Update app.py

app.py

@@ -5,8 +5,9 @@ from data_cleaning import preprocess
 from transformers import pipeline
 from data_integration import scrape_all_pages
 
-sentiment_model = pipeline(model="ashok2216/gpt2-amazon-sentiment-classifier")
+st.title('Amazon Sentiment Analysis using FineTuned :blue[GPT-2] Pre-Trained Model :robot:')
 
+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)
@@ -17,7 +18,7 @@ all_reviews = scrape_all_pages(url)
 reviews = pd.DataFrame(all_reviews)
 reviews['processed_text'] = reviews['content'].apply(preprocess)
 
-st.dataframe(reviews, use_container_width=True)
+# st.dataframe(reviews, use_container_width=True)
 # st.markdown(sentiment_model(['It is Super!']))
 
 sentiments = []
@@ -29,6 +30,6 @@ for text in reviews['processed_text']:
     sentiments.append(output)
 
 reviews['sentiments'] = sentiments
-
+st.title(':rainbow[Output]')
 st.dataframe(reviews, use_container_width=True)
 # sns.countplot(reviews['sentiments'])