Update app.py

app.py

@@ -1,4 +1,3 @@
-# app.py
 import streamlit as st
 import requests
 from transformers import pipeline
@@ -21,7 +20,6 @@ NEWS_API_URL = "https://newsapi.org/v2/everything"
 @st.cache_resource
 def load_model():
     try:
-        # --- นี่คือส่วนที่แก้ไข ---
         print("Loading model: MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli")
         classifier = pipeline("zero-shot-classification", model="MoritzLaurer/DeBERTa-v3-base-mnli-fever-anli")
         print("Model loaded successfully!")
@@ -122,7 +120,7 @@ def search_yahoo_news(keyword, max_articles=10):
         st.error(f"Yahoo Search Error: {e}")
         return []
 
-# --- 5. ฟังก์ชันวิเคราะห์ (เหมือนเดิม) ---
+# --- 5. ฟังก์ชันวิเคราะห์ ---
 def analyze_themes(news_list, model, labels):
     results = []
     if not model:
@@ -143,7 +141,7 @@ def analyze_themes(news_list, model, labels):
             
     return pd.DataFrame(results)
 
-# --- 6. UI (อัปเกรด: รวม 2 แหล่งข่าว) ---
+# --- 6. UI ---
 st.title("📰 News Theme Analyzer")
 st.markdown("Analyzes news from trusted sources (Reuters, Bloomberg, Yahoo...)")
 
@@ -157,11 +155,9 @@ if st.button("Analyze News"):
     else:
         with st.spinner(f"Fetching and analyzing news for '{topic}'..."):
             
-            # 1. ดึงข่าวจาก 2 แหล่ง
             news_api = fetch_news_from_api(topic, API_KEY)
             news_yahoo = search_yahoo_news(topic)
             
-            # 2. รวมข่าวและลบข่าวซ้ำ
             all_news = news_api + news_yahoo
             seen_titles = set()
             unique_news_items = []
@@ -177,7 +173,6 @@ if st.button("Analyze News"):
                 if df.empty:
                     st.warning("Analysis failed, though news was fetched. Check logs.")
                 else:
-                    # 3. แสดงสรุป (เหมือนเดิม)
                     st.subheader("📊 Theme Distribution Summary")
                     theme_counts = df['theme'].value_counts()
                     total_articles = len(df)
@@ -194,7 +189,6 @@ if st.button("Analyze News"):
                     st.dataframe(pd.DataFrame(summary_data), use_container_width=True)
                     st.markdown("---")
 
-                    # 4. แสดงข่าว (เหมือนเดิม)
                     st.subheader(f"📰 Analysis Results (Found {len(df)} unique articles)")
                     
                     for index, row in df.iterrows():