Update app.py

app.py

@@ -1,33 +1,64 @@
 import streamlit as st
 
-# Set up page
-st.title("💬 Sentiment Analysis App (Rule-based)")
-st.write("This app predicts the sentiment of your text using simple Python logic (no ML model).")
+# Page config
+st.set_page_config(
+    page_title="Sentiment Analysis",
+    page_icon="💬",
+    layout="centered"
+)
 
-# Input text
-user_input = st.text_area("Enter your text here:")
+# Custom styles
+st.markdown("""
+    <style>
+        .stTextArea textarea {
+            height: 150px;
+        }
+        .result-box {
+            padding: 1rem;
+            border-radius: 0.5rem;
+            margin-top: 1rem;
+            text-align: center;
+            font-size: 1.3rem;
+        }
+        .positive { background-color: #d4edda; color: #155724; }
+        .negative { background-color: #f8d7da; color: #721c24; }
+        .neutral { background-color: #fff3cd; color: #856404; }
+    </style>
+""", unsafe_allow_html=True)
 
-# Basic keyword lists
+# App title and intro
+st.title("💬 Sentiment Analysis App")
+st.markdown("Predict sentiment using simple Python logic — no ML, just rule-based 😎")
+
+# Input section
+st.subheader("📝 Enter your text")
+user_input = st.text_area("", placeholder="Type or paste your sentence here...")
+
+# Keywords
 positive_words = ["good", "great", "happy", "excellent", "amazing", "love", "awesome", "fantastic", "positive", "nice"]
 negative_words = ["bad", "sad", "terrible", "horrible", "hate", "awful", "worst", "angry", "negative", "poor"]
 
+# Sentiment analysis function
 def analyze_sentiment(text):
     text = text.lower()
     pos_count = sum(word in text for word in positive_words)
     neg_count = sum(word in text for word in negative_words)
 
     if pos_count > neg_count:
-        return "😊 Positive"
+        return "😊 Positive", "positive"
     elif neg_count > pos_count:
-        return "☹️ Negative"
+        return "☹️ Negative", "negative"
     else:
-        return "😐 Neutral"
+        return "😐 Neutral", "neutral"
 
-# Analyze button
-if st.button("Analyze"):
+# Button & result
+if st.button("🔍 Analyze Sentiment"):
     if user_input.strip():
-        result = analyze_sentiment(user_input)
-        st.subheader("Sentiment Result:")
-        st.success(result)
+        sentiment, sentiment_class = analyze_sentiment(user_input)
+        st.markdown(f'<div class="result-box {sentiment_class}">{sentiment}</div>', unsafe_allow_html=True)
     else:
-        st.warning("Please enter some text.")
+        st.warning("⚠️ Please enter some text before analyzing.")
+
+# Footer
+st.markdown("---")
+st.markdown("Made with ❤️ using Streamlit | Rule-based approach")