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import streamlit as st
from api import analyze_news
import base64
import nest_asyncio
nest_asyncio.apply()
st.title("Company News Sentiment Analyzer")
company = st.text_input("Enter Company Name", placeholder="Example: Tesla")
source = st.selectbox("Select the source you want news from:", ("NewsOrg", "Yahoo News"))
if st.button("Fetch News & Analyze"):
if not company or not source:
st.error("Please enter a company name and select the source")
else:
with st.spinner("Fetching from API..."):
data = analyze_news(company=company, source=source)
if data:
st.subheader(f"Sentiment Analysis for {data['Company']}")
# Comparative Sentiment Score
st.write("### Comparative Sentiment Score")
sentiment_dist = data.get("Comparitive Sentiment Score", {})
st.json(sentiment_dist)
# Final Sentiment Analysis
st.write("### Final Sentiment Analysis")
st.success(data.get("Final Sentiment Analysis", "No analysis available"))
# Audio Player for Hindi TTS
if "Audio" in data:
st.write("### Listen to Hindi Summary")
audio_bytes = base64.b64decode(data["Audio"])
st.audio(audio_bytes, format="audio/mp3")
# Articles Display
st.write("### Articles:")
for idx, article in enumerate(data["Articles"]):
st.write(f"**{idx+1}. Title:** {article['Title']}")
st.write(f"**Sentiment:** {article['Sentiment']}")
st.write(f"**Summary:** {article['Summary']}")
st.markdown("---")
else:
st.error("Failed to fetch data from API.")
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