diff options
Diffstat (limited to 'app/converter')
| -rw-r--r-- | app/converter/chunking.py | 400 | ||||
| -rw-r--r-- | app/converter/config.py | 7 | ||||
| -rw-r--r-- | app/converter/converter.py | 36 |
3 files changed, 412 insertions, 31 deletions
diff --git a/app/converter/chunking.py b/app/converter/chunking.py index 9ef6a5d..0ffaa21 100644 --- a/app/converter/chunking.py +++ b/app/converter/chunking.py @@ -8,32 +8,346 @@ from . import config logger = logging.getLogger(__name__) +# Smart-chunking tuning, as fractions of the word limit (not exposed as +# settings): once a smart chunk crosses the target it ends at the next +# clean boundary, so most chunks land between the target and the limit +# with some headroom under the configured size. When the next sentence +# will not fit the running chunk, the break retreats to the previous +# boundary that is clean and at least the floor, so a quotation is not +# severed when a later clean boundary exists nearby. +_TARGET_RATIO = 0.85 +_FLOOR_RATIO = 0.7 +# A single token with no whitespace cannot be broken at a word +# boundary; if such a token runs longer than this many characters per +# allowed word it is sliced at the hard character cap (a last-resort +# bound for punctuation-free input such as some CJK text or damage from +# text extraction). +_MAX_CHARS_PER_WORD = 8 -def split_into_chunks(text: str, max_words: Optional[int] = None) -> List[str]: - """Split text into chunks of at most ``max_words`` words. +_ABBREVIATIONS = frozenset( + "mr mrs ms miss dr prof rev hon pres gov sen rep capt lt col gen " + "sgt maj cpl pvt jr sr st mt vs etc eg ie aka fig figs no nos vol " + "vols ch pp p pg dept univ ave blvd rd inc ltd co corp bros apt " + "ste est approx min sec hrs msg mme mlle".split()) - ``max_words`` defaults to ``config.CHUNK_SIZE`` (read at call time). - There is no ceiling beyond that setting, but note that the TTS - servers silently truncate audio when a single generation runs too - long without reporting an error, so very large values are at your - own risk (see CHUNK_SIZE in app/converter/config.py). +_EVENT = re.compile( + r"(?P<end>[.!?…。！？][\"'”’»)}\]]*)" + r"|(?P<para>\n[ \t]*\n)" + r"|(?P<open>[“«])" + r"|(?P<close>[”»])" + r"|(?P<straight>\")") + +_PARA_AFTER = re.compile(r"[ \t\r]*\n[ \t]*\n") + +# Scripts whose characters are not whitespace-delimited: count each one +# as a word so a long CJK passage is bounded like English text of the +# same spoken length instead of reading as one giant "word". +_NON_SPACED_RUN = re.compile(r"[\u3040-\u30ff\u3400-\u4dbf\u4e00-\u9fff" + r"\uf900-\ufaff]") + + +class _Unit: + """A sentence-sized piece of text plus its packing metadata. - Splits on sentence boundaries. Sentences longer than the limit are - split further at clause punctuation (which is kept attached for TTS - prosody). Clause splits only happen at whitespace after punctuation, - so tokens like "1,000,000" or "12:30" are never broken apart. A piece - with no usable punctuation split point longer than the limit is split - at word boundaries as a last resort: individual tokens stay intact, - but whitespace between them is normalized. + ``in_quote_end`` is the quotation state after the unit's terminator + (double-quote open marks and closes are tracked; apostrophes do not + count as quotes), and ``para_after`` marks a unit that a blank line + follows. """ - if max_words is None: - max_words = config.CHUNK_SIZE - if max_words < 1: - max_words = 1 - if not text.strip(): - return [] + __slots__ = ("text", "words", "para_after", "in_quote_end") + + def __init__(self, text: str, words: int, para_after: bool, + in_quote_end: bool): + self.text = text + self.words = words + self.para_after = para_after + self.in_quote_end = in_quote_end + + +def _count_words(text: str) -> int: + """Words in TEXT; non-spaced-script characters each count as one.""" + return len(text.split()) + len(_NON_SPACED_RUN.findall(text)) + + +def _is_abbreviation(text: str, dot: int) -> bool: + """True when the '.' before which a sentence split is being + considered belongs to an abbreviation or a name initial (Mr. St. + U.S. J.), where a break would fall mid-sentence.""" + start = dot + while start > 0 and (text[start - 1].isalnum() + or text[start - 1] in ".-'’"): + start -= 1 + token = text[start:dot] + if not token: + return False + tail = token.split(".")[-1] + if len(tail) == 1 and tail.isalpha(): + return True + return token.lower() in _ABBREVIATIONS + + +def _sentence_continues(text: str, end: int, attach: bool) -> bool: + """True when the text after a terminator belongs to the same unit. + + Only a closing quote or an ellipsis can pull a lowercase word into + the unit (dialogue tags: ``“Come here!” she said.