updated zero shot fig

app.py

@@ -69,8 +69,8 @@ with st.sidebar:
 if select_task=='Detect Sentiment':
     st.header("You are now performing Sentiment Analysis")
     input_texts = st.text_input(label="Input texts separated by comma")
-
-    if input_texts!='':
+    response=st.button("Calculate")
+    if response:
         sentiments = classify_sentiment(input_texts)
         for i,t in enumerate(input_texts.split(',')):
             if sentiments[i]=='Positive':
@@ -84,7 +84,8 @@ if select_task=='Zero Shot Classification':
     st.header("You are now performing Zero Shot Classification")
     input_texts = st.text_input(label="Input text to classify into topics")
     input_lables = st.text_input(label="Enter labels separated by commas")
-
-    if len(input_texts) !=0 and len(input_lables) != 0:
+    response = st.button("Calculate")
+    if response:
         output=zero_shot_classification(input_texts, input_lables)
-        st.write(output)
+        config = {'displayModeBar': False}
+        st.plotly_chart(output,config=config)

zeroshot_clf.py

@@ -34,11 +34,14 @@ def zero_shot_classification(premise:str,labels:str,model=model,tokenizer=tokeni
 
     df=pd.DataFrame({'labels':labels,
                      'Probability':labels_prob_norm})
-    fig=px.bar(x=df['Probability'],
-               y=df['labels'])
-    return streamlit.plotly_chart(fig)
-
-# zero_shot_classification(premise='Tiny worms and breath analyzers could screen for disease while it’s early and treatable',
+    fig=px.bar(x='Probability',
+               y='labels',
+               text='Probability',
+               data_frame=df,
+               title='Zero Shot Normalized Probabilities')
+    return fig
+
+# zero_shot_classification(premise='Tiny worms and breath analyzers could screen for \disease while it’s early and treatable',
 #                          labels='science, sports, museum')