feat: add PluginManager, compat adapter, and consumer migration

- Add PluginManager singleton for plugin discovery and engine caching
- Add CompatBackend adapter wrapping Engine/EngineSession into old create_backend() API
- Update tts_plugin/__init__.py with public exports
- Migrate preview.py and its test to use compat.create_backend
- Add integration and plugin manager contract tests

abogen/tts_plugin/__init__.py

@@ -1,139 +1,156 @@
-"""TTS Plugin Architecture - Public API.
-
-This package defines the frozen Plugin API for the TTS Plugin Architecture.
-All public interfaces are fully defined but contain no business logic.
-
-Public modules:
-- types: Core domain value objects (AudioFormat, Duration, VoiceSelection, etc.)
-- errors: Error hierarchy (EngineError and subtypes)
-- manifest: Plugin manifest types (PluginManifest, EngineManifest, etc.)
-- engine: Engine and EngineSession protocols
-- capabilities: Optional capability interfaces (VoiceLister, PreviewGenerator, etc.)
-- host_context: HostContext dataclass
-- plugin: Plugin contract (create_engine function signature)
-
-Usage:
-    from abogen.tts_plugin import (
-        # Types
-        AudioFormat,
-        Duration,
-        VoiceSelection,
-        ParameterValues,
-        SynthesisRequest,
-        SynthesizedAudio,
-        EngineConfig,
-        # Errors
-        EngineError,
-        ModelNotFoundError,
-        ModelLoadError,
-        NetworkError,
-        InvalidInputError,
-        ConfigurationError,
-        CancelledError,
-        InternalError,
-        # Manifest
-        PluginManifest,
-        EngineManifest,
-        VoiceSourceManifest,
-        VoiceManifest,
-        ParameterManifest,
-        AudioFormatManifest,
-        EnumOption,
-        RequirementManifest,
-        GpuRequirement,
-        ModelManifest,
-        # Engine
-        Engine,
-        EngineSession,
-        # Capabilities
-        VoiceLister,
-        PreviewGenerator,
-        StreamingSynthesizer,
-        CancelableSession,
-        # Host Context
-        HostContext,
-        HttpClient,
-    )
-"""
-
-from abogen.tts_plugin.capabilities import (
-    CancelableSession,
-    PreviewGenerator,
-    StreamingSynthesizer,
-    VoiceLister,
-)
-from abogen.tts_plugin.engine import Engine, EngineSession
-from abogen.tts_plugin.errors import (
-    CancelledError,
-    ConfigurationError,
-    EngineError,
-    InternalError,
-    InvalidInputError,
-    ModelLoadError,
-    ModelNotFoundError,
-    NetworkError,
-)
-from abogen.tts_plugin.host_context import HttpClient, HostContext
-from abogen.tts_plugin.manifest import (
-    AudioFormatManifest,
-    EngineManifest,
-    EnumOption,
-    GpuRequirement,
-    ModelManifest,
-    ParameterManifest,
-    PluginManifest,
-    RequirementManifest,
-    VoiceManifest,
-    VoiceSourceManifest,
-)
-from abogen.tts_plugin.types import (
-    AudioFormat,
-    Duration,
-    EngineConfig,
-    ParameterValues,
-    SynthesisRequest,
-    SynthesizedAudio,
-    VoiceSelection,
-)
-
-__all__ = [
-    # Types
-    "AudioFormat",
-    "Duration",
-    "VoiceSelection",
-    "ParameterValues",
-    "SynthesisRequest",
-    "SynthesizedAudio",
-    "EngineConfig",
-    # Errors
-    "EngineError",
-    "ModelNotFoundError",
-    "ModelLoadError",
-    "NetworkError",
-    "InvalidInputError",
-    "ConfigurationError",
-    "CancelledError",
-    "InternalError",
-    # Manifest
-    "PluginManifest",
-    "EngineManifest",
-    "VoiceSourceManifest",
-    "VoiceManifest",
-    "ParameterManifest",
-    "AudioFormatManifest",
-    "EnumOption",
-    "RequirementManifest",
-    "GpuRequirement",
-    "ModelManifest",
-    # Engine
-    "Engine",
-    "EngineSession",
-    # Capabilities
-    "VoiceLister",
-    "PreviewGenerator",
-    "StreamingSynthesizer",
-    "CancelableSession",
-    # Host Context
-    "HostContext",
-    "HttpClient",
-]
+"""TTS Plugin Architecture - Public API.
+
+This package defines the frozen Plugin API for the TTS Plugin Architecture.
+All public interfaces are fully defined but contain no business logic.
+
+Public modules:
+- types: Core domain value objects (AudioFormat, Duration, VoiceSelection, etc.)
+- errors: Error hierarchy (EngineError and subtypes)
+- manifest: Plugin manifest types (PluginManifest, EngineManifest, etc.)
+- engine: Engine and EngineSession protocols
+- capabilities: Optional capability interfaces (VoiceLister, PreviewGenerator, etc.)
+- host_context: HostContext dataclass
+- plugin: Plugin contract (create_engine function signature)
+- loader: Plugin discovery and loading
+- plugin_manager: Plugin management and engine creation
+- compat: Backward compatibility adapter for old create_backend() API
+
+Usage:
+    from abogen.tts_plugin import (
+        # Types
+        AudioFormat,
+        Duration,
+        VoiceSelection,
+        ParameterValues,
+        SynthesisRequest,
+        SynthesizedAudio,
+        EngineConfig,
+        # Errors
+        EngineError,
+        ModelNotFoundError,
+        ModelLoadError,
+        NetworkError,
+        InvalidInputError,
+        ConfigurationError,
+        CancelledError,
+        InternalError,
+        # Manifest
+        PluginManifest,
+        EngineManifest,
+        VoiceSourceManifest,
+        VoiceManifest,
+        ParameterManifest,
+        AudioFormatManifest,
+        EnumOption,
+        RequirementManifest,
+        GpuRequirement,
+        ModelManifest,
+        # Engine
+        Engine,
+        EngineSession,
+        # Capabilities
+        VoiceLister,
+        PreviewGenerator,
+        StreamingSynthesizer,
+        CancelableSession,
+        # Host Context
+        HostContext,
+        HttpClient,
+        # Plugin Manager
+        get_plugin_manager,
+        reset_plugin_manager,
+        # Compatibility
+        create_backend,
+    )
+"""
+
+from abogen.tts_plugin.capabilities import (
+    CancelableSession,
+    PreviewGenerator,
+    StreamingSynthesizer,
+    VoiceLister,
+)
+from abogen.tts_plugin.engine import Engine, EngineSession
+from abogen.tts_plugin.errors import (
+    CancelledError,
+    ConfigurationError,
+    EngineError,
+    InternalError,
+    InvalidInputError,
+    ModelLoadError,
+    ModelNotFoundError,
+    NetworkError,
+)
+from abogen.tts_plugin.host_context import HttpClient, HostContext
+from abogen.tts_plugin.manifest import (
+    AudioFormatManifest,
+    EngineManifest,
+    EnumOption,
+    GpuRequirement,
+    ModelManifest,
+    ParameterManifest,
+    PluginManifest,
+    RequirementManifest,
+    VoiceManifest,
+    VoiceSourceManifest,
+)
+from abogen.tts_plugin.types import (
+    AudioFormat,
+    Duration,
+    EngineConfig,
+    ParameterValues,
+    SynthesisRequest,
+    SynthesizedAudio,
+    VoiceSelection,
+)
+
+# Plugin Manager and Compatibility
+from abogen.tts_plugin.plugin_manager import get_plugin_manager, reset_plugin_manager
+from abogen.tts_plugin.compat import create_backend
+
+__all__ = [
+    # Types
+    "AudioFormat",
+    "Duration",
+    "VoiceSelection",
+    "ParameterValues",
+    "SynthesisRequest",
+    "SynthesizedAudio",
+    "EngineConfig",
+    # Errors
+    "EngineError",
+    "ModelNotFoundError",
+    "ModelLoadError",
+    "NetworkError",
+    "InvalidInputError",
+    "ConfigurationError",
+    "CancelledError",
+    "InternalError",
+    # Manifest
+    "PluginManifest",
+    "EngineManifest",
+    "VoiceSourceManifest",
+    "VoiceManifest",
+    "ParameterManifest",
+    "AudioFormatManifest",
+    "EnumOption",
+    "RequirementManifest",
+    "GpuRequirement",
+    "ModelManifest",
+    # Engine
+    "Engine",
+    "EngineSession",
+    # Capabilities
+    "VoiceLister",
+    "PreviewGenerator",
+    "StreamingSynthesizer",
+    "CancelableSession",
+    # Host Context
+    "HostContext",
+    "HttpClient",
+    # Plugin Manager
+    "get_plugin_manager",
+    "reset_plugin_manager",
+    # Compatibility
+    "create_backend",
+]

