Update model.py

model.py

@@ -56,7 +56,14 @@ def smart_summarize(text, n_clusters=1):
 def detect_emotion(text):
     try:
         result = emotion_pipeline(text)[0]
-        return result["label"]
+        label = result["label"].lower()
+
+        # Fallback boost for weak detection
+        fallback_triggers = ["frustrated", "angry", "disappointed", "cancel", "quit", "switch", "leaving", "hate"]
+        if label == "neutral" and any(trigger in text.lower() for trigger in fallback_triggers):
+            return "frustrated"
+
+        return label
     except Exception as e:
         logging.warning(f"Emotion detection failed: {e}")
         return "neutral"