Update app.py

app.py

@@ -25,7 +25,7 @@ def get_model():
         ).to(device).eval()
     return tokenizer, model
 
-# UPDATED: Threshold changed from 0.81 to 0.59
+# UPDATED: Threshold set to 59% for visual triggers
 THRESHOLD = 0.59 
 
 # -----------------------------
@@ -72,7 +72,7 @@ def analyze(text):
         return "—", "—", "<em>Please enter text...</em>", None
         
     word_count = len(text.split())
-    # Word count remains at 300
+    # Word count requirement restored to 300
     if word_count < 300:
         warning_msg = f"⚠️ <b>Insufficient Text:</b> Your input has {word_count} words. Please enter at least 300 words for an accurate analysis."
         return "Too Short", "N/A", f"<div style='color: #b80d0d; padding: 20px; border: 1px solid #b80d0d; border-radius: 8px;'>{warning_msg}</div>", None
@@ -104,7 +104,7 @@ def analyze(text):
     weighted_avg = sum(p * l for p, l in zip(probs, lengths)) / total_words if total_words > 0 else 0
 
     # -----------------------------
-    # HTML RECONSTRUCTION
+    # HTML RECONSTRUCTION (Highlights trigger at THRESHOLD)
     # -----------------------------
     highlighted_html = "<div style='font-family: sans-serif; line-height: 1.8;'>"
     prob_map = {idx: probs[i] for i, idx in enumerate(pure_sents_indices)}
@@ -116,7 +116,7 @@ def analyze(text):
         
         if i in prob_map:
             score = prob_map[i]
-            # Logic now uses the 0.59 threshold
+            # Color determined by the new 59% threshold
             if score >= THRESHOLD:
                 color, bg = "#b80d0d", "rgba(184, 13, 13, 0.15)" # RED
             else: