Update app.py

app.py

@@ -15,7 +15,6 @@ model_nlp = AutoModelForSequenceClassification.from_pretrained("cardiffnlp/twitt
 model = whisper.load_model("small")
 
 
-
 def inference_audio(audio):
     audio = whisper.load_audio(audio)
     audio = whisper.pad_or_trim(audio)
@@ -27,11 +26,10 @@ def inference_audio(audio):
     options = whisper.DecodingOptions(fp16 = False)
     result = whisper.decode(model, mel, options)
     
-    print(result.text)
-    return result.text, gr.update(visible=True), gr.update(visible=True), gr.update(visible=True)
+    return result.text
 
 def inference_text(audio):
-    text,_,_,_ =inference_audio(audio)
+    text =inference_audio(audio)
 
     sentiment_task = pipeline("sentiment-analysis", model=model_nlp, tokenizer=tokenizer)
     res=sentiment_task(text)[0]
@@ -50,6 +48,4 @@ app=gr.Interface(title="Sentiment Audio Analysis",fn=inference_text,inputs=[audi
 
 
 
-app.launch()
-
-
+app.launch()