Update app.py

app.py

@@ -7,11 +7,18 @@ Original file is located at
     https://colab.research.google.com/drive/1OQvi3I_q3WfavYBpjovCYfv2SPYt__pF
 """
 
+"""gradio_app.py
+Automatically generated by Colaboratory.
+Original file is located at
+    https://colab.research.google.com/drive/1OQvi3I_q3WfavYBpjovCYfv2SPYt__pF
+"""
+
 import json
 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')
@@ -35,16 +42,20 @@ def classify_comment(comment):
     predictions = model.predict(comment_sequence)[0]
     results = dict(zip(labels, predictions))
     
-    max_class = max(results, key=results.get)
-    max_value = results[max_class]
+    max_value = max(results.values())
+
+    max_keys = [key for key, value in results.items() if value == max_value]
+
+    return max_keys[0].capitalize()
 
-    return {"Label": max_class.capitalize(), "Confidence": f"{max_value:.2%}"}
+# Create the Gradio interface
+comment_input = gr.inputs.Textbox(label="Enter your comment here")
+output_text = gr.outputs.Textbox(label="Classification Results")
 
-# Create the Gradio interface with an improved layout
 iface = gr.Interface(
     fn=classify_comment,
-    inputs=gr.inputs.Textbox(label="Enter your comment here", lines=5),
-    outputs=gr.outputs.Label(num_top_classes=1, label="Predicted Label", type="auto"),
+    inputs=comment_input,
+    outputs=output_text,
     live=True  # Set to True for live updates without needing to restart the server
 )