mirror of
https://github.com/denizsafak/abogen.git
synced 2026-09-20 11:40:57 +02:00
Artem Akymenko
0dc491e420
- EngineConfig.language: Language (was lang_code: str = 'a') - Engine owns _KOKORO_LANG_MAP, engine_language(), supported_languages() - Engine provides language_for_voice_id() for voice catalog - Plugins/kokoro/__init__.py calls engine_language() internally - create_pipeline(plugin_id, language=Language) — no kokoro codes - pipeline_factory.py clean of kokoro-specific code - Domain functions raise TypeError if non-enum passed - WebUI api.py: _parse_language() helper at API boundary - Voice catalog returns ISO codes (lang.value) - Constants: LANGUAGE_DESCRIPTIONS keyed by Language enum - All tests updated for Language enum - 1414 tests pass
77 lines
2.4 KiB
Python
77 lines
2.4 KiB
Python
"""Chunk processing utilities.
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Functions for grouping chunks, recording override usage, and selecting
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text for TTS synthesis.
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"""
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from __future__ import annotations
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from collections import defaultdict
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from typing import Any, Dict, Iterable, Mapping
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from abogen.domain.enums import Language
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from abogen.pronunciation_store import increment_usage
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def safe_int(value: Any, default: int = 0) -> int:
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try:
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return int(value)
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except (TypeError, ValueError):
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return default
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def group_chunks_by_chapter(chunks: Iterable[Dict[str, Any]]) -> Dict[int, List[Dict[str, Any]]]:
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grouped: Dict[int, List[Dict[str, Any]]] = defaultdict(list)
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for entry in chunks or []:
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if not isinstance(entry, dict):
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continue
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try:
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chapter_index = int(entry.get("chapter_index", 0))
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except (TypeError, ValueError):
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chapter_index = 0
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grouped[chapter_index].append(dict(entry))
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for chapter_index, items in grouped.items():
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items.sort(key=lambda payload: safe_int(payload.get("chunk_index")))
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return grouped
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def record_override_usage(
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job: Any,
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usage_counter: Mapping[str, int],
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token_map: Mapping[str, str],
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) -> None:
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if not usage_counter:
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return
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language = getattr(job, "language", Language.EN_US) or Language.EN_US
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for normalized, amount in usage_counter.items():
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if amount <= 0:
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continue
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token_value = token_map.get(normalized, normalized)
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try:
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increment_usage(language=language, token=token_value, amount=int(amount))
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except Exception: # pragma: no cover - defensive logging
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job.add_log(f"Failed to record usage for override {token_value}", level="warning")
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def chunk_text_for_tts(entry: Mapping[str, Any]) -> str:
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"""Choose the best source text for synthesis.
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We must prefer the raw chunk text (``text`` / ``original_text``) so
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manual/pronunciation overrides can match against the original tokens
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(e.g. censored words like ``Unfu*k``). ``normalized_text`` may have
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already been run through ``normalize_for_pipeline``, which can remove
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punctuation and prevent overrides from triggering.
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"""
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if not isinstance(entry, Mapping):
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return ""
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return str(
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entry.get("text")
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or entry.get("original_text")
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or entry.get("normalized_text")
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or ""
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).strip()
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