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https://github.com/denizsafak/abogen.git
synced 2026-07-18 05:40:26 +02:00
feat: Enhance voice resolution handling and support mixed-provider conversions
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JB
@@ -1511,6 +1511,28 @@ def run_conversion_job(job: Job) -> None:
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return "supertonic", _supertonic_voice_from_spec(spec, getattr(job, "voice", "M1")), None, None
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return "kokoro", spec, None, None
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def resolve_voice_choice(raw_spec: str) -> tuple[str, str, Any, Optional[float], Optional[int]]:
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"""Resolve a raw voice spec into (provider, resolved_spec, choice, speed, steps).
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For Kokoro formulas, `choice` will be a resolved voice tensor (via `voice_formulas`).
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For SuperTonic, `choice` will be a valid SuperTonic voice id.
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"""
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provider, resolved, speed, steps = resolve_voice_target(raw_spec)
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cache_key = f"{provider}:{resolved}" if resolved else provider
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cached = voice_cache.get(cache_key)
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if cached is not None:
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return provider, resolved, cached, speed, steps
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if provider == "kokoro":
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kokoro_pipeline = get_pipeline("kokoro")
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choice = _resolve_voice(kokoro_pipeline, resolved, job.use_gpu)
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else:
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choice = resolved
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voice_cache[cache_key] = choice
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return provider, resolved, choice, speed, steps
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extraction = extract_from_path(job.stored_path)
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file_type = _infer_file_type(job.stored_path)
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pronunciation_rules = _compile_pronunciation_rules(job.pronunciation_overrides)
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@@ -2074,9 +2096,10 @@ def run_conversion_job(job: Job) -> None:
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if outro_voice_spec == "__custom_mix":
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outro_voice_spec = base_voice_spec or ""
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if not outro_voice_spec:
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fallback_voice = next(iter(voice_cache.keys()), "")
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if fallback_voice and fallback_voice != "__custom_mix":
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outro_voice_spec = fallback_voice
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fallback_key = next(iter(voice_cache.keys()), "")
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if fallback_key and fallback_key != "__custom_mix":
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# `voice_cache` keys are internal and include provider prefixes.
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outro_voice_spec = fallback_key.split(":", 1)[-1]
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if not outro_voice_spec and VOICES_INTERNAL:
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outro_voice_spec = VOICES_INTERNAL[0]
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@@ -2085,10 +2108,7 @@ def run_conversion_job(job: Job) -> None:
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outro_audio_path: Optional[Path] = None
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outro_segments = 0
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outro_index = total_chapters + 1
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outro_voice_choice = voice_cache.get(outro_voice_spec)
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if outro_voice_choice is None:
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outro_voice_choice = _resolve_voice(pipeline, outro_voice_spec, job.use_gpu)
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voice_cache[outro_voice_spec] = outro_voice_choice
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outro_provider, _, outro_voice_choice, outro_speed, outro_steps = resolve_voice_choice(outro_voice_spec)
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with ExitStack() as outro_sink_stack:
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chapter_sink: Optional[AudioSink] = None
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@@ -2110,6 +2130,9 @@ def run_conversion_job(job: Job) -> None:
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voice_choice=outro_voice_choice,
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chapter_sink=chapter_sink,
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preview_prefix="Outro",
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tts_provider=outro_provider,
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speed_override=outro_speed,
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supertonic_steps_override=outro_steps,
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)
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outro_end_time = current_time
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@@ -574,11 +574,15 @@ def apply_book_step_form(
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except ValueError:
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pass
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provider_value = str(form.get("tts_provider") or getattr(pending, "tts_provider", None) or "").strip().lower()
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if provider_value not in {"kokoro", "supertonic"}:
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provider_value = ""
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# NOTE: Do not auto-set a global TTS provider at the book level based on the
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# narrator defaults. Provider is resolved per-speaker/per-chunk from the voice
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# spec (e.g. "speaker:Name" for saved speakers, or a Kokoro mix formula).
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# This enables mixed-provider conversions (e.g. narrator=SuperTonic, characters=Kokoro).
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provider_value = str(form.get("tts_provider") or "").strip().lower()
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if provider_value in {"kokoro", "supertonic"}:
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pending.tts_provider = provider_value
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# Determine the base speaker selection (saved speaker or raw voice).
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# Determine the base speaker selection (saved speaker ref or raw voice).
