Update app.py

app.py

@@ -28,18 +28,6 @@ async def text_to_speech_edge(text, language_code):
 
     return "语音合成完成：{}".format(text), tmp_path
 
-# 声音更改函数
-#def voice_change(audio_in, audio_ref):
-    #samplerate1, data1 = wavfile.read(audio_in)
-    #samplerate2, data2 = wavfile.read(audio_ref)
-    #write("./audio_in.wav", samplerate1, data1)
-    #write("./audio_ref.wav", samplerate2, data2)
-
-    #query_seq = knn_vc.get_features("./audio_in.wav")
-    #matching_set = knn_vc.get_matching_set(["./audio_ref.wav"])
-    #out_wav = knn_vc.match(query_seq, matching_set, topk=4)
-    #torchaudio.save('output.wav', out_wav[None], 16000)
-    #return 'output.wav'
 def voice_change(audio_in, audio_ref):
     samplerate1, data1 = wavfile.read(audio_in)
     samplerate2, data2 = wavfile.read(audio_ref)
@@ -58,31 +46,7 @@ def voice_change(audio_in, audio_ref):
     torchaudio.save(output_path, out_wav[None], 16000)
     return output_path
 
-# def voice_change(audio_in, audio_ref):
-#     samplerate1, data1 = wavfile.read(audio_in)
-#     samplerate2, data2 = wavfile.read(audio_ref)
-
-#     # 强制匹配音频文件的长度
-#     max_length = max(data1.shape[0], data2.shape[0])
-
-#     if data1.shape[0] < max_length:
-#         data1 = np.pad(data1, (0, max_length - data1.shape[0]), mode='constant')
-#     if data2.shape[0] < max_length:
-#         data2 = np.pad(data2, (0, max_length - data2.shape[0]), mode='constant')
-
-#     with tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_audio_in, \
-#          tempfile.NamedTemporaryFile(delete=False, suffix=".wav") as tmp_audio_ref:
-#         audio_in_path = tmp_audio_in.name
-#         audio_ref_path = tmp_audio_ref.name
-#         wavfile.write(audio_in_path, samplerate1, data1)
-#         wavfile.write(audio_ref_path, samplerate2, data2)
-
-#     query_seq = knn_vc.get_features(audio_in_path)
-#     matching_set = knn_vc.get_matching_set([audio_ref_path])
-#     out_wav = knn_vc.match(query_seq, matching_set, topk=4)
-#     output_path = 'output.wav'
-#     torchaudio.save(output_path, torch.tensor(out_wav)[None], 16000)
-#     return output_path
+
 # 文字转语音（OpenAI）
 def tts(text, model, voice, api_key):
     if len(text) > 300:
@@ -110,10 +74,10 @@ app = gr.Blocks()
 
 with app:
     gr.Markdown("# <center>OpenAI TTS + 3秒实时AI变声+需要使用中转key</center>")
-    gr.Markdown("### <center>中转key购买地址https://buy.sipola.cn</center>")
+    gr.Markdown("### <center>中转key购买地址[here](https://buy.sipola.cn),ai文案生成可使用中转key,请访问 [here](https://ai.sipola.cn)</center>")
     with gr.Tab("TTS"):
         with gr.Row(variant='panel'):
-            api_key = gr.Textbox(type='password', label='API Key', placeholder='请在此填写您的API Key')
+            api_key = gr.Textbox(type='password', label='API Key', placeholder='请在此填写您的中转API Key')
             model = gr.Dropdown(choices=['tts-1','tts-1-hd'], label='请选择模型（tts-1推理更快，tts-1-hd音质更好）', value='tts-1')
             voice = gr.Dropdown(choices=['alloy', 'echo', 'fable', 'onyx', 'nova', 'shimmer'], label='请选择一个说话人', value='alloy')
         with gr.Row():