abogen/tts_plugin/compat.py

@@ -0,0 +1,137 @@
+"""TTS Backend Compatibility Adapter
+
+Provides a drop-in replacement for the old `create_backend()` function
+that uses the new Plugin Architecture under the hood.
+
+Usage:
+    # Old way:
+    from abogen.tts_backend_registry import create_backend
+    pipeline = create_backend("kokoro", lang_code="a", device="cpu")
+
+    # New way (same interface):
+    from abogen.tts_plugin.compat import create_backend
+    pipeline = create_backend("kokoro", lang_code="a", device="cpu")
+
+The adapter wraps the new Engine/EngineSession into a callable that
+matches the old TTSBackend protocol.
+"""
+
+from typing import Any, Callable, Iterable, Iterator, List, Mapping, Optional, Tuple
+
+import numpy as np
+
+from abogen.tts_plugin.engine import Engine, EngineSession
+from abogen.tts_plugin.plugin_manager import get_plugin_manager
+
+
+class CompatBackend:
+    """Compatibility wrapper that makes a new Engine look like the old TTSBackend.
+
+    This adapter wraps the new Engine/EngineSession into a callable that
+    matches the old Kokoro pipeline interface:
+        pipeline(text, voice=..., speed=..., split_pattern=...) -> Iterator[Segment]
+    """
+
+    def __init__(self, engine: Engine, **engine_kwargs: Any) -> None:
+        self._engine = engine
+        self._engine_kwargs = engine_kwargs
+        self._session: Optional[EngineSession] = None
+
+    def _ensure_session(self) -> EngineSession:
+        """Ensure we have an active session."""
+        if self._session is None:
+            self._session = self._engine.createSession()
+        return self._session
+
+    def __call__(
+        self,
+        text: str,
+        voice: str = "default",
+        speed: float = 1.0,
+        split_pattern: str = r"\n+",
+        **kwargs: Any,
+    ) -> Iterator[Any]:
+        """Call the backend like the old Kokoro pipeline.
+
+        Returns an iterator of segment-like objects with .graphemes and .audio attributes.
+        """
+        session = self._ensure_session()
+
+        # Build synthesis request using the new API types
+        from abogen.tts_plugin.types import (
+            AudioFormat,
+            ParameterValues,
+            SynthesisRequest,
+            VoiceSelection,
+        )
+
+        # Convert voice string to VoiceSelection
+        voice_selection = VoiceSelection(source="builtin", key=voice)
+
+        # Convert speed and split_pattern to parameters
+        parameters = ParameterValues(values={"speed": speed, "split_pattern": split_pattern})
+
+        # Create request with default audio format
+        request = SynthesisRequest(
+            text=text,
+            voice=voice_selection,
+            parameters=parameters,
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+
+        # Synthesize
+        result = session.synthesize(request)
+
+        # Convert result to old-style segment iterator
+        from dataclasses import dataclass
+
+        @dataclass
+        class Segment:
+            graphemes: str
+            audio: np.ndarray
+
+        # Convert bytes back to numpy array
+        audio_array = np.frombuffer(result.data, dtype=np.float32)
+
+        # The new API returns a single audio result, but the old API returns
+        # an iterator of segments. We need to split the text and audio accordingly.
+        # For now, return a single segment with the full text and audio.
+        yield Segment(
+            graphemes=text,
+            audio=audio_array,
+        )
+
+    def dispose(self) -> None:
+        """Dispose the session."""
+        if self._session is not None:
+            try:
+                self._session.dispose()
+            except Exception:
+                pass
+            self._session = None
+
+    def __del__(self) -> None:
+        """Cleanup on garbage collection."""
+        self.dispose()
+
+
+def create_backend(backend_id: str, **kwargs: Any) -> Any:
+    """Create a TTS backend using the new Plugin Architecture.
+
+    This is a drop-in replacement for the old `create_backend()` function
+    from `abogen.tts_backend_registry`.
+
+    Args:
+        backend_id: The backend/plugin ID (e.g., "kokoro")
+        **kwargs: Arguments passed to the engine constructor
+
+    Returns:
+        A callable backend that matches the old TTSBackend protocol
+
+    Raises:
+        KeyError: If plugin_id is not found
+        Exception: If engine creation fails
+    """
+    manager = get_plugin_manager()
+    engine = manager.create_engine(backend_id, **kwargs)
+    return CompatBackend(engine, **kwargs)

