Upload app (1).py

app (1).py

@@ -0,0 +1,139 @@
+import streamlit as st
+from func import (
+    get_sentiment_pipeline,
+    get_ner_pipeline,
+    fetch_news,
+    analyze_sentiment,
+    extract_org_entities,
+)
+import time
+
+# ----------- Page Config -----------
+st.set_page_config(
+    page_title="EquiPulse: Stock Sentiment Tracker",
+    layout="centered",
+    initial_sidebar_state="collapsed"
+)
+
+# ----------- Custom Styling -----------
+st.markdown("""
+    <style>
+        body {
+            background-color: #ffffff;
+        }
+        /* Title styling */
+        .main-title {
+            font-size: 32px;
+            font-weight: 700;
+            font-family: 'Segoe UI', sans-serif;
+            color: #002b45;
+            margin-bottom: 1.2rem;
+            white-space: nowrap;
+            overflow-x: auto;
+        }
+        .main-title::-webkit-scrollbar {
+            height: 4px;
+        }
+        .main-title::-webkit-scrollbar-thumb {
+            background-color: #ccc;
+            border-radius: 2px;
+        }
+        /* Input + Button styling */
+        .stTextInput > div > div > input,
+        .stTextArea textarea {
+            font-size: 16px;
+        }
+        .stButton>button {
+            background-color: #002b45;
+            color: white;
+            font-size: 16px;
+            padding: 0.4rem 1rem;
+            border-radius: 6px;
+        }
+        .stButton>button:hover {
+            background-color: #004b78;
+        }
+        .stMarkdown {
+            font-size: 16px;
+        }
+    </style>
+""", unsafe_allow_html=True)
+
+# ----------- Header Title (Centered + Bold + Large + Professional) -----------
+st.markdown("""
+    <style>
+        .centered-title {
+            text-align: center;
+            font-size: 36px;
+            font-weight: 800;
+            font-family: 'Segoe UI', sans-serif;
+            color: #002b45;
+            margin-top: 20px;
+            margin-bottom: 20px;
+        }
+    </style>
+    <div class="centered-title">📊 EquiPulse: Stock Sentiment Tracker</div>
+""", unsafe_allow_html=True)
+
+
+# ----------- Description Section -----------
+st.markdown("""
+<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, TSLA", height=90)
+
+# ----------- Ticker Extraction -----------
+ner_pipeline = get_ner_pipeline()
+tickers = extract_org_entities(free_text, ner_pipeline)
+
+if tickers:
+    st.markdown(f"✅ **Recognized Tickers:** `{', '.join(tickers)}`")
+else:
+    tickers = []
+
+# ----------- Action Button -----------
+if st.button("🔍 Get News and Sentiment"):
+    if not tickers:
+        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}`")
+
+            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)
+                pos_ratio = pos_count / total if total else 0
+                neg_ratio = neg_count / total if total else 0
+
+                # Simple heuristic for overall sentiment
+                if pos_ratio >= 0.25:
+                    overall = "Positive"
+                elif neg_ratio >= 0.75:
+                    overall = "Negative"
+                else:
+                    overall = "Neutral"
+
+                # Display news
+                st.markdown(f"**📰 Top News for `{ticker}`:**")
+                for i, news in enumerate(news_list[:3]):
+                    st.markdown(f"{i+1}. [{news['title']}]({news['link']}) — **{sentiments[i]}**")
+
+                st.success(f"📈 **Overall Sentiment for `{ticker}`: {overall}**")
+            else:
+                st.info(f"No recent news found for `{ticker}`.")
+
+            progress_bar.progress((idx + 1) / total_stocks)
+            time.sleep(0.1)