Update app.py

app.py

@@ -30,7 +30,7 @@ def classify_toxicity(audio_file, text_input, classify_anxiety):
         '''whisper_model = WhisperModel.from_pretrained("openai/whisper-base")
         feature_extractor = AutoFeatureExtractor.from_pretrained("openai/whisper-base")
         transcription_results = whisper_model.compute(uploaded=audio_file)
-         '''
+        
         audio = whisper.load_audio(audio_file)
         mel = whisper.log_mel_spectrogram(audio).to(model.device)
         _, probs = model.detect_language(mel)    
@@ -38,7 +38,9 @@ def classify_toxicity(audio_file, text_input, classify_anxiety):
         result = whisper.decode(model, mel, options)
         # Extract the transcribed text
         # transcribed_text = transcription_results["transcription"]
-        transcribed_text = resut.text
+        '''
+        model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small", use_auth_token=huggingface_token)
+        transcribed_text = model.transcribe(audio_file)
         
         #### Emotion classification ####
         emotion_classifier = foreign_class(source="speechbrain/emotion-recognition-wav2vec2-IEMOCAP", pymodule_file="custom_interface.py", classname="CustomEncoderWav2vec2Classifier")