Update app.py

app.py

@@ -47,24 +47,21 @@ def analyze_messages(input_text):
 
     # First 14 = pattern scores
     pattern_scores = scores[:14]
-    pattern_count = int(np.sum(pattern_scores > 0.5))
+    pattern_count = int(np.sum(pattern_scores > 0.15))
 
     # Last 3 = danger cues
     danger_scores = scores[14:]
-    danger_flag_count = int(np.sum(danger_scores > 0.5))
-
+    danger_flag_count = int(np.sum(danger_scores > 0.20))
     # (Optional) Print label-by-label for debugging
     for i, s in enumerate(scores):
         print(LABELS[i], "=", round(s, 3))
     
-    # Map danger flag count to Danger Assessment Score
-    if danger_flag_count >= 2:
-        danger_assessment = "High"
-    elif danger_flag_count == 1:
-        danger_assessment = "Moderate"
-    else:
-        danger_assessment = "Low"
-    
+   
+    danger_assessment = (
+    "High" if danger_flag_count >= 2 else
+    "Moderate" if danger_flag_count == 1 else
+    "Low"
+)
     # Customize resource links based on Danger Assessment Score (with additional niche support)
     if danger_assessment == "High":
         resources = (
@@ -88,13 +85,13 @@ def analyze_messages(input_text):
             "**Community Support:** Consider community-based and online support groups, especially those focused on LGBTQ+, immigrant, and neurodivergent survivors."
         )
     
-    # Prepare the output result with both scores
-    result_md = (
-        f"**Abuse Pattern Count:** {pattern_count}\n\n"
-        f"**Danger Assessment Score:** {danger_assessment}\n\n"
-        f"**Support Resources:**\n{resources}"
-    )
-    
+   
+    # Prepare the output result with just pattern count and dynamic resources
+result_md = (
+    f"**Abuse Pattern Count:** {pattern_count}\n\n"
+    f"**Support Resources:**\n{resources}"
+)
+ 
     # Save the result to a temporary text file for download
     with tempfile.NamedTemporaryFile(delete=False, suffix=".txt", mode="w") as f:
         f.write(result_md)