abogen/tts_plugin/plugin_manager.py

@@ -0,0 +1,153 @@
+"""Plugin Manager
+
+Provides a simple interface for consumers to access TTS engines via the
+new Plugin Architecture. Discovers, loads, and manages plugins from the
+plugins directory.
+
+Usage:
+    from abogen.tts_plugin.plugin_manager import get_plugin_manager
+
+    manager = get_plugin_manager()
+    engine = manager.create_engine("kokoro", lang_code="a", device="cpu")
+    session = engine.create_session()
+    try:
+        result = session.synthesize("Hello world")
+    finally:
+        session.dispose()
+"""
+
+from typing import Any, Dict, List, Optional, Type
+
+from abogen.tts_plugin.engine import Engine, EngineSession
+from abogen.tts_plugin.manifest import PluginManifest
+from abogen.tts_plugin.types import AudioFormat
+
+
+class PluginManager:
+    """Manages TTS plugins and provides a simple interface for consumers."""
+
+    def __init__(self) -> None:
+        self._plugins: Dict[str, dict] = {}
+        self._engines: Dict[str, Engine] = {}
+        self._loaded = False
+
+    def discover(self, plugins_dir: str = "plugins") -> None:
+        """Discover and load all plugins from the given directory."""
+        import os
+        from pathlib import Path
+        from abogen.tts_plugin.loader import load_plugin_from_dir
+
+        self._plugins.clear()
+        self._engines.clear()
+
+        plugins_path = Path(plugins_dir)
+        if not plugins_path.exists():
+            self._loaded = True
+            return
+
+        for entry in plugins_path.iterdir():
+            if entry.is_dir() and (entry / "__init__.py").exists():
+                try:
+                    result = load_plugin_from_dir(entry)
+                    if result.success and result.manifest is not None:
+                        self._plugins[result.manifest.id] = {
+                            "manifest": result.manifest,
+                            "create_engine": result.create_engine,
+                            "module": result.module,
+                        }
+                except Exception as e:
+                    # Log error but continue with other plugins
+                    print(f"Warning: Failed to load plugin from {entry}: {e}")
+
+        self._loaded = True
+
+    def _ensure_loaded(self) -> None:
+        """Ensure plugins have been discovered."""
+        if not self._loaded:
+            self.discover()
+
+    def list_plugins(self) -> List[PluginManifest]:
+        """Return manifests for all loaded plugins."""
+        self._ensure_loaded()
+        return [info["manifest"] for info in self._plugins.values()]
+
+    def get_plugin(self, plugin_id: str) -> Optional[dict]:
+        """Get plugin info by ID."""
+        self._ensure_loaded()
+        return self._plugins.get(plugin_id)
+
+    def has_plugin(self, plugin_id: str) -> bool:
+        """Check if a plugin is loaded."""
+        self._ensure_loaded()
+        return plugin_id in self._plugins
+
+    def create_engine(self, plugin_id: str, **kwargs: Any) -> Engine:
+        """Create an engine instance for the given plugin.
+
+        Args:
+            plugin_id: The plugin identifier (e.g., "kokoro")
+            **kwargs: Arguments passed to the engine constructor
+
+        Returns:
+            An Engine instance
+
+        Raises:
+            KeyError: If plugin_id is not found
+            Exception: If engine creation fails
+        """
+        self._ensure_loaded()
+
+        if plugin_id not in self._plugins:
+            raise KeyError(f"Plugin not found: {plugin_id}")
+
+        plugin_info = self._plugins[plugin_id]
+        create_engine_func = plugin_info["create_engine"]
+
+        # Create engine using the plugin's factory
+        engine = create_engine_func(**kwargs)
+        return engine
+
+    def get_or_create_engine(self, plugin_id: str, **kwargs: Any) -> Engine:
+        """Get an existing engine or create a new one.
+
+        Engines are cached by plugin_id. If you need multiple instances
+        with different parameters, use create_engine() directly.
+        """
+        self._ensure_loaded()
+
+        cache_key = plugin_id
+        if cache_key in self._engines:
+            return self._engines[cache_key]
+
+        engine = self.create_engine(plugin_id, **kwargs)
+        self._engines[cache_key] = engine
+        return engine
+
+    def dispose_all(self) -> None:
+        """Dispose all cached engines."""
+        for engine in self._engines.values():
+            try:
+                engine.dispose()
+            except Exception:
+                pass  # dispose() should never raise
+        self._engines.clear()
+
+
+# Global singleton
+_manager: Optional[PluginManager] = None
+
+
+def get_plugin_manager() -> PluginManager:
+    """Get the global PluginManager instance."""
+    global _manager
+    if _manager is None:
+        _manager = PluginManager()
+    return _manager
+
+
+def reset_plugin_manager() -> None:
+    """Reset the global PluginManager (for testing)."""
+    global _manager
+    if _manager is not None:
+        _manager.dispose_all()
+    _manager = None

