Update app.py

app.py

@@ -40,10 +40,10 @@ class_options = {
 
 pipe = pipeline("automatic-speech-recognition", model="openai/whisper-large")
 
-def classify_emotion():
+def classify_emotion(audio):
         #### Emotion classification ####
         emotion_classifier = foreign_class(source="speechbrain/emotion-recognition-wav2vec2-IEMOCAP", pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")
-        out_prob, score, index, text_lab = emotion_classifier.classify_file(audio_file)
+        out_prob, score, index, text_lab = emotion_classifier.classify_file(audio)
         emostr = "emo class"
         return  emo_dict[text_lab[0]], emostr
     
@@ -67,7 +67,7 @@ def classify_toxicity(audio_file, text_input, classify_anxiety, emo_class):
         print(toxicity_score)
         # emo call
         if emo_class != None:
-            classify_emotion()
+            classify_emotion(audio_file)
         #### Text classification #####
     
         device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")