spam_classifier: Implement flagging function

Signed-off-by: Panchajanya1999 <rsk52959@gmail.com>

spam_classifier.py

@@ -1,8 +1,7 @@
 # import libraries
 import pandas as pd
-import numpy as np
-import matplotlib.pyplot as plt
 import gradio as gr
+import os
 
 # import string
 import string
@@ -16,6 +15,9 @@ from sklearn.model_selection import train_test_split
 # import multinomial naive bayes
 from sklearn.naive_bayes import MultinomialNB
 
+# read the variable from the environment
+HF_API_TOKEN = os.getenv("HF_API_TOKEN")
+
 # read data from csv file
 df = pd.read_csv('dataset/spam.tsv', sep='\t', names=['label', 'message'])
 
@@ -69,12 +71,15 @@ def predict_spam(message):
         message = 'This is a spam message'
     return message
 
+hf_writer = gr.HuggingFaceDatasetSaver(HF_API_TOKEN, "spam-mistakes") 
+
 iface = gr.Interface(
     fn=predict_spam, 
     inputs=gr.Textbox(lines=2, placeholder="Enter a message to check if it is spam or ham", label="Message", info = "Enter a message"),
     outputs=gr.Textbox(lines=2, info="Check if the enetered message is spam or ham", label="Prediction", placeholder = "Output will be here.."),
     title="Spam Classifier", 
     description="Enter a message to check if it is spam or ham", 
-    allow_flagging='never', 
+    allow_flagging='manual',
+    flagging_callback=hf_writer,
     examples=[['Hey, how are you doing?'], ['Congratulations! You have won a free trip to Dubai!']])
 iface.launch()