Update app.py

app.py

@@ -43,7 +43,7 @@ right: 2rem;
 st.markdown(page_bg_img, unsafe_allow_html=True)
 # st.image("logo.png", width=200, height=200)
 st.image("logo.png", width=100)
-st.subheader(':darkblue[NLP HUB®]')
+st.subheader(':violet[NLP HUB®]')
 st.markdown("")
 st.markdown("")
 st.markdown("")
@@ -58,26 +58,30 @@ sentiment_model = pipeline(model="ashok2216/gpt2-amazon-sentiment-classifier")
 # Example usage:-
 sample_url = 'https://www.amazon.in/Dell-Inspiron-i7-1255U-Processor-Platinum/product-reviews/B0C9F142V6/ref=cm_cr_dp_d_show_all_btm?ie=UTF8&reviewerType=all_reviews'
 url = st.text_input("Amazon product link", sample_url)
-st.button("Say hello")
+st.button("Re-run")
 st.write("Done")
 st.subheader('', divider='rainbow')
-all_reviews = scrape_all_pages(url)
-# Convert to DataFrame for further analysis
-reviews = pd.DataFrame(all_reviews)
-reviews['processed_text'] = reviews['content'].apply(preprocess)
 
-# st.dataframe(reviews, use_container_width=True)
-# st.markdown(sentiment_model(['It is Super!']))
-
-sentiments = []
-for text in reviews['processed_text']:
-    if list(sentiment_model(text)[0].values())[0] == 'LABEL_1':
-        output = 'Positive'
-    else:
-        output = 'Negative'
-    sentiments.append(output)
-
-reviews['sentiments'] = sentiments
-st.markdown(':white[Output]')
-st.dataframe(reviews, use_container_width=True)
-# sns.countplot(reviews['sentiments'])
+try:
+    all_reviews = scrape_all_pages(url)
+    # Convert to DataFrame for further analysis
+    reviews = pd.DataFrame(all_reviews)
+    reviews['processed_text'] = reviews['content'].apply(preprocess)
+    
+    # st.dataframe(reviews, use_container_width=True)
+    # st.markdown(sentiment_model(['It is Super!']))
+    
+    sentiments = []
+    for text in reviews['processed_text']:
+        if list(sentiment_model(text)[0].values())[0] == 'LABEL_1':
+            output = 'Positive'
+        else:
+            output = 'Negative'
+        sentiments.append(output)
+    
+    reviews['sentiments'] = sentiments
+    st.markdown(':white[Output]')
+    st.dataframe(reviews, use_container_width=True)
+    # sns.countplot(reviews['sentiments'])
+except KeyError:
+    st.markdown('Please :red[Re-run] the app')