abogen/webui/routes/utils/preview.py

@@ -1,234 +1,234 @@
-import io
-import threading
-from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple
-import numpy as np
-import soundfile as sf
-from flask import current_app, send_file
-from flask.typing import ResponseReturnValue
-
-
-SPLIT_PATTERN = r"\n+"
-SAMPLE_RATE = 24000
-
-_preview_pipelines: Dict[Tuple[str, str], Any] = {}
-_preview_pipeline_lock = threading.Lock()
-
-
-def _select_device() -> str:
-    import platform
-
-    try:
-        import torch  # type: ignore[import-not-found]
-    except Exception:
-        return "cpu"
-
-    system = platform.system()
-    if system == "Darwin" and platform.processor() == "arm":
-        try:
-            if torch.backends.mps.is_available():
-                return "mps"
-        except Exception:
-            pass
-        return "cpu"
-
-    try:
-        if torch.cuda.is_available():
-            return "cuda"
-    except Exception:
-        pass
-    return "cpu"
-
-
-def _resolve_pipeline(language: str, use_gpu: bool) -> Tuple[Any, bool]:
-    devices: List[str] = ["cpu"]
-    if use_gpu:
-        preferred = _select_device()
-        if preferred != "cpu":
-            devices.insert(0, preferred)
-
-    last_error: Optional[Exception] = None
-    for device in devices:
-        try:
-            return get_preview_pipeline(language, device), device != "cpu"
-        except Exception as exc:
-            last_error = exc
-
-    raise RuntimeError("Preview pipeline is unavailable") from last_error
-
-
-def _to_float32(audio_segment) -> np.ndarray:
-    if audio_segment is None:
-        return np.zeros(0, dtype="float32")
-
-    tensor = audio_segment
-    if hasattr(tensor, "detach"):
-        tensor = tensor.detach()
-    if hasattr(tensor, "cpu"):
-        try:
-            tensor = tensor.cpu()
-        except Exception:
-            pass
-    if hasattr(tensor, "numpy"):
-        return np.asarray(tensor.numpy(), dtype="float32").reshape(-1)
-    return np.asarray(tensor, dtype="float32").reshape(-1)
-
-def get_preview_pipeline(language: str, device: str) -> Any:
-    key = (language, device)
-    with _preview_pipeline_lock:
-        pipeline = _preview_pipelines.get(key)
-        if pipeline is not None:
-            return pipeline
-        from abogen.tts_backend_registry import create_backend
-
-        pipeline = create_backend("kokoro", lang_code=language, device=device)
-        _preview_pipelines[key] = pipeline
-        return pipeline
-
-def generate_preview_audio(
-    text: str,
-    voice_spec: str,
-    language: str,
-    speed: float,
-    use_gpu: bool,
-    tts_provider: str = "kokoro",
-    supertonic_total_steps: int = 5,
-    max_seconds: float = 8.0,
-    pronunciation_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
-    manual_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
-    speakers: Optional[Mapping[str, Any]] = None,
-) -> bytes:
-    if not text.strip():
-        raise ValueError("Preview text is required")
-
-    provider = (tts_provider or "kokoro").strip().lower()
-
-    # Apply pronunciation/manual overrides first so tokens like `Unfu*k` still match
-    # before any downstream normalization potentially strips punctuation.
-    source_text = text
-    if pronunciation_overrides or manual_overrides or speakers:
-        try:
-            from abogen.webui import conversion_runner as runner
-
-            class _PreviewJob:
-                def __init__(self):
-                    self.language = language
-                    self.voice = voice_spec
-                    self.speakers = speakers
-                    self.manual_overrides = list(manual_overrides or [])
-                    self.pronunciation_overrides = list(pronunciation_overrides or [])
-
-            job = _PreviewJob()
-            merged = runner._merge_pronunciation_overrides(job)
-            rules = runner._compile_pronunciation_rules(merged)
-            source_text = runner._apply_pronunciation_rules(source_text, rules)
-        except Exception:
-            current_app.logger.exception("Preview override application failed; using raw text")
-            source_text = text
-
-    normalized_text = source_text
-    if provider != "supertonic":
-        try:
-            from abogen.kokoro_text_normalization import normalize_for_pipeline
-
-            normalized_text = normalize_for_pipeline(source_text)
-        except Exception:
-            current_app.logger.exception("Preview normalization failed; using raw text")
-            normalized_text = source_text
-
-    if provider == "supertonic":
-        from abogen.tts_backend_registry import create_backend
-
-        pipeline = create_backend("supertonic", sample_rate=SAMPLE_RATE, auto_download=True, total_steps=supertonic_total_steps)
-        segments = pipeline(
-            normalized_text,
-            voice=voice_spec,
-            speed=speed,
-            split_pattern=SPLIT_PATTERN,
-            total_steps=supertonic_total_steps,
-        )
-    else:
-        pipeline, pipeline_uses_gpu = _resolve_pipeline(language, use_gpu)
-        if pipeline is None:
-            raise RuntimeError("Preview pipeline is unavailable")
-
-        voice_choice: Any = voice_spec
-        if voice_spec and "*" in voice_spec:
-            from abogen.voice_formulas import get_new_voice
-
-            voice_choice = get_new_voice(pipeline, voice_spec, pipeline_uses_gpu)
-
-        segments = pipeline(
-            normalized_text,
-            voice=voice_choice,
-            speed=speed,
-            split_pattern=SPLIT_PATTERN,
-        )
-
-    audio_chunks: List[np.ndarray] = []
-    accumulated = 0
-    max_samples = int(max(1.0, max_seconds) * SAMPLE_RATE)
-
-    for segment in segments:
-        graphemes = getattr(segment, "graphemes", "").strip()
-        if not graphemes:
-            continue
-        audio = _to_float32(getattr(segment, "audio", None))
-        if audio.size == 0:
-            continue
-        remaining = max_samples - accumulated
-        if remaining <= 0:
-            break
-        if audio.shape[0] > remaining:
-            audio = audio[:remaining]
-        audio_chunks.append(audio)
-        accumulated += audio.shape[0]
-        if accumulated >= max_samples:
-            break
-
-    if not audio_chunks:
-        raise RuntimeError("Preview could not be generated")
-
-    audio_data = np.concatenate(audio_chunks)
-    buffer = io.BytesIO()
-    sf.write(buffer, audio_data, SAMPLE_RATE, format="WAV")
-    return buffer.getvalue()
-
-def synthesize_preview(
-    text: str,
-    voice_spec: str,
-    language: str,
-    speed: float,
-    use_gpu: bool,
-    tts_provider: str = "kokoro",
-    supertonic_total_steps: int = 5,
-    max_seconds: float = 8.0,
-    pronunciation_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
-    manual_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
-    speakers: Optional[Mapping[str, Any]] = None,
-) -> ResponseReturnValue:
-    try:
-        audio_bytes = generate_preview_audio(
-            text=text,
-            voice_spec=voice_spec,
-            language=language,
-            speed=speed,
-            use_gpu=use_gpu,
-            tts_provider=tts_provider,
-            supertonic_total_steps=supertonic_total_steps,
-            max_seconds=max_seconds,
-            pronunciation_overrides=pronunciation_overrides,
-            manual_overrides=manual_overrides,
-            speakers=speakers,
-        )
-    except Exception as e:
-        raise e
-
-    buffer = io.BytesIO(audio_bytes)
-    response = send_file(
-        buffer,
-        mimetype="audio/wav",
-        as_attachment=False,
-        download_name="speaker_preview.wav",
-    )
-    response.headers["Cache-Control"] = "no-store"
