Update model.py

model.py

@@ -52,12 +52,16 @@ def smart_summarize(text, n_clusters=1):
         logging.error(f"Smart summarize error: {e}")
         return text
 
-# === Emotion Detection ===
+# === Emotion Detection (Fixed) ===
 def detect_emotion(text):
     try:
         result = emotion_pipeline(text)
-        top_label = result[0][0]["label"] if isinstance(result[0], list) else result[0]["label"]
-        return top_label
+        if isinstance(result, list) and len(result) > 0:
+            item = result[0]
+            if isinstance(item, list):  # Nested list case
+                return item[0]["label"]
+            return item["label"]
+        return "neutral"
     except Exception as e:
         logging.warning(f"Emotion detection failed: {e}")
         return "neutral"
@@ -65,9 +69,13 @@ def detect_emotion(text):
 # === Follow-up Q&A ===
 def answer_followup(text, question, verbosity="brief"):
     try:
+        if not question:
+            return "No question provided."
         if isinstance(question, list):
             answers = []
             for q in question:
+                if not q.strip():
+                    continue
                 response = qa_pipeline({"question": q, "context": text})
                 ans = response.get("answer", "")
                 answers.append(f"**{q}** → {ans}" if verbosity.lower() == "detailed" else ans)
@@ -80,6 +88,7 @@ def answer_followup(text, question, verbosity="brief"):
         logging.warning(f"Follow-up error: {e}")
         return "Sorry, I couldn't generate a follow-up answer."
 
+# === Direct follow-up route handler ===
 def answer_only(text, question):
     try:
         if not question:
@@ -106,10 +115,6 @@ def assess_churn_risk(sentiment_label, emotion_label):
 
 # === Pain Point Extractor ===
 def extract_pain_points(text):
-    """
-    Returns a list of keyword-based user pain points.
-    Later you can extend with transformer-based aspect mining (KeyBERT, LLMs).
-    """
     common_issues = [
         "slow", "crash", "lag", "expensive", "confusing", "noisy", "poor", "rude",
         "unhelpful", "bug", "broken", "unresponsive", "not working", "error", "delay", "disconnect"