Update app.py

app.py

@@ -12,7 +12,6 @@ import gradio as gr
 import tensorflow as tf
 from tensorflow.keras.models import load_model
 from tensorflow.keras.preprocessing.text import tokenizer_from_json
-import tensorflow_addons as tfa
 
 # Load the pre-trained model and tokenizer
 model = tf.keras.models.load_model('baseline.h5')
@@ -36,23 +35,18 @@ def classify_comment(comment):
     predictions = model.predict(comment_sequence)[0]
     results = dict(zip(labels, predictions))
     
-    max_value = max(results.values())
+    max_class = max(results, key=results.get)
+    max_value = results[max_class]
 
-    max_keys = [key for key, value in results.items() if value == max_value]
-
-    return max_keys[0].capitalize()
-
-# Create the Gradio interface
-comment_input = gr.inputs.Textbox(label="Enter your comment here")
-output_text = gr.outputs.Textbox(label="Classification Results")
+    return {"Label": max_class.capitalize(), "Confidence": f"{max_value:.2%}"}
 
+# Create the Gradio interface with an improved layout
 iface = gr.Interface(
     fn=classify_comment,
-    inputs=comment_input,
-    outputs=output_text,
+    inputs=gr.inputs.Textbox(label="Enter your comment here", lines=5),
+    outputs=gr.outputs.Label(num_top_classes=1, label="Predicted Label", type="auto"),
     live=True  # Set to True for live updates without needing to restart the server
 )
 
 # Launch the Gradio app
-iface.launch()
-
+iface.launch()