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app.py

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+import gradio as gr
+
+model = tf.keras.models.load_model('toxic-detect.h5')
+
+def evaluate_comment(Comment):
+    processed_Comment = vectorizer([Comment])
+    res = model.predict(processed_Comment)
+
+    text = ''
+    for i, col in enumerate(df.columns[2:]):
+        text += '{}: {}\n'.format(col, 'Violate' if res[0][i] > 0.5 else 'None')
+    
+    return text
+    
+ interface = gr.Interface(fn = evaluate_comment, 
+                         inputs = gr.inputs.Textbox(lines = 4, placeholder='Comment to evaluate'), 
+                         outputs = 'text')
+                         
+ interface.launch(share=True)