Update app.py

app.py

@@ -4,8 +4,12 @@ from transformers import pipeline
 # Load the sentiment analysis model pipeline
 sentiment_classifier = pipeline("text-classification",model='Ryleeeee/CustomSentimentModel', return_all_scores=True)
 
+# Load the text summarization model pipeline
+summarizer = pipeline("summarization", model="MurkatG/review-summarizer-en")
+
 # Streamlit application title and background image
-st.image("./header.png", width=600, use_column_width=False)
+# st.image("./header.png", width=300, use_column_width=False)
+st.markdown("<div style='text-align:center'><img src='./header.png' width='300'></div>", unsafe_allow_html=True)
 st.markdown("<h1 style='text-align: center;'>Customer Review Analysis</h1>", unsafe_allow_html=True)
 
 st.write("Setiment classification: positive, netural, negative")
@@ -22,7 +26,12 @@ def sentiment_class(text):
             max_score = result['score']
             max_label = result['label']
     return max_score, max_label
- 
+
+def summarize_text(text):
+    results = summarizer(text)[0]['summary_text']
+    return results
+
+    
 # Perform sentiment analysis when the user clicks the "Classify Sentiment" button
 if st.button("Classify Sentiment"):
     # Check if the user has entered review
@@ -34,3 +43,5 @@ if st.button("Classify Sentiment"):
         st.write("This review sentiment is ", sentiment_result[1])
         st.write("Prediction score is ", sentiment_result[0])
 
+if sentiment_result[1] == 'negative':
+    st.button("Summarize Review")