Update app.py

app.py

@@ -15,6 +15,11 @@ from nltk import bigrams
 import malaya
 from collections import Counter
 
+
+HF_TOKEN = os.getenv('hf_token')
+
+hf_writer = gr.HuggingFaceDatasetSaver(HF_TOKEN,'aisyahhrazak/tpb-crowdsourced-dataset')
+
 with open('en.json') as fopen:
     en = json.load(fopen)
     
@@ -373,9 +378,13 @@ with gr.Blocks(css=css + """
                 tpb_output = gr.Textbox(lines=3, label="TPB Classification")
                 sentiment_output = gr.Textbox(lines=3, label="Sentiment Analysis")
             decision_output = gr.Textbox(lines=3, label="Purchase Prediction")
+            # This needs to be called at some point prior to the first call to callback.flag()
+            hf_writer.setup([input_text,tpb_output, sentiment_output], "flagged_data_points")
             classify_button = gr.Button("Analyze")
-            classify_button.click(fn=text_classification_and_sentiment, inputs=input_text, outputs=[tpb_output, sentiment_output, decision_output])
+            classify_button.click(lambda *args: hf_writer.flag(list(args)),fn=text_classification_and_sentiment, inputs=input_text, outputs=[tpb_output, sentiment_output, decision_output])
             gr.Examples(examples=examples, inputs=input_text)
+
+
         
         with gr.TabItem("Company View", id=1):
             gr.Markdown("# Sentiment Analysis and Purchase Decision Factor for Halal Food Acquisition")