Update app.py

app.py

@@ -1,11 +1,11 @@
 import streamlit as st
 from transformers import pipeline
 
-#def text_summarize(text):
-#    pipe = pipeline("summarization", model="human-centered-summarization/financial-summarization-pegasus")
-#    summary = pipe(text)[0]['summary_text']
-#    print(summary)
-#    return summary
+def text_summarize(text):
+    pipe = pipeline("summarization", model="nickmuchi/fb-bart-large-finetuned-trade-the-event-finance-summarizer")
+    summary = pipe(text)[0]['summary_text']
+    print(summary)
+    return summary
 
 def sentiment(summary):
     pipe = pipeline("text-classification", model="WillWEI0103/CustomModel_finance_sentiment_analytics")
@@ -17,10 +17,10 @@ def main():
     st.set_page_config(page_title="Your Finance news", page_icon="📰")
     st.header("Summarize Your Finance News and Analyze Sentiment")
     text=st.text_input('Input your Finance news: ')
+    st.text('Your Finance news: ')
+    st.write(text)
     
     #Stage 1: Text Summarization
-    text_summarize=pipeline("summarization", model="nickmuchi/fb-bart-large-finetuned-trade-the-event-finance-summarizer")
-    #text_summarize=pipeline("summarization", model="human-centered-summarization/financial-summarization-pegasus")
     summary = text_summarize(text)
     summary = summary[0]['summary_text']
     st.text('Processing Finance News Summarization...')