-    return response
+import io
+import threading
+from typing import Any, Dict, Iterable, List, Mapping, Optional, Tuple
+import numpy as np
+import soundfile as sf
+from flask import current_app, send_file
+from flask.typing import ResponseReturnValue
+
+
+SPLIT_PATTERN = r"\n+"
+SAMPLE_RATE = 24000
+
+_preview_pipelines: Dict[Tuple[str, str], Any] = {}
+_preview_pipeline_lock = threading.Lock()
+
+
+def _select_device() -> str:
+    import platform
+
+    try:
+        import torch  # type: ignore[import-not-found]
+    except Exception:
+        return "cpu"
+
+    system = platform.system()
+    if system == "Darwin" and platform.processor() == "arm":
+        try:
+            if torch.backends.mps.is_available():
+                return "mps"
+        except Exception:
+            pass
+        return "cpu"
+
+    try:
+        if torch.cuda.is_available():
+            return "cuda"
+    except Exception:
+        pass
+    return "cpu"
+
+
+def _resolve_pipeline(language: str, use_gpu: bool) -> Tuple[Any, bool]:
+    devices: List[str] = ["cpu"]
+    if use_gpu:
+        preferred = _select_device()
+        if preferred != "cpu":
+            devices.insert(0, preferred)
+
+    last_error: Optional[Exception] = None
+    for device in devices:
+        try:
+            return get_preview_pipeline(language, device), device != "cpu"
+        except Exception as exc:
+            last_error = exc
+
+    raise RuntimeError("Preview pipeline is unavailable") from last_error
+
+
+def _to_float32(audio_segment) -> np.ndarray:
+    if audio_segment is None:
+        return np.zeros(0, dtype="float32")
+
+    tensor = audio_segment
+    if hasattr(tensor, "detach"):
+        tensor = tensor.detach()
+    if hasattr(tensor, "cpu"):
+        try:
+            tensor = tensor.cpu()
+        except Exception:
+            pass
+    if hasattr(tensor, "numpy"):
+        return np.asarray(tensor.numpy(), dtype="float32").reshape(-1)
+    return np.asarray(tensor, dtype="float32").reshape(-1)
+
+def get_preview_pipeline(language: str, device: str) -> Any:
+    key = (language, device)
+    with _preview_pipeline_lock:
+        pipeline = _preview_pipelines.get(key)
+        if pipeline is not None:
+            return pipeline
+        from abogen.tts_plugin.compat import create_backend
+
+        pipeline = create_backend("kokoro", lang_code=language, device=device)
+        _preview_pipelines[key] = pipeline
+        return pipeline
+
+def generate_preview_audio(
+    text: str,
+    voice_spec: str,
+    language: str,
+    speed: float,
+    use_gpu: bool,
+    tts_provider: str = "kokoro",
+    supertonic_total_steps: int = 5,
+    max_seconds: float = 8.0,
+    pronunciation_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
+    manual_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
+    speakers: Optional[Mapping[str, Any]] = None,
+) -> bytes:
+    if not text.strip():
+        raise ValueError("Preview text is required")
+
+    provider = (tts_provider or "kokoro").strip().lower()
+
+    # Apply pronunciation/manual overrides first so tokens like `Unfu*k` still match
+    # before any downstream normalization potentially strips punctuation.
+    source_text = text
+    if pronunciation_overrides or manual_overrides or speakers:
+        try:
+            from abogen.webui import conversion_runner as runner
+
+            class _PreviewJob:
+                def __init__(self):
+                    self.language = language
+                    self.voice = voice_spec
+                    self.speakers = speakers
+                    self.manual_overrides = list(manual_overrides or [])
+                    self.pronunciation_overrides = list(pronunciation_overrides or [])
+
+            job = _PreviewJob()
+            merged = runner._merge_pronunciation_overrides(job)
+            rules = runner._compile_pronunciation_rules(merged)
+            source_text = runner._apply_pronunciation_rules(source_text, rules)
+        except Exception:
+            current_app.logger.exception("Preview override application failed; using raw text")
+            source_text = text
+
+    normalized_text = source_text
+    if provider != "supertonic":
+        try:
+            from abogen.kokoro_text_normalization import normalize_for_pipeline
+
+            normalized_text = normalize_for_pipeline(source_text)
+        except Exception:
+            current_app.logger.exception("Preview normalization failed; using raw text")
+            normalized_text = source_text
+
+    if provider == "supertonic":
+        from abogen.tts_plugin.compat import create_backend
+
+        pipeline = create_backend("supertonic", sample_rate=SAMPLE_RATE, auto_download=True, total_steps=supertonic_total_steps)
+        segments = pipeline(
+            normalized_text,
+            voice=voice_spec,
+            speed=speed,
+            split_pattern=SPLIT_PATTERN,
+            total_steps=supertonic_total_steps,
+        )
+    else:
+        pipeline, pipeline_uses_gpu = _resolve_pipeline(language, use_gpu)
+        if pipeline is None:
+            raise RuntimeError("Preview pipeline is unavailable")
+
+        voice_choice: Any = voice_spec
+        if voice_spec and "*" in voice_spec:
+            from abogen.voice_formulas import get_new_voice
+
+            voice_choice = get_new_voice(pipeline, voice_spec, pipeline_uses_gpu)
+
+        segments = pipeline(
+            normalized_text,
+            voice=voice_choice,
+            speed=speed,
+            split_pattern=SPLIT_PATTERN,
+        )
+
+    audio_chunks: List[np.ndarray] = []
+    accumulated = 0
+    max_samples = int(max(1.0, max_seconds) * SAMPLE_RATE)
+
+    for segment in segments:
+        graphemes = getattr(segment, "graphemes", "").strip()
+        if not graphemes:
+            continue
+        audio = _to_float32(getattr(segment, "audio", None))
+        if audio.size == 0:
+            continue
+        remaining = max_samples - accumulated
+        if remaining <= 0:
+            break
+        if audio.shape[0] > remaining:
+            audio = audio[:remaining]
+        audio_chunks.append(audio)
+        accumulated += audio.shape[0]
+        if accumulated >= max_samples:
+            break
+
+    if not audio_chunks:
+        raise RuntimeError("Preview could not be generated")
+
+    audio_data = np.concatenate(audio_chunks)
+    buffer = io.BytesIO()
+    sf.write(buffer, audio_data, SAMPLE_RATE, format="WAV")
+    return buffer.getvalue()
+
+def synthesize_preview(
+    text: str,
+    voice_spec: str,
+    language: str,
+    speed: float,
+    use_gpu: bool,
+    tts_provider: str = "kokoro",
+    supertonic_total_steps: int = 5,
+    max_seconds: float = 8.0,
+    pronunciation_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
+    manual_overrides: Optional[Iterable[Mapping[str, Any]]] = None,
+    speakers: Optional[Mapping[str, Any]] = None,
+) -> ResponseReturnValue:
+    try:
+        audio_bytes = generate_preview_audio(
+            text=text,
+            voice_spec=voice_spec,
+            language=language,
+            speed=speed,
+            use_gpu=use_gpu,
+            tts_provider=tts_provider,
+            supertonic_total_steps=supertonic_total_steps,
+            max_seconds=max_seconds,
+            pronunciation_overrides=pronunciation_overrides,
+            manual_overrides=manual_overrides,
+            speakers=speakers,
+        )
+    except Exception as e:
+        raise e
+
+    buffer = io.BytesIO(audio_bytes)
+    response = send_file(
+        buffer,
+        mimetype="audio/wav",
+        as_attachment=False,
+        download_name="speaker_preview.wav",
+    )
+    response.headers["Cache-Control"] = "no-store"
+    return response

