Merge pull request #180 from k0sm0naft/refactor/use-registry-for-preview

refactor: migrate preview and conversion code to use TTSBackendRegistry
This commit is contained in:
Artem Akymenko
2026-07-06 16:53:28 +03:00
committed by GitHub
5 changed files with 28 additions and 26 deletions
+9 -9
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@@ -40,14 +40,14 @@ from abogen.utils import (
get_user_output_path,
load_config,
)
from abogen.tts_backends.kokoro import load_numpy_kpipeline
from abogen.tts_backend_registry import create_backend
from abogen.tts_backend import TTSBackend
from abogen.voice_cache import ensure_voice_assets
from abogen.voice_formulas import extract_voice_ids, get_new_voice
from abogen.voice_profiles import load_profiles, normalize_profile_entry
from abogen.pronunciation_store import increment_usage
from abogen.llm_client import LLMClientError
from abogen.tts_backends.supertonic import DEFAULT_SUPERTONIC_VOICES, SupertonicPipeline
from abogen.tts_backends.supertonic import DEFAULT_SUPERTONIC_VOICES
from .service import Job, JobStatus
@@ -1582,7 +1582,8 @@ def run_conversion_job(job: Job) -> None:
return existing
if provider_norm == "supertonic":
pipelines[provider_norm] = SupertonicPipeline(
pipelines[provider_norm] = create_backend(
"supertonic",
sample_rate=SAMPLE_RATE,
auto_download=True,
total_steps=int(getattr(job, "supertonic_total_steps", 5) or 5),
@@ -1595,11 +1596,10 @@ def run_conversion_job(job: Job) -> None:
device = "cpu"
if not disable_gpu:
device = _select_device()
_np, KPipeline = load_numpy_kpipeline()
# Create KPipeline instance directly (conforms to TTSBackend protocol)
pipelines[provider_norm] = KPipeline(
pipelines[provider_norm] = create_backend(
"kokoro",
lang_code=job.language,
repo_id="hexgrad/Kokoro-82M",
device=device
)
if not kokoro_cache_ready:
@@ -2443,7 +2443,8 @@ def _load_pipeline(job: Job):
disable_gpu = not job.use_gpu or not cfg.get("use_gpu", True)
provider = str(getattr(job, "tts_provider", "kokoro") or "kokoro").strip().lower()
if provider == "supertonic":
return SupertonicPipeline(
return create_backend(
"supertonic",
sample_rate=SAMPLE_RATE,
auto_download=True,
total_steps=int(getattr(job, "supertonic_total_steps", 5) or 5),
@@ -2452,8 +2453,7 @@ def _load_pipeline(job: Job):
device = "cpu"
if not disable_gpu:
device = _select_device()
_np, KPipeline = load_numpy_kpipeline()
return KPipeline(lang_code=job.language, repo_id="hexgrad/Kokoro-82M", device=device)
return create_backend("kokoro", lang_code=job.language, device=device)
def _select_device() -> str:
+2 -3
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@@ -15,7 +15,7 @@ from abogen.normalization_settings import build_apostrophe_config
from abogen.text_extractor import extract_from_path
from abogen.voice_cache import ensure_voice_assets
from abogen.webui.conversion_runner import SAMPLE_RATE, SPLIT_PATTERN, _select_device, _to_float32, _resolve_voice, _spec_to_voice_ids
from abogen.tts_backends.kokoro import load_numpy_kpipeline
from abogen.tts_backend_registry import create_backend
_MARKER_RE = re.compile(re.escape(MARKER_PREFIX) + r"(?P<code>[A-Z0-9_]+)" + re.escape(MARKER_SUFFIX))
@@ -45,8 +45,7 @@ def _load_pipeline(language: str, use_gpu: bool) -> Any:
device = "cpu"
if use_gpu:
device = _select_device()
_np, KPipeline = load_numpy_kpipeline()
return KPipeline(lang_code=language, repo_id="hexgrad/Kokoro-82M", device=device)
return create_backend("kokoro", lang_code=language, device=device)
def _extract_cases_from_text(text: str) -> List[Tuple[str, str]]:
+4 -5
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@@ -78,10 +78,9 @@ def get_preview_pipeline(language: str, device: str) -> Any:
pipeline = _preview_pipelines.get(key)
if pipeline is not None:
return pipeline
from abogen.tts_backends.kokoro import load_numpy_kpipeline
from abogen.tts_backend_registry import create_backend
_, KPipeline = load_numpy_kpipeline()
pipeline = KPipeline(lang_code=language, repo_id="hexgrad/Kokoro-82M", device=device)
pipeline = create_backend("kokoro", lang_code=language, device=device)
_preview_pipelines[key] = pipeline
return pipeline
@@ -137,9 +136,9 @@ def generate_preview_audio(
normalized_text = source_text
if provider == "supertonic":
from abogen.tts_backends.supertonic import SupertonicPipeline
from abogen.tts_backend_registry import create_backend
pipeline = SupertonicPipeline(sample_rate=SAMPLE_RATE, auto_download=True, total_steps=supertonic_total_steps)
pipeline = create_backend("supertonic", sample_rate=SAMPLE_RATE, auto_download=True, total_steps=supertonic_total_steps)
segments = pipeline(
normalized_text,
voice=voice_spec,
+2 -3
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@@ -20,7 +20,7 @@ from abogen.constants import (
VOICES_INTERNAL,
)
from abogen.speaker_configs import list_configs
from abogen.tts_backends.kokoro import load_numpy_kpipeline
from abogen.tts_backend_registry import create_backend
from abogen.webui.conversion_runner import _select_device, _to_float32, SAMPLE_RATE, SPLIT_PATTERN
_preview_pipeline_lock = threading.RLock()
@@ -741,8 +741,7 @@ def get_preview_pipeline(language: str, device: str):
pipeline = _preview_pipelines.get(key)
if pipeline is not None:
return pipeline
_, KPipeline = load_numpy_kpipeline()
pipeline = KPipeline(lang_code=language, repo_id="hexgrad/Kokoro-82M", device=device)
pipeline = create_backend("kokoro", lang_code=language, device=device)
_preview_pipelines[key] = pipeline
return pipeline
+11 -6
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@@ -19,7 +19,7 @@ def test_preview_applies_manual_override_before_normalization(monkeypatch):
# And stub the kokoro pipeline path so generate_preview_audio won't proceed.
# We'll instead validate by calling the override logic through generate_preview_audio
# with provider=supertonic and stub SupertonicPipeline to capture input.
# with provider=supertonic and stub create_backend to capture input.
captured = {}
class DummyPipeline:
@@ -30,11 +30,16 @@ def test_preview_applies_manual_override_before_normalization(monkeypatch):
captured["text"] = text
return iter(())
monkeypatch.setitem(
__import__("sys").modules,
"abogen.tts_backends.supertonic",
type("M", (), {"SupertonicPipeline": DummyPipeline}),
)
from abogen import tts_backend_registry
original_create_backend = tts_backend_registry.create_backend
def _mock_create_backend(backend_id, **kwargs):
if backend_id == "supertonic":
return DummyPipeline(**kwargs)
return original_create_backend(backend_id, **kwargs)
monkeypatch.setattr(tts_backend_registry, "create_backend", _mock_create_backend)
try:
preview.generate_preview_audio(