Update app.py

app.py

@@ -111,7 +111,10 @@ def classify_toxicity(audio_file, text_input, classify_anxiety, emo_class, expli
         # classification_df = pd.DataFrame.from_dict(classification_output)
         print("keys ", classification_output.keys())
         
-        formatted_classification_output = "\n".join([f"{key}: {value}" for key, value in classification_output.items()])
+        # formatted_classification_output = "\n".join([f"{key}: {value}" for key, value in classification_output.items()])
+        label_score_pairs = [(label, score) for label, score in zip(classification_output['labels'], classification_output['scores'])]
+
+
 
 
         # plot.update(x=classification_df["labels"], y=classification_df["scores"])
@@ -121,7 +124,7 @@ def classify_toxicity(audio_file, text_input, classify_anxiety, emo_class, expli
         else:
             affirm = ""
  
-        return toxicity_score, formatted_classification_output, transcribed_text, affirm
+        return toxicity_score, label_score_pairs, transcribed_text, affirm
         # return f"Toxicity Score ({available_models[selected_model]}): {toxicity_score:.4f}"
     else: 
         threshold = slider_logic(slider)
@@ -182,7 +185,7 @@ with gr.Blocks() as iface:
         submit_btn = gr.Button(label="Run")
     with gr.Column():
         out_val = gr.Textbox()
-        out_class = gr.Textbox()
+        out_class = gr.Label()
         out_text = gr.Textbox()
         out_affirm = gr.Textbox()
     submit_btn.click(fn=classify_toxicity, inputs=[aud_input, text, anxiety_class, emo_class, explit_preference, sense_slider], outputs=[out_val, out_class, out_text, out_affirm])