Update app.py

app.py

@@ -1,34 +1,21 @@
 import streamlit as st
-import pandas as pd
 from transformers import pipeline
 from textblob import TextBlob
-from datasets import load_dataset
-
-# Load dataset
-
-df = load_dataset("gxb912/large-twitter-tweets-sentiment")
-
-pipe = pipeline(f"cardiffnlp/twitter-roberta-base-{task}")
 
+pipe = pipeline('sentiment-analysis')
 st.title("Sentiment Analysis")
 
-st.subheader("Choose Framework:")
-option = st.selectbox('Choose Framework:', ('Transformers', 'TextBlob'))
+st.subheader("Which framework would you like to use for sentiment analysis?")
+option = st.selectbox('Choose Framework:',('Transformers', 'TextBlob')) # option is stored in this variable
 
 st.subheader("Enter the text you want to analyze")
-text = st.text_input('Enter text:')
-
-if text:
-    if option == 'Transformers':
-        out = pipe(text)
-    else:
-        out = TextBlob(text).sentiment
-
-    st.write("Sentiment of Text:", out)
-
-# Display dataset insights
-if st.checkbox("Show dataset sample"):
-    st.write(df.head())
-
-if st.checkbox("Show dataset statistics"):
-    st.write(df.describe())
+text = st.text_input('Enter text:') # text is stored in this variable
+
+if option == 'Transformers':
+    out = pipe(text)
+else:
+    out = TextBlob(text)
+    out = out.sentiment
+    
+st.write("Sentiment of Text: ")
+st.write(out)