Update app.py

app.py

@@ -5,13 +5,13 @@ from data_cleaning import preprocess
 from transformers import pipeline
 from data_integration import scrape_all_pages
 
-st.markdown('Amazon Sentiment Analysis using FineTuned :blue[GPT-2] Pre-Trained Model')
+st.header('Amazon Sentiment Analysis using FineTuned :blue[GPT-2] Pre-Trained Model')
 
 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.write("The current movie title is", url)
+st.write("Done")
 
 all_reviews = scrape_all_pages(url)
 # Convert to DataFrame for further analysis
@@ -30,6 +30,6 @@ for text in reviews['processed_text']:
     sentiments.append(output)
 
 reviews['sentiments'] = sentiments
-st.markdown(':rainbow[Output]')
+st.header(':rainbow[Output]')
 st.dataframe(reviews, use_container_width=True)
 # sns.countplot(reviews['sentiments'])