Update app.py

app.py

@@ -175,7 +175,7 @@ def greet(apikey,Voicetoclone,VoiceMicrophone, audio, choice1):
 
     messages.append({"role": "assistant", "content": chat_response})   
     
-    text= "%s" % (chat_response)
+    text = chat_response
     if Voicetoclone is not None:
       reference_files= "%s" % (Voicetoclone)
       print("path url")
@@ -226,21 +226,21 @@ def greet(apikey,Voicetoclone,VoiceMicrophone, audio, choice1):
       print(" > Saving output to {}".format(out_path))
       ap.save_wav(wav, out_path)
 
-      voicefixer.restore(input=out_path, # input wav file path
-                      output="audio1.wav", # output wav file path
-                      cuda=True, # whether to use gpu acceleration
-                      mode = 0) # You can try out mode 0, 1 to find out the best result
+#      voicefixer.restore(input=out_path, # input wav file path
+ #                     output="audio1.wav", # output wav file path
+  #                    cuda=True, # whether to use gpu acceleration
+   #                   mode = 0) # You can try out mode 0, 1 to find out the best result
 
 
 
-      noisy = enhance_model.load_audio(
-      "audio1.wav"
-      ).unsqueeze(0)
+#      noisy = enhance_model.load_audio(
+ #     "audio1.wav"
+  #    ).unsqueeze(0)
 
-      enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.]))
-      torchaudio.save("enhanced.wav", enhanced.cpu(), 16000)
+#      enhanced = enhance_model.enhance_batch(noisy, lengths=torch.tensor([1.]))
+#      torchaudio.save("enhanced.wav", enhanced.cpu(), 16000)
 
-      return [result.text, chat_response, "enhanced.wav"]
+      return [result.text, chat_response, out_path]
 
 output_1 = gr.Textbox(label="Speech to Text")
 output_2 = gr.Textbox(label="ChatGPT Output")