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narrator_voice_raw = (
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form.get("voice")
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or pending.voice
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@@ -588,102 +592,54 @@ def apply_book_step_form(
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).strip()
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profiles_map = dict(profiles) if isinstance(profiles, Mapping) else dict(profiles or {})
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base_spec, selected_speaker_name = split_profile_spec(narrator_voice_raw)
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selected_speaker_entry = None
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if selected_speaker_name:
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selected_speaker_entry = normalize_profile_entry(profiles_map.get(selected_speaker_name))
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base_spec, _selected_speaker_name = split_profile_spec(narrator_voice_raw)
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# If a saved speaker is selected, prefer its provider.
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if selected_speaker_entry and selected_speaker_entry.get("provider") in {"kokoro", "supertonic"}:
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provider_value = str(selected_speaker_entry.get("provider"))
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profile_selection = (form.get("voice_profile") or pending.voice_profile or "__standard").strip()
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custom_formula_raw = (form.get("voice_formula") or "").strip()
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narrator_voice_raw = (base_spec or narrator_voice_raw or settings.get("default_voice") or "").strip()
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resolved_default_voice, inferred_profile, _ = resolve_voice_setting(
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narrator_voice_raw,
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profiles=profiles_map,
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)
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if not provider_value:
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# Fall back to inferring provider from the raw voice spec.
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provider_value = "supertonic" if base_spec in {"M1","M2","M3","M4","M5","F1","F2","F3","F4","F5"} else "kokoro"
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if profile_selection in {"__standard", "", None} and inferred_profile:
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profile_selection = inferred_profile
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pending.tts_provider = provider_value
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try:
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pending.supertonic_total_steps = int(
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form.get("supertonic_total_steps")
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or getattr(pending, "supertonic_total_steps", None)
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or (selected_speaker_entry or {}).get("total_steps")
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or settings.get("supertonic_total_steps")
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or 5
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)
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except (TypeError, ValueError):
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pending.supertonic_total_steps = int(settings.get("supertonic_total_steps") or 5)
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if provider_value == "supertonic":
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# If the user picked a saved Supertonic speaker, use its config.
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if selected_speaker_entry and selected_speaker_entry.get("provider") == "supertonic":
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pending.voice_profile = None
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pending.voice = str(selected_speaker_entry.get("voice") or "M1")
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pending.supertonic_total_steps = int(selected_speaker_entry.get("total_steps") or pending.supertonic_total_steps)
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if speed_value is None:
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try:
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pending.speed = float(selected_speaker_entry.get("speed") or settings.get("supertonic_speed") or 1.0)
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except (TypeError, ValueError):
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pending.speed = 1.0
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pending.language = str(selected_speaker_entry.get("language") or "a")
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else:
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# Supertonic does not support Abogen voice mixing.
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pending.voice_profile = None
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pending.voice = (base_spec or "M1").strip() or "M1"
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# Provider-specific speed default.
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if speed_value is None:
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try:
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pending.speed = float(settings.get("supertonic_speed") or 1.0)
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except (TypeError, ValueError):
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pending.speed = 1.0
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pending.language = "a"
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if profile_selection == "__formula":
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profile_name = ""
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custom_formula = custom_formula_raw
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elif profile_selection in {"__standard", "", None}:
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profile_name = ""
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custom_formula = ""
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else:
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profile_selection = (form.get("voice_profile") or pending.voice_profile or "__standard").strip()
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custom_formula_raw = (form.get("voice_formula") or "").strip()
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narrator_voice_raw = (base_spec or narrator_voice_raw or settings.get("default_voice") or "").strip()
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resolved_default_voice, inferred_profile, _ = resolve_voice_setting(
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narrator_voice_raw,
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profiles=profiles_map,
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)
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profile_name = profile_selection
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custom_formula = ""
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if profile_selection in {"__standard", "", None} and inferred_profile:
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profile_selection = inferred_profile
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base_voice_spec = resolved_default_voice or narrator_voice_raw
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if not base_voice_spec and VOICES_INTERNAL:
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base_voice_spec = VOICES_INTERNAL[0]
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if profile_selection == "__formula":
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profile_name = ""
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custom_formula = custom_formula_raw
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elif profile_selection in {"__standard", "", None}:
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profile_name = ""
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custom_formula = ""
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else:
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profile_name = profile_selection
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custom_formula = ""
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voice_choice, resolved_language, selected_profile = resolve_voice_choice(
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pending.language,
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base_voice_spec,
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profile_name,
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custom_formula,
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profiles_map,
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)
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base_voice_spec = resolved_default_voice or narrator_voice_raw
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if not base_voice_spec and VOICES_INTERNAL:
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base_voice_spec = VOICES_INTERNAL[0]
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if resolved_language:
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pending.language = resolved_language
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voice_choice, resolved_language, selected_profile = resolve_voice_choice(
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pending.language,
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base_voice_spec,
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profile_name,
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custom_formula,
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profiles_map,
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)
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if resolved_language:
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pending.language = resolved_language
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if profile_selection == "__formula" and custom_formula_raw:
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pending.voice = custom_formula_raw