``); a plain + period always ends the sentence, whatever follows. + """ + match = re.compile(r"\S").search(text, end) + if match is None: + return False + return attach and match.group().islower() + + +def _scan_units(text: str) -> List[_Unit]: + """Split TEXT into sentence units, tracking quotes and paragraphs. + + Splits at sentence terminators (.!?…) plus any closing quotes or + brackets that trail them, suppressing false boundaries for + abbreviations, initials, and lowercase continuations. Blank lines + close a paragraph (and reset the quotation state, so one unclosed + quote cannot silence clean boundaries for the rest of a book). + Non-whitespace content is preserved; only whitespace between + boundaries may be normalized. + """ + units: List[_Unit] = [] + seg_start = 0 + in_quote = False + depth = 0 + + def emit(end: int, para_after: bool) -> None: + nonlocal seg_start + segment = text[seg_start:end] + seg_start = end + if not segment.strip(): + return + units.append(_Unit(segment, _count_words(segment), para_after, + in_quote or depth > 0)) + + for match in _EVENT.finditer(text): + kind = match.lastgroup + if kind == "end": + run = match.group() + for ch in run[1:]: + if ch == '"': + in_quote = not in_quote + elif ch in "”»": + depth = max(0, depth - 1) + end = match.end() + nxt = text[end:end + 1] + if nxt and not nxt.isspace() \ + and not _NON_SPACED_RUN.match(nxt): + continue # glued punctuation: "3.14" is not a boundary + if (run[0] == "." and _is_abbreviation(text, match.start())) \ + or _sentence_continues(text, end, len(run) > 1 + or run[0] == "…"): + continue + emit(end, _PARA_AFTER.match(text, end) is not None) + elif kind == "para": + emit(match.start(), True) + in_quote = False + depth = 0 + elif kind == "open": + depth += 1 + elif kind == "close": + depth = max(0, depth - 1) + elif kind == "straight": + in_quote = not in_quote + + emit(len(text), False) + return units + + +def _join(units: List[_Unit]) -> str: + """Join units into one chunk, keeping paragraph breaks inside it.""" + parts: List[str] = [] + previous = None + for unit in units: + text = unit.text.strip() + if not text: + continue + if parts: + parts.append("\n\n" if previous.para_after else " ") + parts.append(text) + previous = unit + return "".join(parts) + + +def _retreat_point(cur: List[_Unit], floor: int) -> int: + """Index in CUR to break at when the next unit will not fit. + + Picks the largest prefix of at least FLOOR words that ends outside + a quotation; failing that, the largest prefix of at least FLOOR + words that ends a paragraph; failing both, the whole prefix (the + chunk keeps as much as fits and carries the open quotation into the + next chunk). + """ + best_clean = 0 + best_para = 0 + words = 0 + for k, unit in enumerate(cur, 1): + words += unit.words + if words < floor: + continue + if not unit.in_quote_end: + best_clean = k + elif unit.para_after: + best_para = k + return best_clean or best_para or len(cur) + + +def _split_oversized(text: str, max_words: int) -> List[str]: + """Break a sentence longer than the limit into packable pieces. + + First at clause punctuation (kept attached for TTS prosody, and + never at commas without whitespace so tokens like "1,000,000" and + "12:30" survive), then at word boundaries. A token with no + whitespace at all is sliced at the hard character cap so a + punctuation-free run cannot exceed the bound. + """ + parts = re.split(r"(?:(?<=[,;:])\s+|(?<=[，、；：]))", text) + pieces: List[str] = [] + cap = max_words * _MAX_CHARS_PER_WORD + for part in parts: + part = part.strip() + if not part: + continue + if len(part) <= cap and _count_words(part) <= max_words: + pieces.append(part) + continue + pieces.extend(_hard_slices(part, max_words, cap)) + return pieces + + +def _hard_slices(text: str, max_words: int, cap: int) -> List[str]: + """Slice TEXT at word boundaries, then at CAP characters when a + single token has no whitespace to break at. Buffers never exceed + the word limit or the character cap, so every piece is packable.""" + pieces: List[str] = [] + buf: List[str] = [] + buf_words = 0 + buf_chars = 0 + for word in text.split(): + if len(word) > cap: + if buf: + pieces.append(" ".join(buf)) + buf, buf_words, buf_chars = [], 0, 0 + for start in range(0, len(word), cap): + pieces.append(word[start:start + cap]) + continue + words = _count_words(word) + if buf and buf_words + words <= max_words \ + and buf_chars + 1 + len(word) <= cap: + buf.append(word) + buf_words += words + buf_chars += 1 + len(word) + else: + if buf: + pieces.append(" ".join(buf)) + buf, buf_words, buf_chars = [word], words, len(word) + if buf: + pieces.append(" ".join(buf)) + return pieces + + +def _joined_chars(units: