Explaination and Radio Button added

app.py

@@ -1,17 +1,23 @@
+from os import write
 from typing import Sequence
 import streamlit as st
 from hf_model import classifier_zero,load_model
 from utils import plot_result
+import json
 classifier=load_model()
+with open("examples.json") as f:
+    data=json.load(f)
+
 if __name__ == '__main__':
     st.header("Zero Shot Classification")
-    
+    st.write("This app allows you to classify any text into any categories you are interested in.")
 
     with st.form(key='my_form'):
-        text_input = st.text_area(label="Input Text")
-        labels = st.text_input('Possible topics (separated by `,`)', max_chars=1000)
+        text_input = st.text_area("Input Text",data['text'])
+        labels = st.text_input('Possible topics (separated by `,`)',data["labels"], max_chars=1000)
         labels = list(set([x.strip() for x in labels.strip().split(',') if len(x.strip()) > 0]))
-        multi_class = st.checkbox('Allow multiple correct topics', value=True)
+        radio = st.radio("Select Multiclass",('Only one topic can be corect at a time','Multiple topics can be correct at a time'),)
+        multi_class= True if radio=="Multiple topics can be correct at a time" else False
         submit_button = st.form_submit_button(label='Submit')
     if submit_button:
         if len(labels) == 0:

examples.json

@@ -0,0 +1,4 @@
+{
+"text":"The Democratic president had just signed into law the most significant infrastructure package in generations. And he had done it by bringing Democrats and Republicans together.",
+"labels":["Economy", "Politics", "Environment", "Entertainment"]
+}

zx.py

@@ -0,0 +1,3 @@
+import streamlit as st
+text_input = st.text_area(label="Input Text",placeholder="Hello world!")
+st.write(text_input+"ZZ")