Update app.py

app.py

@@ -1,55 +1,17 @@
 import streamlit as st
 from transformers import pipeline
 
-# Model path
-model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetuned"
+model_path = "citizenlab/twitter-xlm-roberta-base-sentiment-finetunned"
 
-# 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
@@ -58,4 +20,4 @@ if st.button("Analyze Sentiment"):
         sentiment_score = results[0]["score"]
 
         st.write(f"Sentiment: {sentiment_label}")
-        st.write(f"Confidence Score: {sentiment_score:.2f}")
+        st.write(f"Confidence Score: {sentiment_score:.2f}")