update

app.py

@@ -1,23 +1,39 @@
 import gradio as gr
-from transformers import pipeline
+import os
+import torchaudio
+from fireredtts.fireredtts import FireRedTTS
 
-# 加载一个 Hugging Face 预训练的 TTS 模型
-tts = pipeline("text-to-speech", model="facebook/fastspeech2-en-ljspeech", device=0)
 
-def tts_inference(text):
-    # 使用 TTS 模型生成语音
-    audio = tts(text)[0]['audio']
-    return audio
+gpt_path = 'https://huggingface.co/fireredteam/FireRedTTS/resolve/main/fireredtts_gpt.pt'
+speaker_path = 'https://huggingface.co/fireredteam/FireRedTTS/resolve/main/fireredtts_speaker.bin'
+decoder_path = 'https://huggingface.co/fireredteam/FireRedTTS/resolve/main/fireredtts_token2wav.pt'
+
+
+tts = FireRedTTS(
+    config_path="configs/config_24k.json",
+    pretrained_path='pretrained_models',
+)
+
+def tts_inference(text, prompt_wav='examples/prompt_1.wav', lang='zh'):
+    syn_audio = tts.synthesize(
+        prompt_wav=prompt_wav,
+        text=text,
+        lang=lang,
+    )
+    return syn_audio.detach().cpu()
+
 
-# 创建 Gradio 接口
 iface = gr.Interface(
-    fn=tts_inference, 
-    inputs="text", 
-    outputs="audio", 
+    fn=tts_inference,
+    inputs=[
+        gr.Textbox(label="输入文本"),
+        # gr.Dropdown(["en-US-Wav2Vec2-Kendra", "en-US-Wav2Vec2-John"], label="选择声音"),
+        # gr.Slider(minimum=0.5, maximum=2.0, value=1.0, label="语速")
+    ],
+    outputs=gr.Audio(label="生成的语音"),
     title="TTS Demo", 
     description="Enter some text and listen to the generated speech."
 )
 
-# 启动 Gradio 应用
 if __name__ == "__main__":
     iface.launch()