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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:#333; 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 (Up to 5 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"], pipe=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 >= 0.5:
overall = "Positive"
elif neg_ratio >= 0.5:
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)
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