Update app.py

app.py

@@ -21,10 +21,25 @@ st.markdown("""
         body {
             background-color: #ffffff;
         }
-        h1 {
+        .title-wrapper {
+            display: inline-block;
+            white-space: nowrap;
+            overflow-x: auto;
+            max-width: 100%;
+        }
+        .title-wrapper::-webkit-scrollbar {
+            height: 4px;
+        }
+        .title-wrapper::-webkit-scrollbar-thumb {
+            background-color: #ccc;
+            border-radius: 2px;
+        }
+        .main-title {
             color: #002b45;
             font-family: 'Segoe UI', sans-serif;
-            font-size: 18px;
+            font-size: 26px;
+            font-weight: 600;
+            margin: 0;
         }
         .stTextInput > div > div > input,
         .stTextArea textarea {
@@ -46,50 +61,49 @@ st.markdown("""
     </style>
 """, unsafe_allow_html=True)
 
-# ----------- Header Section with Title Only -----------
+# ----------- Header Title (One-line, Scrollable if Long) -----------
 st.markdown("""
-    <div style="margin-bottom: 1.5rem;">
-        <h1 style="margin: 0;">📊 EquiPulse: Real-Time Stock News Sentiment</h1>
+    <div class="title-wrapper">
+        <h1 class="main-title">📊 EquiPulse: Real-Time Stock News Sentiment</h1>
     </div>
 """, unsafe_allow_html=True)
 
-
-# ----------- Clean Description Section -----------
+# ----------- Description Section -----------
 st.markdown("""
-<div style='font-size:16px; line-height:1.6; color: #333333;'>
-    Analyze financial sentiment from real-time news headlines related to your selected companies.
+<div style='font-size:16px; line-height:1.6; color: #333333; margin-bottom: 1rem;'>
+    Analyze real-time financial sentiment from news headlines related to companies you're interested in.
 </div>
 """, unsafe_allow_html=True)
 
 # ----------- Input Area -----------
-st.markdown("#### 🎯 Enter Your Target Company Tickers")
-free_text = st.text_area("Example: AAPL, NVDA, NKE", height=90)
+st.markdown("#### 🎯 Enter Company Tickers or Names")
+free_text = st.text_area("Example: AAPL, NVIDIA, Tesla", height=90)
 
+# ----------- Ticker Extraction -----------
 ner_pipeline = get_ner_pipeline()
 tickers = extract_org_entities(free_text, ner_pipeline)
 
 if tickers:
-    st.markdown(f"✅ **Identified Tickers:** `{', '.join(tickers)}`")
+    st.markdown(f"✅ **Recognized Tickers:** `{', '.join(tickers)}`")
 else:
     tickers = []
 
 # ----------- Action Button -----------
-if st.button("Get News and Sentiment"):
+if st.button("🔍 Get News and Sentiment"):
     if not tickers:
-        st.warning("⚠️ Please enter at least one recognizable company name.")
+        st.warning("⚠️ Please enter at least one recognizable company name or ticker.")
     else:
         sentiment_pipeline = get_sentiment_pipeline()
         progress_bar = st.progress(0)
         total_stocks = len(tickers)
 
         for idx, ticker in enumerate(tickers):
-            st.markdown(f"---\n#### 🔍 Analyzing: `{ticker}`")
+            st.markdown(f"---\n#### 🔍 Analyzing `{ticker}`")
 
             news_list = fetch_news(ticker)
 
             if news_list:
                 sentiments = [analyze_sentiment(news['title'], sentiment_pipeline) for news in news_list]
-
                 pos_count = sentiments.count("Positive")
                 neg_count = sentiments.count("Negative")
                 total = len(sentiments)
@@ -109,7 +123,7 @@ if st.button("Get News and Sentiment"):
 
                 st.success(f"📈 **Overall Sentiment for `{ticker}`: {overall}**")
             else:
-                st.info(f"No recent news available for `{ticker}`.")
+                st.info(f"No recent news found for `{ticker}`.")
 
             progress_bar.progress((idx + 1) / total_stocks)
             time.sleep(0.1)