Update app.py

app.py

@@ -1,23 +1,9 @@
-import nltk
-try:
-    nltk.data.find('tokenizers/punkt')
-except LookupError:
-    nltk.download('punkt')
-
-import nltk
-nltk.download('punkt')
-
-
 import streamlit as st
 from api import get_news, NewsRequest
 from utils import text_to_speech
-import time
 import base64
-import os
 
-
-
-# Function to play audio automatically
+# Function to auto-play audio
 def autoplay_audio(file_path):
     with open(file_path, "rb") as audio_file:
         audio_bytes = audio_file.read()
@@ -29,20 +15,19 @@ def autoplay_audio(file_path):
     """
     st.markdown(audio_tag, unsafe_allow_html=True)
 
-# UI Function
+# Streamlit UI
 def main():
     st.set_page_config(page_title="News Sentiment & Summarization", layout="wide")
 
-    # Sidebar
+    # Sidebar UI
     st.sidebar.markdown(
         "<h1 style='color:#00FFAF; text-align:center;'>📰 News Finder</h1>", 
         unsafe_allow_html=True
     )
-    st.sidebar.write("Enter a company name below to get the latest summarized news with sentiment analysis:")
+    st.sidebar.write("Enter a company name to fetch the latest summarized news with sentiment analysis:")
 
     company_name = st.sidebar.text_input("🔎 Company Name:")
     fetch_button = st.sidebar.button("Fetch News")
-
     st.sidebar.markdown("---")
     sentiment_summary_placeholder = st.sidebar.empty()
 
@@ -53,13 +38,13 @@ def main():
 
     if fetch_button and company_name:
         response = get_news(NewsRequest(company=company_name))
-        articles = response["articles"]
+        articles = response.get("articles", [])
 
         if not articles:
             st.warning("No news found for this company.")
             return
 
-        # Calculate sentiment summary
+        # Sentiment summary display
         sentiments = [article['sentiment'] for article in articles]
         positive = sentiments.count("Positive")
         negative = sentiments.count("Negative")
@@ -74,6 +59,7 @@ def main():
             </div>
         """, unsafe_allow_html=True)
 
+        # Auto play audio summary of headlines
         all_headlines = ". ".join([f"{idx + 1}. {article['title']}" for idx, article in enumerate(articles)])
         audio_file = text_to_speech(all_headlines)
         if audio_file:
@@ -81,6 +67,7 @@ def main():
 
         st.write("## Latest News Articles")
 
+        # News cards
         for idx, article in enumerate(articles, start=1):
             sentiment_color = {
                 "Positive": "#4CAF50",