tests/contracts/test_integration_pr5.py

@@ -0,0 +1,400 @@
+"""Integration tests for PR #5: Migrate First Consumer to Plugin Architecture.
+
+These tests verify:
+1. Consumer Flow Test: consumer → plugin → engine → session → synthesis → result
+2. Lifecycle Test: dispose, no leaks, error handling
+3. Regression Test: old path vs new path equivalence
+
+Tests use mock plugins to avoid requiring real TTS dependencies.
+"""
+
+import pytest
+from typing import Any, Iterator
+from unittest.mock import MagicMock, patch
+
+import numpy as np
+
+from abogen.tts_plugin.engine import Engine, EngineSession
+from abogen.tts_plugin.errors import EngineError
+from abogen.tts_plugin.plugin_manager import PluginManager, get_plugin_manager, reset_plugin_manager
+from abogen.tts_plugin.compat import CompatBackend, create_backend
+from abogen.tts_plugin.types import (
+    AudioFormat,
+    Duration,
+    ParameterValues,
+    SynthesisRequest,
+    SynthesizedAudio,
+    VoiceSelection,
+)
+
+
+class MockEngineSession:
+    """Mock EngineSession that records calls for verification."""
+    
+    def __init__(self):
+        self._disposed = False
+        self.synthesize_calls = []
+    
+    def synthesize(self, request: SynthesisRequest) -> SynthesizedAudio:
+        if self._disposed:
+            raise EngineError("Session disposed")
+        
+        self.synthesize_calls.append(request)
+        
+        # Return fake audio
+        audio = np.ones(1000, dtype=np.float32) * 0.5
+        return SynthesizedAudio(
+            data=audio.tobytes(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+            duration=Duration(seconds=1000 / 24000),
+        )
+    
+    def dispose(self) -> None:
+        self._disposed = True
+
+
+class MockEngine:
+    """Mock Engine that creates MockEngineSessions."""
+    
+    def __init__(self, **kwargs):
+        self.kwargs = kwargs
+        self._disposed = False
+        self.sessions_created = []
+    
+    def createSession(self) -> MockEngineSession:
+        if self._disposed:
+            raise EngineError("Engine disposed")
+        session = MockEngineSession()
+        self.sessions_created.append(session)
+        return session
+    
+    def dispose(self) -> None:
+        self._disposed = True
+
+
+def create_mock_plugin(create_engine_func=None):
+    """Helper to create a mock plugin module."""
+    if create_engine_func is None:
+        create_engine_func = lambda **kwargs: MockEngine(**kwargs)
+    
+    from abogen.tts_plugin.manifest import PluginManifest, EngineManifest
+    
+    manifest = PluginManifest(
+        id="mock_tts",
+        name="Mock TTS",
+        version="1.0.0",
+        api_version="1.0",
+        description="Mock TTS for testing",
+        author="Test",
+        capabilities=(),
+        requires=None,
+        engine=EngineManifest(
+            voiceSources=(),
+            parameters=(),
+            audioFormats=(),
+        ),
+    )
+    
+    return {
+        "PLUGIN_MANIFEST": manifest,
+        "MODEL_REQUIREMENTS": [],
+        "create_engine": create_mock_plugin_engine if create_engine_func is None else create_engine_func,
+    }
+
+
+def create_mock_plugin_engine(**kwargs):
+    """Default mock plugin engine factory."""
+    return MockEngine(**kwargs)
+
+
+class TestConsumerFlow:
+    """Consumer Flow Test: consumer → plugin → engine → session → synthesis → result"""
+    
+    def test_full_consumer_flow(self):
+        """Verify complete flow from consumer to audio output."""
+        manager = PluginManager()
+        
+        # Register mock plugin
+        mock_plugin = create_mock_plugin()
+        manager._plugins["mock_tts"] = mock_plugin
+        manager._loaded = True
+        
+        # Step 1: Consumer gets plugin
+        assert manager.has_plugin("mock_tts") is True
+        
+        # Step 2: Plugin creates engine
+        engine = manager.create_engine("mock_tts")
+        assert engine is not None
+        assert isinstance(engine, MockEngine)
+        
+        # Step 3: Engine creates session
+        session = engine.createSession()
+        assert session is not None
+        assert isinstance(session, MockEngineSession)
+        
+        # Step 4: Session synthesizes
+        request = SynthesisRequest(
+            text="Hello world",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(values={"speed": 1.0}),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        result = session.synthesize(request)
+        
+        # Step 5: Result returned
+        assert result is not None
+        assert isinstance(result, SynthesizedAudio)
+        assert len(result.data) > 0
+        assert result.format.mime == "audio/wav"
+        assert result.duration.seconds > 0
+    
+    def test_consumer_flow_via_compat_adapter(self):
+        """Verify flow through compatibility adapter matches direct flow."""
+        manager = PluginManager()
+        
+        # Register mock plugin
+        mock_plugin = create_mock_plugin()
+        manager._plugins["mock_tts"] = mock_plugin
+        manager._loaded = True
+        
+        # Use compat adapter
+        with patch("abogen.tts_plugin.compat.get_plugin_manager", return_value=manager):
+            backend = create_backend("mock_tts")
+            
+            # Call like old TTSBackend
+            segments = list(backend("Hello world", voice="default", speed=1.0))
+            
+            # Verify result
+            assert len(segments) >= 1
+            segment = segments[0]
+            assert hasattr(segment, "graphemes")
+            assert hasattr(segment, "audio")
+            assert segment.graphemes == "Hello world"
+
+
+class TestLifecycle:
+    """Lifecycle Test: dispose, no leaks, error handling"""
+    
+    def test_session_dispose_is_idempotent(self):
+        """dispose() can be called multiple times safely."""
+        session = MockEngineSession()
+        
+        session.dispose()
+        session.dispose()  # Should not raise
+        assert session._disposed is True
+    
+    def test_session_synthesize_after_dispose_raises(self):
+        """synthesize() after dispose() raises EngineError."""
+        session = MockEngineSession()
+        session.dispose()
+        
+        request = SynthesisRequest(
+            text="test",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        
+        with pytest.raises(EngineError):
+            session.synthesize(request)
+    
+    def test_engine_dispose_is_idempotent(self):
+        """Engine dispose() can be called multiple times safely."""
+        engine = MockEngine()
+        
+        engine.dispose()
+        engine.dispose()  # Should not raise
+        assert engine._disposed is True
+    
+    def test_engine_create_session_after_dispose_raises(self):
+        """createSession() after dispose() raises EngineError."""
+        engine = MockEngine()
+        engine.dispose()
+        
+        with pytest.raises(EngineError):
+            engine.createSession()
+    
+    def test_full_lifecycle(self):
+        """Test complete lifecycle: create → use → dispose."""
+        engine = MockEngine()
+        
+        # Create and use session
+        session = engine.createSession()
+        request = SynthesisRequest(
+            text="test",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        result = session.synthesize(request)
+        assert len(result.data) > 0
+        
+        # Dispose session
+        session.dispose()
+        assert session._disposed is True
+        
+        # Dispose engine
+        engine.dispose()
+        assert engine._disposed is True
+    
+    def test_no_session_leak_on_engine_dispose(self):
+        """Engine can be disposed even if sessions were created."""
+        engine = MockEngine()
+        
+        # Create multiple sessions
+        session1 = engine.createSession()
+        session2 = engine.createSession()
+        
+        # Use sessions
+        request = SynthesisRequest(
+            text="test",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        session1.synthesize(request)
+        session2.synthesize(request)
+        
+        # Dispose engine (sessions still exist but engine is disposed)
+        engine.dispose()
+        assert engine._disposed is True
+        
+        # Sessions can still be used (they hold reference to pipeline)
+        result = session1.synthesize(request)
+        assert len(result.data) > 0
+    
+    def test_error_handling_in_synthesis(self):
+        """Error during synthesis is handled correctly."""
+        class FailingSession:
+            def synthesize(self, request):
+                raise EngineError("Synthesis failed")
+            
+            def dispose(self):
+                pass
+        
+        session = FailingSession()
+        request = SynthesisRequest(
+            text="test",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        
+        with pytest.raises(EngineError, match="Synthesis failed"):
+            session.synthesize(request)
+
+
+class TestRegression:
+    """Regression Test: old path vs new path equivalence"""
+    
+    def test_old_path_vs_new_path_same_result(self):
+        """Both paths should produce equivalent results."""
+        # Setup mock plugin
+        manager = PluginManager()
+        mock_plugin = create_mock_plugin()
+        manager._plugins["mock_tts"] = mock_plugin
+        manager._loaded = True
+        
+        # New path: Plugin Manager → Engine → Session → Synthesis
+        with patch("abogen.tts_plugin.compat.get_plugin_manager", return_value=manager):
+            new_backend = create_backend("mock_tts")
+            new_segments = list(new_backend("Hello world", voice="default", speed=1.0))
+        
+        # Old path: Direct MockEngine (simulating old registry)
+        old_engine = MockEngine()
+        old_session = old_engine.createSession()
+        request = SynthesisRequest(
+            text="Hello world",
+            voice=VoiceSelection(source="builtin", key="default"),
+            parameters=ParameterValues(values={"speed": 1.0}),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+        )
+        old_result = old_session.synthesize(request)
+        
+        # Compare results
+        # New path returns segments, old path returns SynthesizedAudio
+        # But both should have valid audio data
+        assert len(new_segments) >= 1
+        assert len(old_result.data) > 0
+        
+        # Both should have same format
+        assert new_segments[0].audio.dtype == np.float32
+    
+    def test_compat_adapter_matches_old_interface(self):
+        """Compat adapter should match old TTSBackend interface."""
+        manager = PluginManager()
+        mock_plugin = create_mock_plugin()
+        manager._plugins["mock_tts"] = mock_plugin
+        manager._loaded = True
+        
+        with patch("abogen.tts_plugin.compat.get_plugin_manager", return_value=manager):
+            backend = create_backend("mock_tts", lang_code="a", device="cpu")
+            
+            # Old interface: pipeline(text, voice=..., speed=..., split_pattern=...)
+            segments = list(backend(
+                "Hello world",
+                voice="af_heart",
+                speed=1.0,
+                split_pattern=r"\n+"
+            ))
+            
+            # Should return segments with graphemes and audio
+            assert len(segments) >= 1
+            segment = segments[0]
+            assert segment.graphemes == "Hello world"
+            assert isinstance(segment.audio, np.ndarray)
+            assert segment.audio.dtype == np.float32
+            assert len(segment.audio) > 0
+
+
+class TestPluginManagerIntegration:
+    """Integration tests for PluginManager."""
+    
+    def test_plugin_manager_singleton_pattern(self):
+        """Global plugin manager follows singleton pattern."""
+        reset_plugin_manager()
+        
+        manager1 = get_plugin_manager()
+        manager2 = get_plugin_manager()
+        
+        assert manager1 is manager2
+        
+        reset_plugin_manager()
+        
+        manager3 = get_plugin_manager()
+        assert manager1 is not manager3
+    
+    def test_plugin_manager_discover_plugins(self):
+        """Plugin manager can discover plugins from directory."""
+        manager = PluginManager()
+        
+        # Discover from test plugins directory
+        manager.discover("tests/plugins")
+        
+        # Should find valid_plugin
+        # (This depends on test plugins existing)
+        plugins = manager.list_plugins()
+        assert isinstance(plugins, list)
+    
+    def test_plugin_manager_dispose_all(self):
+        """Plugin manager can dispose all cached engines."""
+        manager = PluginManager()
+        
+        # Register mock plugin
+        mock_plugin = create_mock_plugin()
+        manager._plugins["mock_tts"] = mock_plugin
+        manager._loaded = True
+        
+        # Create engines
+        engine1 = manager.get_or_create_engine("mock_tts")
+        engine2 = manager.get_or_create_engine("mock_tts")
+        
+        # Dispose all
+        manager.dispose_all()
+        
+        # Engines should be disposed
+        assert engine1._disposed is True
+        assert engine2._disposed is True
+        
+        # Cache should be empty
+        assert len(manager._engines) == 0

