refactor: migrate preview and conversion code to use TTSBackendRegistry

Migrate all preview/debug/conversion pipeline creation to use
TTSBackendRegistry.create_backend() instead of direct imports:

- debug_tts_runner._load_pipeline(): Kokoro via registry
- preview.get_preview_pipeline(): Kokoro via registry
- preview.generate_preview_audio(): Supertonic via registry
- voice.get_preview_pipeline(): Kokoro via registry
- conversion_runner._load_pipeline(): both backends via registry
- conversion_runner inline pipeline creation: both via registry
- test: update mock to target tts_backend_registry.create_backend

abogen/webui/conversion_runner.py

@@ -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:

abogen/webui/debug_tts_runner.py

@@ -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]]:

abogen/webui/routes/utils/preview.py

@@ -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,

abogen/webui/routes/utils/voice.py

@@ -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
 

tests/test_preview_applies_manual_overrides.py

@@ -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(