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import sys
import os
import torch
import torchaudio

sys.path.insert(0, './CosyVoice')

from cosyvoice.cli.cosyvoice import CosyVoice2
from cosyvoice.utils.file_utils import load_wav

class CosyVoice2TTS:
    def __init__(self, model_dir, device="cuda"):
        print(f"[TTS] Loading CosyVoice2 model from {model_dir}...")
        
        # εˆε§‹εŒ–ζ¨‘εž‹
        self.model = CosyVoice2(
            model_dir, 
            load_jit=False, 
            load_trt=False, 
            load_vllm=False, 
            fp16=True
        )
        print("[TTS] CosyVoice2 Model loaded successfully.")

    def synthesize(self, text, prompt_text, prompt_speech_path, output_path=None, stream=False):
        if not text:
            return None, None

        # εŠ θ½½ιŸ³ι’‘
        prompt_speech_16k = load_wav(prompt_speech_path, 16000)

        # 调用 zero_shot ζŽ¨η†
        output = self.model.inference_zero_shot(
            tts_text=text, 
            prompt_text=prompt_text, 
            prompt_speech_16k=prompt_speech_16k,
            stream=stream
        )

        final_audio = []
        # θŽ·ε–ι‡‡ζ ·ηŽ‡
        sample_rate = getattr(self.model, 'sample_rate', 24000) 

        for i in output:
            final_audio.append(i['tts_speech'])

        if not final_audio:
            return None, None
            
        full_audio_tensor = torch.cat(final_audio, dim=1)
        
        if output_path:
            os.makedirs(os.path.dirname(output_path), exist_ok=True)
            torchaudio.save(output_path, full_audio_tensor, sample_rate)
            print(f"[TTS] Audio saved to {output_path}")

        return sample_rate, full_audio_tensor.cpu().numpy()