c86e323d7a
Quality-first multi-pass audiobook generation from English manuscripts. Includes: - umbraaudio/ core package (pipeline, config, voices, web review UI) - scripts/ CLI utilities + model download script - tts_server/ remote TTS server - specs/ design docs, tests/, pyproject.toml + uv.lock - Qwen3-TTS git submodule (pinned 022e286) with local demo.py UI patch saved at scripts/qwen3_tts_demo_umbra_patch.patch - .env with runtime config/secrets Excluded (see .gitignore): models/ (downloaded via scripts/download_models.sh), output/, logs/, .venv, .umbra runtime data, and book projects (DealHunterShip_*), which are committed separately.
112 lines
3.6 KiB
Python
112 lines
3.6 KiB
Python
from __future__ import annotations
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from umbraaudio.web.routes import (
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_extract_proper_nouns,
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_lowercase_words,
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_mid_sentence_counts,
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_proper_name_candidates,
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_speaker_name_words,
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)
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_TEXT = (
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"Kainda walked in. Princess Kainda Murphy smiled. The Warbots roared. "
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"They went there and they left after what happened. "
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"Wow, that is odd. Additionally, I have a plan. "
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"Captain Weston spoke. Weston is a friend. The ship is the Deal Hunter. "
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"Gisfrid arrived. Karel waited. It was a good deal, the captain said to the princess."
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)
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_SPEAKERS = [
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{"primary_name": "Kainda Walters Foster Murphy", "aliases": ["Princess Kainda"]},
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{"primary_name": "Captain Weston", "aliases": []},
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{"primary_name": "Deal Hunter", "aliases": []},
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{"primary_name": "Gisfrid", "aliases": []},
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]
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def _records() -> dict:
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return {
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"Kainda": {"phonetic": "KAYN-duh", "source": "user", "confirmed": True, "common": False},
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}
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def test_extract_proper_nouns_flattens_multiword() -> None:
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nouns = {entry["name"]: entry["count"] for entry in _extract_proper_nouns(_TEXT)}
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assert "Princess Kainda Murphy" not in nouns
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assert "Captain Weston" not in nouns
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assert nouns["Kainda"] == 2
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assert nouns["Murphy"] == 1
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assert nouns["Weston"] == 2
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def test_extract_proper_nouns_excludes_titles_and_stopwords() -> None:
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nouns = {entry["name"] for entry in _extract_proper_nouns(_TEXT)}
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assert "Captain" not in nouns
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assert "Princess" not in nouns
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assert "The" not in nouns
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assert "It" not in nouns
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def test_lowercase_words_only_literal_lowercase() -> None:
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words = _lowercase_words(_TEXT)
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assert "they" in words
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assert "after" in words
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assert "deal" in words
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assert "kainda" not in words
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assert "murphy" not in words
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def test_mid_sentence_counts() -> None:
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counts = _mid_sentence_counts(_TEXT, {"Kainda", "Weston", "Wow", "Gisfrid"})
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assert counts["Kainda"] == 1
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assert counts["Weston"] >= 1
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assert counts.get("Wow", 0) == 0
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assert counts.get("Gisfrid", 0) == 0
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def test_speaker_name_words_excludes_descriptors() -> None:
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words = _speaker_name_words(_SPEAKERS, _lowercase_words(_TEXT))
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assert "kainda" in words
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assert "murphy" in words
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assert "weston" in words
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assert "gisfrid" in words
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assert "captain" not in words
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assert "princess" not in words
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def test_proper_name_candidates_keeps_names() -> None:
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kept = {
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entry["name"]: entry
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for entry in _proper_name_candidates(
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_extract_proper_nouns(_TEXT), _TEXT, _SPEAKERS, _records()
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)
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}
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for name in ("Kainda", "Murphy", "Warbots", "Weston", "Hunter", "Gisfrid"):
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assert name in kept, f"{name} should be kept"
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assert kept["Kainda"]["is_speaker"] is True
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assert kept["Murphy"]["is_speaker"] is True
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assert kept["Gisfrid"]["is_speaker"] is True
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def test_proper_name_candidates_drops_prose() -> None:
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kept = {
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entry["name"]
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for entry in _proper_name_candidates(
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_extract_proper_nouns(_TEXT), _TEXT, _SPEAKERS, _records()
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)
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}
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for name in ("They", "After", "What", "That", "Wow", "Additionally", "Deal", "Karel"):
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assert name not in kept, f"{name} should be dropped"
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def test_proper_name_candidates_keeps_confirmed_name() -> None:
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records = _records()
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records["Karel"] = {"phonetic": "KAH-rel", "source": "user", "confirmed": True, "common": False}
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kept = {
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entry["name"]
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for entry in _proper_name_candidates(
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_extract_proper_nouns(_TEXT), _TEXT, _SPEAKERS, records
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)
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}
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assert "Karel" in kept
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