"""Split a long sentence at clause boundaries, then word boundaries."""
clauses = CLAUSE_SPLIT.split(text)
chunks = []
current = ""
for clause in clauses:
clause = clause.strip()
if not clause:
continue
if len(current) + len(clause) + 1 <= max_chars:
current = f"{current} {clause}".strip()
continue
if current:
chunks.append(current)
if len(clause) <= max_chars:
current = clause
else:
hard_chunks = _hard_split(clause, max_chars)
chunks.extend(hard_chunks[:-1])
current = hard_chunks[-1] if hard_chunks else ""
if current:
chunks.append(current)
return chunks
def _hard_split(text: str, max_chars: int) -> List[str]:
"""Last resort: split text at word boundaries."""
words = text.split()
chunks = []
current = ""
for word in words:
if len(current) + len(word) + 1 <= max_chars:
current = f"{current} {word}".strip()
continue
if current:
chunks.append(current)
if len(word) > max_chars:
chunks.extend(word[i:i + max_chars] for i in range(0, len(word), max_chars))
current = ""
else:
current = word
if current:
chunks.append(current)
return chunks
def estimate_total_chunks(segments: list, max_chars: int = MAX_CHUNK_CHARS) -> int:
"""Estimate how many TTS chunks will be generated."""
return sum(len(chunk_text(text, max_chars)) for _speaker_id, text in segments)
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