tests/contracts/test_plugin_manager_contract.py

@@ -0,0 +1,264 @@
+"""Integration tests for Plugin Manager and compatibility adapter."""
+
+import pytest
+from unittest.mock import MagicMock, patch
+
+from abogen.tts_plugin.plugin_manager import PluginManager, get_plugin_manager, reset_plugin_manager
+from abogen.tts_plugin.compat import CompatBackend, create_backend
+from abogen.tts_plugin.engine import Engine, EngineSession
+from abogen.tts_plugin.types import SynthesisRequest, SynthesizedAudio, AudioFormat
+
+
+class FakeEngine:
+    """Fake Engine for testing."""
+    
+    def __init__(self, **kwargs):
+        self.kwargs = kwargs
+        self._disposed = False
+    
+    def createSession(self):
+        return FakeEngineSession()
+    
+    def dispose(self):
+        self._disposed = True
+    
+    @property
+    def manifest(self):
+        return MagicMock()
+
+
+class FakeEngineSession:
+    """Fake EngineSession for testing."""
+    
+    def __init__(self):
+        self._disposed = False
+    
+    def synthesize(self, request):
+        # Return fake audio
+        import numpy as np
+        from abogen.tts_plugin.types import AudioFormat, Duration, SynthesizedAudio
+        
+        audio = np.zeros(1000, dtype=np.float32)
+        return SynthesizedAudio(
+            data=audio.tobytes(),
+            format=AudioFormat(mime="audio/wav", extension="wav"),
+            duration=Duration(seconds=0.04167),  # 1000 samples / 24000 Hz
+        )
+    
+    def dispose(self):
+        self._disposed = True
+
+
+class TestPluginManager:
+    """Test PluginManager functionality."""
+    
+    def test_plugin_manager_creation(self):
+        """PluginManager can be created."""
+        manager = PluginManager()
+        assert manager is not None
+    
+    def test_plugin_manager_list_discovers_plugins(self):
+        """PluginManager discovers plugins from plugins directory."""
+        manager = PluginManager()
+        manager.discover("plugins")
+        plugins = manager.list_plugins()
+        # Should discover kokoro plugin if it exists
+        assert isinstance(plugins, list)
+    
+    def test_plugin_manager_has_plugin_after_discover(self):
+        """PluginManager reports plugins after discovery."""
+        manager = PluginManager()
+        manager.discover("plugins")
+        # kokoro plugin should be discovered if plugins/kokoro exists
+        # This is expected behavior
+        assert isinstance(manager._plugins, dict)
+    
+    def test_plugin_manager_get_plugin_after_discover(self):
+        """PluginManager returns plugin info after discovery."""
+        manager = PluginManager()
+        manager.discover("plugins")
+        # kokoro plugin should be discovered if plugins/kokoro exists
+        assert isinstance(manager._plugins, dict)
+    
+    def test_plugin_manager_create_engine_not_found(self):
+        """PluginManager raises KeyError for unknown plugins."""
+        manager = PluginManager()
+        with pytest.raises(KeyError, match="Plugin not found"):
+            manager.create_engine("nonexistent")
+    
+    def test_plugin_manager_discover_with_empty_dir(self):
+        """PluginManager handles missing plugins directory."""
+        manager = PluginManager()
+        manager.discover("/nonexistent/path")
+        plugins = manager.list_plugins()
+        assert plugins == []
+    
+    def test_global_plugin_manager_singleton(self):
+        """Global PluginManager is a singleton."""
+        reset_plugin_manager()
+        manager1 = get_plugin_manager()
+        manager2 = get_plugin_manager()
+        assert manager1 is manager2
+        reset_plugin_manager()
+    
+    def test_reset_plugin_manager(self):
+        """reset_plugin_manager clears the singleton."""
+        manager1 = get_plugin_manager()
+        reset_plugin_manager()
+        manager2 = get_plugin_manager()
+        assert manager1 is not manager2
+        reset_plugin_manager()
+
+
+class TestCompatBackend:
+    """Test CompatBackend functionality."""
+    
+    def test_compat_backend_creation(self):
+        """CompatBackend can be created."""
+        engine = FakeEngine()
+        backend = CompatBackend(engine)
+        assert backend is not None
+    
+    def test_compat_backend_callable(self):
+        """CompatBackend is callable like old TTSBackend."""
+        engine = FakeEngine()
+        backend = CompatBackend(engine)
+        
+        # Should be callable
+        assert callable(backend)
+    
+    def test_compat_backend_synthesize(self):
+        """CompatBackend can synthesize text."""
+        engine = FakeEngine()
+        backend = CompatBackend(engine)
+        
+        # Call the backend
+        segments = list(backend("Hello world", voice="default", speed=1.0))
+        
+        # Should return at least one segment
+        assert len(segments) >= 1
+        
+        # Segment should have graphemes and audio
+        segment = segments[0]
+        assert hasattr(segment, "graphemes")
+        assert hasattr(segment, "audio")
+        assert segment.graphemes == "Hello world"
+    
+    def test_compat_backend_dispose(self):
+        """CompatBackend can be disposed."""
+        engine = FakeEngine()
+        backend = CompatBackend(engine)
+        
+        # Create a session by calling
+        list(backend("test"))
+        
+        # Dispose should not raise
+        backend.dispose()
+        
+        # Double dispose should be safe
+        backend.dispose()
+
+
+class TestCreateBackendCompat:
+    """Test create_backend compatibility function."""
+    
+    def test_create_backend_returns_callable(self):
+        """create_backend returns a callable backend."""
+        # Mock the plugin manager
+        with patch("abogen.tts_plugin.compat.get_plugin_manager") as mock_get_manager:
+            mock_manager = MagicMock()
+            mock_get_manager.return_value = mock_manager
+            
+            mock_engine = FakeEngine()
+            mock_manager.create_engine.return_value = mock_engine
+            
+            backend = create_backend("kokoro", lang_code="a", device="cpu")
+            
+            assert callable(backend)
+            mock_manager.create_engine.assert_called_once_with("kokoro", lang_code="a", device="cpu")
+    
+    def test_create_backend_raises_for_unknown_plugin(self):
+        """create_backend raises KeyError for unknown plugins."""
+        with patch("abogen.tts_plugin.compat.get_plugin_manager") as mock_get_manager:
+            mock_manager = MagicMock()
+            mock_get_manager.return_value = mock_manager
+            mock_manager.create_engine.side_effect = KeyError("Plugin not found")
+            
+            with pytest.raises(KeyError):
+                create_backend("nonexistent")
+
+
+class TestPluginManagerWithFakePlugins:
+    """Test PluginManager with fake plugin loading."""
+    
+    def test_plugin_manager_create_engine_from_plugin(self):
+        """PluginManager creates engine from loaded plugin."""
+        manager = PluginManager()
+        
+        # Manually add a fake plugin
+        def fake_create_engine(**kwargs):
+            return FakeEngine(**kwargs)
+        
+        manager._plugins["fake"] = {
+            "manifest": MagicMock(),
+            "create_engine": fake_create_engine,
+        }
+        manager._loaded = True
+        
+        # Create engine
+        engine = manager.create_engine("fake", param="value")
+        
+        assert isinstance(engine, FakeEngine)
+        assert engine.kwargs == {"param": "value"}
+    
+    def test_plugin_manager_get_or_create_engine(self):
+        """PluginManager caches engines."""
+        manager = PluginManager()
+        
+        call_count = 0
+        
+        def fake_create_engine(**kwargs):
+            nonlocal call_count
+            call_count += 1
+            return FakeEngine(**kwargs)
+        
+        manager._plugins["fake"] = {
+            "manifest": MagicMock(),
+            "create_engine": fake_create_engine,
+        }
+        manager._loaded = True
+        
+        # Get engine twice
+        engine1 = manager.get_or_create_engine("fake")
+        engine2 = manager.get_or_create_engine("fake")
+        
+        # Should be same instance
+        assert engine1 is engine2
+        assert call_count == 1
+    
+    def test_plugin_manager_dispose_all(self):
+        """PluginManager disposes all cached engines."""
+        manager = PluginManager()
+        
+        def fake_create_engine(**kwargs):
+            return FakeEngine(**kwargs)
+        
+        manager._plugins["fake"] = {
+            "manifest": MagicMock(),
+            "create_engine": fake_create_engine,
+        }
+        manager._loaded = True
+        
+        # Create and cache engines
+        engine1 = manager.get_or_create_engine("fake")
+        engine2 = manager.get_or_create_engine("fake")
+        
+        # Dispose all
+        manager.dispose_all()
+        
+        # Engines should be disposed
+        assert engine1._disposed is True
+        assert engine2._disposed is True
+        
+        # Cache should be empty
+        assert len(manager._engines) == 0

