Update app.py

app.py

@@ -1,23 +0,0 @@
-import streamlit as st
-from transformers import pipeline
-
-# Load the summarization & translation model pipeline
-tran_sum_pipe = pipeline("translation", model='utrobinmv/t5_summary_en_ru_zh_base_2048')
-sentiment_pipeline = pipeline("text-classification", model="Howosn/Sentiment_Model")
-
-# Streamlit application title
-st.title("Emotion analysis")
-st.write("Turn Your Input Into Sentiment Score")
-
-# Text input for the user to enter the text to analyse
-text = st.text_area("Enter the text", "")
-
-# Perform analysis result when the user clicks the "Analyse" button
-if st.button("Analyse"):
-    # Perform text classification on the input text
-    trans_sum = tran_sum_pipe(text)
-    result = sentiment_pipeline(trans_sum)
-    
-    # Display the analysis result
-    st.write("Text:", text)
-    st.write("result:", result)