Update app.py

app.py

@@ -1,21 +1,34 @@
 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("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("Choose Framework:")
+option = st.selectbox('Choose Framework:', ('Transformers', 'TextBlob'))
 
 st.subheader("Enter the text you want to analyze")
-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)
+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())