choice

app.py

@@ -7,25 +7,28 @@ classifier = pipeline(task="sentiment-analysis")
 
 textIn = st.text_input("Input Text Here:", "I really like the color of your car!")
 
-option = st.selectbox('Which pre-trained model would you like for your sentiment analysis?',('Pipeline', 'textblob', ''))
+option = st.selectbox('Which pre-trained model would you like for your sentiment analysis?',('Pipeline', 'TextBlob', ''))
 
 st.write('You selected:', option)
 
-# pipeline
-preds = classifier(textIn)
-preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
-st.write('According to Pipeline, input text is ', preds[0]['label'], ' with a confidence of ', preds[0]['score'])
-
-# textblob
-polarity = TextBlob(textIn).sentiment.polarity
-subjectvitity = TextBlob(textIn).sentiment.subjectivity
-sentiment = ''
-if polarity < 0:
-    sentiment = 'Negative'
-elif polarity == 0:
-    sentiment = 'Neutral'
-else:
-    sentiment = 'Positive'
-
-st.write('According to textblob, input text is ', sentiment, ' and a subjectvitity score (from 0 being objective to 1 being subjective) of ', subjectvitity)
+
+if option == 'Pipeline':
+    # pipeline
+    preds = classifier(textIn)
+    preds = [{"score": round(pred["score"], 4), "label": pred["label"]} for pred in preds]
+    st.write('According to Pipeline, input text is ', preds[0]['label'], ' with a confidence of ', preds[0]['score'])
+
+if option == 'TextBlob':
+    # textblob
+    polarity = TextBlob(textIn).sentiment.polarity
+    subjectivity = TextBlob(textIn).sentiment.subjectivity
+    sentiment = ''
+    if polarity < 0:
+        sentiment = 'Negative'
+    elif polarity == 0:
+        sentiment = 'Neutral'
+    else:
+        sentiment = 'Positive'
+
+    st.write('According to textblob, input text is ', sentiment, ' and a subjectivity score (from 0 being objective to 1 being subjective) of ', subjectivity)