app.py

import gradio as gr
from transformers import AutoProcessor, AutoModelForSpeechT5
import torch
import scipy.io.wavfile
import tempfile

# 加载模型和处理器
processor = AutoProcessor.from_pretrained("FunAudioLLM/CosyVoice2-0.5B")
model = AutoModelForSpeechT5.from_pretrained("FunAudioLLM/CosyVoice2-0.5B")

device = "cuda" if torch.cuda.is_available() else "cpu"
model = model.to(device)

# 合成语音的函数
def tts_fn(text):
    inputs = processor(text, return_tensors="pt").to(device)
    with torch.no_grad():
        speech = model.generate(**inputs)
    speech = speech.cpu().numpy()

    # 保存为临时 wav 文件
    with tempfile.NamedTemporaryFile(suffix=".wav", delete=False) as f:
        scipy.io.wavfile.write(f.name, rate=16000, data=speech)
        return f.name

# Gradio 界面
demo = gr.Interface(
    fn=tts_fn,
    inputs=gr.Textbox(label="请输入中文文本", placeholder="例如：你好，这是 CosyVoice2 的语音演示"),
    outputs=gr.Audio(label="合成语音"),
    title="CosyVoice2 中文语音合成演示"
)

demo.launch()