List[_Unit]) -> int: + """The character length of the text _join would produce.""" + total = 0 + previous = None + for unit in units: + text = unit.text.strip() + if not text: + continue + if previous is not None: + total += 2 if previous.para_after else 1 + total += len(text) + previous = unit + return total + +def _split_smart(text: str, max_words: int) -> List[str]: + """Smart strategy: fill chunks up to MAX_WORDS at sentence + boundaries, end them at the target once a quotation has closed or + a paragraph ends, and retreat cleanly instead of breaking quotes + when the next sentence does not fit. Every chunk also respects the + hard character cap, so punctuation-free or non-spaced input stays + bounded.""" + target = max(1, round(max_words * _TARGET_RATIO)) + floor = max(1, round(max_words * _FLOOR_RATIO)) + char_cap = max_words * _MAX_CHARS_PER_WORD + chunks: List[str] = [] + cur: List[_Unit] = [] + cur_words = 0 + cur_chars = 0 + + def flush() -> None: + nonlocal cur, cur_words, cur_chars + if cur: + chunks.append(_join(cur)) + cur, cur_words, cur_chars = [], 0, 0 + + for unit in _scan_units(text): + if cur and cur_words >= target \ + and (not cur[-1].in_quote_end or cur[-1].para_after): + flush() + if unit.words <= max_words \ + and len(unit.text.strip()) <= char_cap \ + and _joined_chars(cur + [unit]) <= char_cap: + if cur_words + unit.words <= max_words: + cur.append(unit) + cur_words += unit.words + cur_chars = _joined_chars(cur) + continue + # The sentence does not fit: break earlier if a clean + # boundary keeps the chunk above the floor. + point = _retreat_point(cur, floor) + if point < len(cur): + chunks.append(_join(cur[:point])) + cur = cur[point:] + cur_words = sum(u.words for u in cur) + cur_chars = _joined_chars(cur) + if cur_words + unit.words <= max_words: + cur.append(unit) + cur_words += unit.words + cur_chars = _joined_chars(cur) + continue + flush() + cur.append(unit) + cur_words = unit.words + cur_chars = _joined_chars(cur) + continue + # One piece exceeds the limit itself: send its pieces out + # packed as tightly as the pieces allow. + flush() + for piece_text in _split_oversized(unit.text, max_words): + if _count_words(piece_text) > max_words \ + or len(piece_text) > char_cap: + # A character-sliced piece of degenerate input: its own + # chunk (already at the hard cap). + flush() + chunks.append(piece_text) + continue + piece = _Unit(piece_text, _count_words(piece_text), False, False) + if cur and cur_words + piece.words <= max_words \ + and cur_chars + 1 + len(piece_text) <= char_cap: + cur.append(piece) + cur_words += piece.words + cur_chars += 1 + len(piece_text) + continue + flush() + cur.append(piece) + cur_words = piece.words + cur_chars = len(piece_text) + flush() + return [chunk for chunk in chunks if chunk.strip()] + + +def _split_legacy(text: str, max_words: int) -> List[str]: + """The pre-smart splitter, kept intact for the Smart chunking=off + setting. Chunks pack whole sentences up to MAX_WORDS; sentences + longer than the limit split at clause punctuation, then at word + boundaries.""" sentences = re.split(r"(?<=[.!?])\s+", text) chunks = [] current_chunk = "" @@ -89,3 +403,49 @@ def split_into_chunks(text: str, max_words: Optional[int] = None) -> List[str]: chunks.append(current_chunk.strip()) return [chunk for chunk in chunks if chunk.strip()] + + +def split_into_chunks(text: str, max_words: Optional[int] = None, + smart: Optional[bool] = None) -> List[str]: + """Split text into chunks of at most ``max_words`` words. + + ``max_words`` defaults to ``config.CHUNK_SIZE`` (read at call time). + There is no ceiling beyond that setting, but note that the TTS + servers silently truncate audio when a single generation runs too + long without reporting an error, so very large values are at your + own risk (see CHUNK_SIZE in app/converter/config.py). + + With smart chunking on (``config.SMART_CHUNKING``, the default), a + chunk crossing the target (~85% of the limit) ends at the next + sentence end outside a quotation or at a paragraph break, so most + requests stop at natural boundaries instead of pressing against the + limit. When the next sentence will not fit, the break retreats to + the last boundary that ends outside a quotation (never smaller than + ~70% of the limit), so short quotations stay in one request when + possible; very long or unclosed quotes still split, carrying their + open state into the next chunk. Malformed punctuation never grows a + chunk beyond the limit: every break consumes text, and input without + sentence punctuation or whitespace (some CJK text, extraction + damage) falls back to clause punctuation, then word boundaries, + then a hard character cap. Content is preserved: no closing