Upload app.py

app.py

@@ -5,6 +5,7 @@ import matplotlib.pyplot as plt
 HOME_DIR = ""
 local_config_path = 'config.json'
 local_preprocessor_config_path = 'preprocessor_config.json'
+local_weights_path = 'pytorch_model.bin'
 local_training_args_path = 'training_args.bin'
 
 import torch
@@ -138,8 +139,7 @@ with demo:
                             show_label=True
                             )
     text_output = gr.Textbox(label="Recognized Emotion")
-    predict_button = gr.Button("Predict Emotion")
 
     # Automatically call the recognize_emotion function when audio is recorded
-    predict_button.click(recognize_emotion, inputs=audio_input, outputs=text_output)
+    audio_input.stop_recording(fn=recognize_emotion, inputs=audio_input, outputs=text_output)
 demo.launch(share=True)