Update app.py

app.py

@@ -10,6 +10,11 @@ from PIL import Image
 from datetime import datetime
 from transformers import pipeline as hf_pipeline  # prevent name collision with gradio pipeline
 
+def get_emotion_profile(text):
+    emotions = emotion_pipeline(text)
+    if isinstance(emotions, list) and isinstance(emotions[0], list):
+        emotions = emotions[0]
+    return {e['label'].lower(): round(e['score'], 3) for e in emotions}
 # Emotion model (no retraining needed)
 emotion_pipeline = hf_pipeline(
     "text-classification",
@@ -332,11 +337,8 @@ def compute_abuse_score(matched_scores, sentiment):
         adjusted_score += 10
 
     return min(adjusted_score, 100)
-    def get_emotion_profile(text):
-        emotions = emotion_pipeline(text)
-    if isinstance(emotions, list) and isinstance(emotions[0], list):
-        emotions = emotions[0]
-    return {e['label'].lower(): round(e['score'], 3) for e in emotions}
+    
+    
 def analyze_single_message(text, thresholds):
     motif_hits, matched_phrases = detect_motifs(text)