quote + or punctuation is ever invented or dropped. + + Both strategies split on sentence boundaries. Sentences longer than + the limit are split further at clause punctuation (which is kept + attached for TTS prosody). Clause splits only happen at whitespace + after punctuation, so tokens like "1,000,000" or "12:30" are never + broken apart. + """ + if max_words is None: + max_words = config.CHUNK_SIZE + if max_words < 1: + max_words = 1 + + if not text.strip(): + return [] + + if smart is None: + smart = bool(getattr(config, "SMART_CHUNKING", False)) + if smart: + return _split_smart(text, max_words) + return _split_legacy(text, max_words) diff --git a/app/converter/config.py b/app/converter/config.py index da73427..c021375 100644 --- a/app/converter/config.py +++ b/app/converter/config.py @@ -10,6 +10,13 @@ HEARTBEAT_INTERVAL_SECONDS = 30 # Print "still working" in console logs every N # Words per TTS generation request (client-side chunking). CHUNK_SIZE = 250 +# Chunking strategy. Smart chunking ends each request at the end of a +# sentence or quotation instead of a mid-sentence overflow: chunks stay +# at or below CHUNK_SIZE (most land slightly under it, aiming for a +# natural boundary near 85%) and short quotations are kept in one +# request when they fit. Turn it off for the exact legacy splitting. +SMART_CHUNKING = True + # Where books are read from and where finished audiobooks are written. # Relative paths resolve against the project root. INPUT_DIR = "input" diff --git a/app/converter/converter.py b/app/converter/converter.py index 2b849a2..f8815d8 100644 --- a/app/converter/converter.py +++ b/app/converter/converter.py @@ -251,11 +251,11 @@ def chunk_clamp_needed(entry) -> bool: def chunk_clamp_message(entry) -> List[str]: """The popup text for a chunk_words-capped ENTRY (short lines).""" return [ - f"{entry.label} can narrate at most ~{entry.chunk_words} words " - "per request: the server caps", - "each request's prompt plus generation at a fixed window. " - "Longer sub-chunks", - "may cut off mid-sentence.", + f"{entry.label} narrates best at ~{entry.chunk_words} words " + "per request on this server:", + "each request's prompt plus generation must fit a fixed " + "window, so longer", + "sub-chunks may cut off mid-sentence.", ] @@ -305,6 +305,9 @@ class AudiobookConverter: # Class-level default so a partially-constructed instance (tests build # these with __new__) behaves like a plain console run. _progress = None + # Same for the per-run chunk override: without __init__ there is no + # clamp, so chunking follows the config.CHUNK_SIZE setting. + chunk_size = None def __init__(self, voice_mode: str = VOICE_MODE_CUSTOM, voice_clone_ref_audio: Optional[str] = None, voice_clone_ref_text: Optional[str] = None, skip_transcription: bool = False, @@ -340,6 +343,12 @@ class AudiobookConverter: self.backend = backend self.voice = voice self.debug = bool(debug) + # Per-run chunk-word override (the pre-flight popup's clamp for + # models whose engine caps one request below a full sub-chunk, + # SGLang-Omni's Higgs): caps the chapter chunks themselves so + # progress and debug dumps span one generation request each. + # None follows the config.CHUNK_SIZE setting. + self.chunk_size = chunk_size # The run's model selection (audio.cpp: a server entry id, sglomni: # the resolved catalog key, None elsewhere) — the startup banner # reports it. @@ -404,10 +413,9 @@ class AudiobookConverter: "catalog key for --model (see the backend docs).") model_id = entry.key self.model_id = model_id - # CHUNK_SIZE carries a per-run override (the pre-flight chunk - # popup's clamp for models whose engine caps one request below - # a full sub-chunk); None follows the config.CHUNK_SIZE setting. - self.chunk_size = chunk_size + # The catalog/request shape is resolved below; the per-run + # chunk override (self.chunk_size) was recorded above and + # reaches the client here. self.tts = SgOmniTTSClient( chunks_dir=CHUNKS_FOLDER, model=model_id, voice=voice, ref_audio=voice_clone_ref_audio, @@ -839,8 +847,14 @@ class AudiobookConverter: return results def _chapter_chunks(self, text: str) -> List[str]: - """Split chapter text into CHUNK_SIZE-word TTS requests.""" - return chunking.split_into_chunks(text) + """Split chapter text into word-capped TTS request chunks. + + Each chunk is one progress unit; when the pre-flight popup set + a per-run clamp (models whose engine caps one request below + CHUNK_SIZE), it caps these chunks too so a chunk is never + wider than one generation request. + """ + return chunking.split_into_chunks(text, max_words=self.chunk_size) def _convert_text(self, text: str, output_path: Path, start_time: float, speed: Optional[float] = None, |