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pending.voice_profile = None
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elif profile_selection not in {"__standard", "", None, "__formula"}:
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pending.voice_profile = selected_profile or profile_selection
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pending.voice = voice_choice
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else:
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pending.voice_profile = None
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fallback_voice = base_voice_spec or narrator_voice_raw
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pending.voice = voice_choice or fallback_voice
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if profile_selection == "__formula" and custom_formula_raw:
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pending.voice = custom_formula_raw
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pending.voice_profile = None
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elif profile_selection not in {"__standard", "", None, "__formula"}:
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pending.voice_profile = selected_profile or profile_selection
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pending.voice = voice_choice
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else:
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pending.voice_profile = None
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fallback_voice = base_voice_spec or narrator_voice_raw
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pending.voice = voice_choice or fallback_voice
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pending.applied_speaker_config = (form.get("speaker_config") or "").strip() or None
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@@ -658,14 +658,31 @@ def resolve_voice_choice(
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selected_profile = None
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if profile_name:
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entry = profiles.get(profile_name)
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formula = formula_from_profile(entry or {}) if entry else None
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if formula:
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resolved_voice = formula
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from abogen.voice_profiles import normalize_profile_entry
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entry_raw = profiles.get(profile_name)
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entry = normalize_profile_entry(entry_raw)
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provider = str((entry or {}).get("provider") or "").strip().lower()
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# Provider-aware behavior:
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# - Kokoro profiles typically represent mixes (formula strings).
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# - SuperTonic profiles represent a discrete voice id + settings.
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# In that case, we return a speaker reference so downstream can
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# resolve provider per-speaker and allow mixed-provider casting.
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if provider == "supertonic":
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resolved_voice = f"speaker:{profile_name}"
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selected_profile = profile_name
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profile_language = (entry or {}).get("language")
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if profile_language:
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resolved_language = profile_language
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resolved_language = str(profile_language)
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else:
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formula = formula_from_profile(entry or {}) if entry else None
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if formula:
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resolved_voice = formula
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selected_profile = profile_name
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profile_language = (entry or {}).get("language")
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if profile_language:
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resolved_language = profile_language
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if custom_formula:
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resolved_voice = custom_formula
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@@ -0,0 +1,83 @@
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from pathlib import Path
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from werkzeug.datastructures import MultiDict
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from abogen.web.routes.utils.form import apply_book_step_form
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from abogen.web.service import PendingJob
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def _make_pending_job() -> PendingJob:
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pending = PendingJob(
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id="pending",
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original_filename="example.epub",
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stored_path=Path("example.epub"),
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language="a",
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voice="af_nova",
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speed=1.0,
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use_gpu=False,
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subtitle_mode="none",
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output_format="mp3",
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save_mode="save_next_to_input",
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output_folder=None,
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replace_single_newlines=False,
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subtitle_format="srt",
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total_characters=0,
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save_chapters_separately=False,
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merge_chapters_at_end=True,
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separate_chapters_format="wav",
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silence_between_chapters=2.0,
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save_as_project=False,
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voice_profile=None,
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max_subtitle_words=50,
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metadata_tags={},
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chapters=[],
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normalization_overrides={},
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created_at=0.0,
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read_title_intro=False,
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normalize_chapter_opening_caps=True,
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)
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pending.tts_provider = "kokoro"
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return pending
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def test_book_step_supertonic_profile_becomes_speaker_reference() -> None:
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pending = _make_pending_job()
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settings = {
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"language": "a",
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"chunk_level": "paragraph",
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"speaker_analysis_threshold": 3,
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"default_voice": "af_nova",
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"default_speaker": "",
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"default_speed": 1.0,
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"read_title_intro": False,
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"read_closing_outro": True,
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"normalize_chapter_opening_caps": True,
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}
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profiles = {
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"Female HQ": {
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"provider": "supertonic",
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"voice": "F3",
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"speed": 1.0,
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"total_steps": 5,
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"language": "a",
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}
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}
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form = MultiDict(
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{
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"language": "a",
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"voice_profile": "Female HQ",
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"speed": "1.0",
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}
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)
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apply_book_step_form(pending, form, settings=settings, profiles=profiles)
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# Voice is stored as a speaker reference so provider can be resolved per-speaker.
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assert pending.voice == "speaker:Female HQ"
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assert pending.voice_profile == "Female HQ"
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# Book-level provider should not be overridden by narrator defaults.
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assert pending.tts_provider == "kokoro"
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