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| """Kokoro TTS provider implementation.""" | |
| import logging | |
| import numpy as np | |
| import soundfile as sf | |
| import io | |
| from typing import Iterator, TYPE_CHECKING | |
| if TYPE_CHECKING: | |
| from ...domain.models.speech_synthesis_request import SpeechSynthesisRequest | |
| from ..base.tts_provider_base import TTSProviderBase | |
| from ...domain.exceptions import SpeechSynthesisException | |
| logger = logging.getLogger(__name__) | |
| # Flag to track Kokoro availability | |
| KOKORO_AVAILABLE = False | |
| # Try to import Kokoro | |
| try: | |
| from kokoro import KPipeline | |
| KOKORO_AVAILABLE = True | |
| logger.info("Kokoro TTS engine is available") | |
| except ImportError: | |
| logger.warning("Kokoro TTS engine is not available") | |
| except Exception as e: | |
| logger.error(f"Kokoro import failed with unexpected error: {str(e)}") | |
| KOKORO_AVAILABLE = False | |
| class KokoroTTSProvider(TTSProviderBase): | |
| """Kokoro TTS provider implementation.""" | |
| def __init__(self, lang_code: str = 'z'): | |
| """Initialize the Kokoro TTS provider.""" | |
| super().__init__( | |
| provider_name="Kokoro", | |
| supported_languages=['en', 'z'] # Kokoro supports English and multilingual | |
| ) | |
| self.lang_code = lang_code | |
| self.pipeline = None | |
| def _ensure_pipeline(self): | |
| """Ensure the pipeline is loaded.""" | |
| if self.pipeline is None and KOKORO_AVAILABLE: | |
| try: | |
| self.pipeline = KPipeline(lang_code=self.lang_code) | |
| logger.info("Kokoro pipeline successfully loaded") | |
| except Exception as e: | |
| logger.error(f"Failed to initialize Kokoro pipeline: {str(e)}") | |
| self.pipeline = None | |
| return self.pipeline is not None | |
| def is_available(self) -> bool: | |
| """Check if Kokoro TTS is available.""" | |
| return KOKORO_AVAILABLE and self._ensure_pipeline() | |
| def get_available_voices(self) -> list[str]: | |
| """Get available voices for Kokoro.""" | |
| # Common Kokoro voices based on the original implementation | |
| return [ | |
| 'af_heart', 'af_bella', 'af_sarah', 'af_nicole', | |
| 'am_adam', 'am_michael', 'bf_emma', 'bf_isabella' | |
| ] | |
| def _generate_audio(self, request: 'SpeechSynthesisRequest') -> tuple[bytes, int]: | |
| """Generate audio using Kokoro TTS.""" | |
| if not self.is_available(): | |
| raise SpeechSynthesisException("Kokoro TTS engine is not available") | |
| try: | |
| # Extract parameters from request | |
| text = request.text_content.text | |
| voice = request.voice_settings.voice_id | |
| speed = request.voice_settings.speed | |
| # Generate speech using Kokoro | |
| generator = self.pipeline(text, voice=voice, speed=speed) | |
| for _, _, audio in generator: | |
| # Convert numpy array to bytes | |
| audio_bytes = self._numpy_to_bytes(audio, sample_rate=24000) | |
| return audio_bytes, 24000 | |
| raise SpeechSynthesisException("Kokoro failed to generate audio") | |
| except Exception as e: | |
| self._handle_provider_error(e, "audio generation") | |
| def _generate_audio_stream(self, request: 'SpeechSynthesisRequest') -> Iterator[tuple[bytes, int, bool]]: | |
| """Generate audio stream using Kokoro TTS.""" | |
| if not self.is_available(): | |
| raise SpeechSynthesisException("Kokoro TTS engine is not available") | |
| try: | |
| # Extract parameters from request | |
| text = request.text_content.text | |
| voice = request.voice_settings.voice_id | |
| speed = request.voice_settings.speed | |
| # Generate speech stream using Kokoro | |
| generator = self.pipeline(text, voice=voice, speed=speed) | |
| chunk_count = 0 | |
| for _, _, audio in generator: | |
| chunk_count += 1 | |
| # Convert numpy array to bytes | |
| audio_bytes = self._numpy_to_bytes(audio, sample_rate=24000) | |
| # Assume this is the final chunk for now (Kokoro typically generates one chunk) | |
| is_final = True | |
| yield audio_bytes, 24000, is_final | |
| except Exception as e: | |
| self._handle_provider_error(e, "streaming audio generation") | |
| def _numpy_to_bytes(self, audio_array: np.ndarray, sample_rate: int) -> bytes: | |
| """Convert numpy audio array to bytes.""" | |
| try: | |
| # Create an in-memory buffer | |
| buffer = io.BytesIO() | |
| # Write audio data to buffer as WAV | |
| sf.write(buffer, audio_array, sample_rate, format='WAV') | |
| # Get bytes from buffer | |
| buffer.seek(0) | |
| return buffer.read() | |
| except Exception as e: | |
| raise SpeechSynthesisException(f"Failed to convert audio to bytes: {str(e)}") from e |