Fixed bugs.

app.py

@@ -157,54 +157,18 @@ def predict(tweet):
 
     return prediction
 
+demo = gr.Interface(
+    fn=predict,
 
-# # def predict(tweet):
-    
-# #     fuzzy_text, matches = fuzzy_lookup(tweet)
-# #     processed_text = preprocess(fuzzy_text)
-# #     output = query(processed_text)
-
-
-# #     if 'error' in output:
-# #         return output['error'], 'Error occured. Try again later.', {}
-# #     elif len(matches) == 0:
-# #         return 'No Profanity Found.', '', {}
-# #     else:
-# #         output = [tuple(i.values()) for i in output[0]]
-# #         output = dict((x, y) for x, y in output)
-# #         predicted_label = list(output.keys())[0]
-
-# #         if predicted_label == 'Abusive':
-# #             # Censor
-# #             for base_word, _ in matches.items():
-# #                 mask = '*' * len(base_word)
-# #                 compiled = re.compile(re.escape(base_word), re.IGNORECASE)
-# #                 tweet = compiled.sub(mask, tweet)
-# #                 # tweet = tweet.replace(base_word, re.sub("[a-zA-Z0-9@]", "*", base_word))
-# #             return output, tweet, json.dumps(matches)
-# #         else:
-# #             return output, tweet, json.dumps(matches)
-
-# # # output, tweet, matches = predict('ul0L Sama ng ugali mo pre Tangina uL0l!!!')
-# # # print(output, '\n', tweet, '\n', matches)
-
-# # hf_writer = gr.HuggingFaceDatasetSaver('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', 'tagalog-profanity-feedbacks')
-
-
-# demo = gr.Interface(
-#     fn=predict,
-
-#     inputs=[gr.components.Textbox(lines=5, placeholder='Enter your input here', label='INPUT')],
-
-#     outputs=[gr.components.Label(num_top_classes=2, label="PREDICTION")],
+    inputs=[gr.components.Textbox(lines=5, placeholder='Enter your input here', label='INPUT')],
 
-#     examples=['Tangina mo naman sobrang yabang mo gago!!😠😤 @davidrafael',
-#               'Napakainit ngayong araw pakshet namaaan!!',
-#               'Napakabagal naman ng wifi tangina #PLDC #HelloDITO',
-#               'Bobo ka ba? napakadali lang nyan eh... 🤡',
-#               'Uy gago laptrip yung nangyare samen kanina HAHAHA😂😂'],
-# )
+    outputs=[gr.components.Label(num_top_classes=2, label="PREDICTION")],
 
-# demo.launch()
+    examples=['Tangina mo naman sobrang yabang mo gago!!😠😤 @davidrafael',
+              'Napakainit ngayong araw pakshet namaaan!!',
+              'Napakabagal naman ng wifi tangina #PLDC #HelloDITO',
+              'Bobo ka ba? napakadali lang nyan eh... 🤡',
+              'Uy gago laptrip yung nangyare samen kanina HAHAHA😂😂'],
+)
 
-predict("asdasd kgjhgjhgj")
+demo.launch()