tests/test_preview_applies_manual_overrides.py

@@ -1,60 +1,60 @@
-from abogen.webui.routes.utils import preview
-
-
-def test_preview_applies_manual_override_before_normalization(monkeypatch):
-    # Don't run real TTS/normalization; just exercise the override stage by
-    # forcing provider=kokoro and then stubbing normalize_for_pipeline.
-
-    monkeypatch.setattr(preview, "get_preview_pipeline", lambda language, device: None)
-
-    # Stub normalize_for_pipeline to be identity; we only care that overrides run.
-    class _Norm:
-        @staticmethod
-        def normalize_for_pipeline(text):
-            return text
-
-    monkeypatch.setitem(
-        __import__("sys").modules, "abogen.kokoro_text_normalization", _Norm
-    )
-
-    # 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 create_backend to capture input.
-    captured = {}
-
-    class DummyPipeline:
-        def __init__(self, **kwargs):
-            pass
-
-        def __call__(self, text, **kwargs):
-            captured["text"] = text
-            return iter(())
-
-    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(
-            text="He said Unfu*k loudly.",
-            voice_spec="M1",
-            language="en",
-            speed=1.0,
-            use_gpu=False,
-            tts_provider="supertonic",
-            manual_overrides=[{"token": "Unfu*k", "pronunciation": "Unfuck"}],
-        )
-    except Exception:
-        # generate_preview_audio will raise because no audio chunks; that's fine.
-        pass
-
-    assert "text" in captured
-    assert "Unfuck" in captured["text"]
-    assert "Unfu*k" not in captured["text"]
+from abogen.webui.routes.utils import preview
+
+
+def test_preview_applies_manual_override_before_normalization(monkeypatch):
+    # Don't run real TTS/normalization; just exercise the override stage by
+    # forcing provider=kokoro and then stubbing normalize_for_pipeline.
+
+    monkeypatch.setattr(preview, "get_preview_pipeline", lambda language, device: None)
+
+    # Stub normalize_for_pipeline to be identity; we only care that overrides run.
+    class _Norm:
+        @staticmethod
+        def normalize_for_pipeline(text):
+            return text
+
+    monkeypatch.setitem(
+        __import__("sys").modules, "abogen.kokoro_text_normalization", _Norm
+    )
+
+    # 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 create_backend to capture input.
+    captured = {}
+
+    class DummyPipeline:
+        def __init__(self, **kwargs):
+            pass
+
+        def __call__(self, text, **kwargs):
+            captured["text"] = text
+            return iter(())
+
+    from abogen.tts_plugin import compat
+
+    original_create_backend = compat.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(compat, "create_backend", _mock_create_backend)
+
+    try:
+        preview.generate_preview_audio(
+            text="He said Unfu*k loudly.",
+            voice_spec="M1",
+            language="en",
+            speed=1.0,
+            use_gpu=False,
+            tts_provider="supertonic",
+            manual_overrides=[{"token": "Unfu*k", "pronunciation": "Unfuck"}],
+        )
+    except Exception:
+        # generate_preview_audio will raise because no audio chunks; that's fine.
+        pass
+
+    assert "text" in captured
+    assert "Unfuck" in captured["text"]
+    assert "Unfu*k" not in captured["text"]