Update app.py

app.py

@@ -9,24 +9,29 @@ from keras.utils import pad_sequences
 
 max_len = 200
 
-# set the vocabulary mapping on a new TextVectorization layer
+# Load the tokenizer
 with open('tokenizer.pickle', 'rb') as handle:
     tokenizer = pickle.load(handle)
+
+# Load the pre-trained model
 model = tf.keras.models.load_model('toxic.h5')
 
+arr = ["toxic", "severe_toxic", "obscene", "threat", "insult", "identity_hate"]
 
-arr=["toxic","severe_toxic","obscene threat","insult","identity_hate"]
 def score_comment(comment):
     sequences = tokenizer.texts_to_sequences([comment])
-    inp = pad_sequences(sequences,maxlen=max_len)
+    inp = pad_sequences(sequences, maxlen=max_len)
     results = model.predict(inp)
     text = ''
     for i in range(len(arr)):
-        text += '{}: {}\n'.format(arr[i], results[0][i]>0.5)
+        text += '{}: {}\n'.format(arr[i], results[0][i] > 0.5)
     return text
 
-interface = gr.Interface(fn=score_comment, 
-                         inputs=gr.inputs.Textbox(lines=2, placeholder='Comment to score'),
-                        outputs='text')
+# Update the Gradio interface to use the latest syntax
+inputs = gr.Textbox(lines=2, placeholder='Comment to score')
+outputs = gr.Textbox()
+
+interface = gr.Interface(fn=score_comment, inputs=inputs, outputs=outputs)
 
-interface.launch(debug=True,share=True)
+# Launch the interface
+interface.launch(debug=True, share=True)