Encapsulate SupertonicPipeline as an internal detail of
SupertonicBackend. The factory create_supertonic_backend() now
returns a SupertonicBackend instance instead of a raw
SupertonicPipeline, satisfying the TTSBackend protocol with
metadata, synthesize, get_available_voices, get_supported_formats,
and get_info methods. Backward-compatible __call__ delegates to
the internal pipeline.
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
- Add create_kokoro_backend() factory in kokoro.py
- Add create_supertonic_backend() factory in supertonic.py
- Auto-discover backend modules in __init__.py via pkgutil
- Both backends register themselves on import
- Tests verify registration and factory callables
- TTSBackendRegistry class with register(), list_backends(), get_metadata(), create_backend()
- Global registry singleton with register_backend() and create_backend() convenience functions
- Unit tests for registry operations
Moved SupertonicPipeline from abogen/tts_supertonic.py to
abogen/tts_backends/supertonic.py and load_numpy_kpipeline from
abogen/utils.py to abogen/tts_backends/kokoro.py.
Git correctly detects the Supertonic file as a rename (R),
preserving full commit history.
- New package: abogen/tts_backends/
- __init__.py (package marker)
- supertonic.py (SupertonicPipeline, moved from tts_supertonic.py)
- kokoro.py (load_numpy_kpipeline, moved from utils.py)
- abogen/utils.py: re-exports load_numpy_kpipeline for backward compat
- All imports updated to new canonical paths
- Implemented voice management routes in `voices.py` for listing, saving, and deleting speaker configurations.
- Added a test endpoint for voice synthesis preview, allowing users to test voice settings with provided text and speed.
- Introduced utility functions in `voice.py` for building voice catalogs, resolving voice settings, and synthesizing audio from normalized text.
- Enhanced speaker roster building and configuration application logic to support dynamic voice settings.
Artem Akymenko