Update app.py

app.py

@@ -1,17 +1,55 @@
 import streamlit as st
 from transformers import pipeline
 
-model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned"
+# Model path
+model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetuned"
 
+# Set Streamlit page config
 st.set_page_config(page_title="Sentiment Analysis App")
 
-
+# Load sentiment analysis model
 sentiment_classifier = pipeline("text-classification", model=model_path, tokenizer=model_path)
 
+# Title and user input
 st.title("Sentiment Analysis App")
-
 user_input = st.text_area("Enter a message:")
 
+# Function to add CSS style and icons
+def custom_css():
+    st.markdown(
+        """
+        <style>
+        /* Add some custom CSS */
+        .btn {
+            background-color: #008CBA;
+            color: white;
+            padding: 8px 20px;
+            text-align: center;
+            text-decoration: none;
+            display: inline-block;
+            font-size: 16px;
+            margin: 4px 2px;
+            transition-duration: 0.4s;
+            cursor: pointer;
+            border-radius: 8px;
+        }
+        /* Add an icon to the button */
+        .icon {
+            display: inline-block;
+            vertical-align: middle;
+            width: 20px;
+            height: 20px;
+            margin-right: 5px;
+        }
+        </style>
+        """,
+        unsafe_allow_html=True,
+    )
+
+# Render the custom CSS
+custom_css()
+
+# Analyze sentiment button
 if st.button("Analyze Sentiment"):
     if user_input:
         # Perform sentiment analysis
@@ -21,4 +59,3 @@ if st.button("Analyze Sentiment"):
 
         st.write(f"Sentiment: {sentiment_label}")
         st.write(f"Confidence Score: {sentiment_score:.2f}")
-