Delete app.py

app.py

@@ -1,36 +0,0 @@
-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 sentiment(summary):
-    pipe = pipeline("text-classification", model="WillWEI0103/CustomModel_finance_sentiment_analytics")
-    label = pipe(summary)[0]['label']
-    return label
-
-
-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: ')
-    
-    #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...')
-    st.write(summary)
-
-    #Stage 2: Sentiment Analytics
-    st.text('Processing Sentiment Analytics...')
-    label = sentiment(summary)
-    st.text('The sentiment of finance news is: ')
-    st.write(label)
-
-if __name__ == "__main__":
-    main()