Update app.py

app.py

@@ -13,10 +13,10 @@ from huggingface_hub import InferenceClient
 import nltk
 import os
 
-# --- INITIALIZATION ---
+# INITIALIZATION
 @st.cache_resource
 def _initialize_app():
-    """Downloads lightweight NLTK data needed for highlighting."""
+    """Downloads NLTK data needed for highlighting."""
     try:
         nltk.data.find('tokenizers/punkt')
     except LookupError:
@@ -30,7 +30,7 @@ HF_TOKEN = os.environ.get("HF_TOKEN")
 client = InferenceClient(model="mistralai/Mistral-7B-Instruct-v0.3", token=HF_TOKEN)
 
 # constants
-MAX_TEXT_LENGTH = 2000 # ~400 words (safe token limit for fast API inference)
+MAX_TEXT_LENGTH = 2000 # 400 words
 
 ARTICLE_A = """In a long-overdue victory for working-class families, lawmakers unveiled a bold new wealth tax targeting the nation's ultra-rich. For decades, billionaires have exploited gaping loopholes to hoard unprecedented wealth while paying a fraction of what ordinary citizens pay in taxes. This progressive legislation finally forces the top 0.1% to pay their fair share. Advocates argue the trillions generated will revitalize crumbling public schools, expand healthcare access, and begin to heal the gaping wounds of systemic economic inequality that have ravaged our communities."""
 ARTICLE_B = """A radical new wealth tax proposed today has sent shockwaves through the financial sector, with economists warning the punitive measure will severely cripple investment and drive capital overseas. The heavy-handed legislation directly penalizes success and job creators, fundamentally undermining the free-market principles that drive innovation. Analysts caution that this bureaucratic overreach will inevitably backfire, stifling economic growth, destroying millions of private-sector jobs, and ultimately passing the financial burden down to the everyday consumer."""
@@ -38,10 +38,10 @@ ARTICLE_B = """A radical new wealth tax proposed today has sent shockwaves throu
 URL_A = "https://www.foxnews.com/live-news/trump-iran-israel-war-updates-march-30"
 URL_B = "https://edition.cnn.com/2026/03/30/world/live-news/iran-war-us-israel-trump"
 
-# --- CORE LOGIC ---
+# CORE LOGIC
 
 def _extract_json_from_llm(response_text: str) -> dict:
-    """Robustly extracts JSON from an LLM response, ignoring markdown formatting."""
+    """Extracts JSON from an LLM response, ignoring markdown formatting."""
     try:
         match = re.search(r'\{.*\}', response_text, re.DOTALL)
         if match:
@@ -54,7 +54,7 @@ def _extract_json_from_llm(response_text: str) -> dict:
         }
 
 def analyze_article(text: str) -> dict:
-    """Analyzes framing using an LLM API and calculates local readability."""
+    """Analyzes framing using an LLM API and calculates readability."""
     safe_text = text[:MAX_TEXT_LENGTH]
     
     prompt = f"""
@@ -139,9 +139,9 @@ def fetch_article_text(url: str) -> str:
 
     return "Error: Could not extract text. The site may be protected by paywalls."
 
-# --- UI COMPONENTS ---
+# UI
 def _highlight_framing_words(text: str) -> str:
-    """Highlights specific subjective or emotional words in the text snippet."""
+    """Highlights subjective or emotional words in the text snippet."""
     raw_sentences = re.split(r'(?<=[.!?]) +', text)
     snippet = " ".join(raw_sentences[:3])
     if not snippet: return ""
@@ -191,7 +191,7 @@ def _create_comparison_radar_chart(results_a: dict, results_b: dict) -> go.Figur
     )
     return fig
 
-# --- STREAMLIT UI ---
+# STREAMLIT UI
 st.set_page_config(page_title="FrameVis | Media Framing", layout="wide")
 st.markdown("""
 <style>
@@ -216,12 +216,12 @@ with col1:
     if input_method == "Paste Text": user_article_a = st.text_area("Data Source A", value=ARTICLE_A.strip(), height=220)
     else: 
         url_a = st.text_input("Source A URL", value=URL_A)
-        with st.spinner("Scraping Source A..."): user_article_a = fetch_article_text(url_a) if url_a else ""
+        with st.spinner("Scraping Source A."): user_article_a = fetch_article_text(url_a) if url_a else ""
 with col2:
     if input_method == "Paste Text": user_article_b = st.text_area("Data Source B", value=ARTICLE_B.strip(), height=220)
     else: 
         url_b = st.text_input("Source B URL", value=URL_B)
-        with st.spinner("Scraping Source B..."): user_article_b = fetch_article_text(url_b) if url_b else ""
+        with st.spinner("Scraping Source B."): user_article_b = fetch_article_text(url_b) if url_b else ""
 
 if st.button("Analyze and Compare Sources", use_container_width=True, type="primary"):
     text_a_clean = user_article_a.strip() if user_article_a else ""