Update app.py

app.py

@@ -10,11 +10,6 @@ from PIL import Image
 from datetime import datetime
 from transformers import pipeline as hf_pipeline  # prevent name collision with gradio pipeline
 
-def get_emotional_tone_tag(emotions, sentiment, patterns, abuse_score, 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",
@@ -130,9 +125,15 @@ ESCALATION_QUESTIONS = [
     ("Violence has increased in frequency or severity", 3),
     ("Partner monitors your calls/GPS/social media", 2)
 ]
-tone_tag = get_emotional_tone_tag(emotion_profile, sentiment, threshold_labels, abuse_score, text)
 
 
+def get_emotional_tone_tag(emotions, sentiment, patterns, abuse_score, text):
+    sadness = emotions.get("sadness", 0)
+    joy = emotions.get("joy", 0)
+    neutral = emotions.get("neutral", 0)
+    disgust = emotions.get("disgust", 0)
+    anger = emotions.get("anger", 0)
+    fear = emotions.get("fear", 0)
     # 1. Performative Regret
     if (
         sadness > 0.4 and