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import logging | |
import numpy as np | |
import soundfile as sf | |
from typing import Optional, Generator, Tuple | |
from utils.tts_base import TTSBase | |
# Configure logging | |
logger = logging.getLogger(__name__) | |
# Flag to track CosyVoice2 availability | |
COSYVOICE2_AVAILABLE = False | |
DEFAULT_SAMPLE_RATE = 24000 | |
# Try to import CosyVoice2 dependencies | |
try: | |
import torch | |
import torchaudio | |
# Import CosyVoice2 from the correct package | |
# Based on https://github.com/FunAudioLLM/CosyVoice | |
from cosyvoice.cli.cosyvoice import CosyVoice | |
COSYVOICE2_AVAILABLE = True | |
logger.info("CosyVoice2 TTS engine is available") | |
except ImportError as e: | |
logger.warning(f"CosyVoice2 TTS engine is not available - ImportError: {str(e)}") | |
COSYVOICE2_AVAILABLE = False | |
except ModuleNotFoundError as e: | |
logger.warning(f"CosyVoice2 TTS engine is not available - ModuleNotFoundError: {str(e)}") | |
COSYVOICE2_AVAILABLE = False | |
def _get_model(): | |
"""Lazy-load the CosyVoice2 model | |
Returns: | |
CosyVoice2 or None: The CosyVoice2 model or None if not available | |
""" | |
if not COSYVOICE2_AVAILABLE: | |
logger.warning("CosyVoice2 TTS engine is not available") | |
return None | |
try: | |
import torch | |
import torchaudio | |
from cosyvoice.cli.cosyvoice import CosyVoice | |
# Initialize the model with correct path | |
model = CosyVoice('pretrained_models/CosyVoice-300M') | |
logger.info("CosyVoice2 model successfully loaded") | |
return model | |
except ImportError as e: | |
logger.error(f"Failed to import CosyVoice2 dependencies: {str(e)}") | |
return None | |
except FileNotFoundError as e: | |
logger.error(f"Failed to load CosyVoice2 model files: {str(e)}") | |
return None | |
except Exception as e: | |
logger.error(f"Failed to initialize CosyVoice2 model: {str(e)}") | |
return None | |
class CosyVoice2TTS(TTSBase): | |
"""CosyVoice2 TTS engine implementation | |
This engine uses the CosyVoice2 model for TTS generation. | |
""" | |
def __init__(self, lang_code: str = 'z'): | |
"""Initialize the CosyVoice2 TTS engine | |
Args: | |
lang_code (str): Language code for the engine | |
""" | |
super().__init__(lang_code) | |
self.model = None | |
def _ensure_model(self): | |
"""Ensure the model is loaded | |
Returns: | |
bool: True if model is available, False otherwise | |
""" | |
if self.model is None: | |
self.model = _get_model() | |
return self.model is not None | |
def generate_speech(self, text: str, voice: str = 'default', speed: float = 1.0) -> Optional[str]: | |
"""Generate speech using CosyVoice2 TTS engine | |
Args: | |
text (str): Input text to synthesize | |
voice (str): Voice ID (may not be used in CosyVoice2) | |
speed (float): Speech speed multiplier (may not be used in CosyVoice2) | |
Returns: | |
Optional[str]: Path to the generated audio file or None if generation fails | |
""" | |
logger.info(f"Generating speech with CosyVoice2 for text length: {len(text)}") | |
# Check if CosyVoice2 is available | |
if not COSYVOICE2_AVAILABLE: | |
logger.error("CosyVoice2 TTS engine is not available") | |
return None | |
# Ensure model is loaded | |
if not self._ensure_model(): | |
logger.error("Failed to load CosyVoice2 model") | |
return None | |
try: | |
import torch | |
# Generate unique output path | |
output_path = self._generate_output_path(prefix="cosyvoice2") | |
# Generate audio using CosyVoice2 | |
try: | |
# Use the inference method from CosyVoice | |
output_audio_tensor = self.model.inference_sft(text, '中文女') | |
# Convert tensor to numpy array | |
if isinstance(output_audio_tensor, torch.Tensor): | |
output_audio_np = output_audio_tensor.cpu().numpy() | |
else: | |
output_audio_np = output_audio_tensor | |
except Exception as api_error: | |
# Try alternative API if the first one fails | |
try: | |
output_audio_tensor = self.model.inference_zero_shot(text, '请输入提示文本', '中文女') | |
if isinstance(output_audio_tensor, torch.Tensor): | |
output_audio_np = output_audio_tensor.cpu().numpy() | |
else: | |
output_audio_np = output_audio_tensor | |
except Exception as alt_error: | |
logger.error(f"CosyVoice2 inference failed: {str(api_error)}") | |
return None | |
if output_audio_np is not None: | |
logger.info(f"Successfully generated audio with CosyVoice2 (length: {len(output_audio_np)})") | |
sf.write(output_path, output_audio_np, DEFAULT_SAMPLE_RATE) | |
logger.info(f"CosyVoice2 audio generation complete: {output_path}") | |
return output_path | |
else: | |
logger.error("CosyVoice2 model returned None for audio output") | |
return None | |
except Exception as e: | |
logger.error(f"Error generating speech with CosyVoice2: {str(e)}", exc_info=True) | |
return None | |
def generate_speech_stream(self, text: str, voice: str = 'default', speed: float = 1.0) -> Generator[Tuple[int, np.ndarray], None, None]: | |
"""Generate speech stream using CosyVoice2 TTS engine | |
Args: | |
text (str): Input text to synthesize | |
voice (str): Voice ID (may not be used in CosyVoice2) | |
speed (float): Speech speed multiplier (may not be used in CosyVoice2) | |
Yields: | |
tuple: (sample_rate, audio_data) pairs for each segment | |
""" | |
logger.info(f"Generating speech stream with CosyVoice2 for text length: {len(text)}") | |
# Check if CosyVoice2 is available | |
if not COSYVOICE2_AVAILABLE: | |
logger.error("CosyVoice2 TTS engine is not available") | |
return | |
# Ensure model is loaded | |
if not self._ensure_model(): | |
logger.error("Failed to load CosyVoice2 model") | |
return | |
try: | |
import torch | |
# Generate audio using CosyVoice2 | |
try: | |
# Use the inference method from CosyVoice | |
output_audio_tensor = self.model.inference_sft(text, '中文女') | |
# Convert tensor to numpy array | |
if isinstance(output_audio_tensor, torch.Tensor): | |
output_audio_np = output_audio_tensor.cpu().numpy() | |
else: | |
output_audio_np = output_audio_tensor | |
except Exception as api_error: | |
# Try alternative API if the first one fails | |
try: | |
output_audio_tensor = self.model.inference_zero_shot(text, '请输入提示文本', '中文女') | |
if isinstance(output_audio_tensor, torch.Tensor): | |
output_audio_np = output_audio_tensor.cpu().numpy() | |
else: | |
output_audio_np = output_audio_tensor | |
except Exception as alt_error: | |
logger.error(f"CosyVoice2 inference failed: {str(api_error)}") | |
return | |
if output_audio_np is not None: | |
logger.info(f"Successfully generated audio with CosyVoice2 (length: {len(output_audio_np)})") | |
yield DEFAULT_SAMPLE_RATE, output_audio_np | |
else: | |
logger.error("CosyVoice2 model returned None for audio output") | |
return | |
except Exception as e: | |
logger.error(f"Error generating speech stream with CosyVoice2: {str(e)}", exc_info=True) | |
return |