Update app.py

app.py

@@ -22,13 +22,33 @@ candidate_tasks = [
     "upgrade device"
 ]
 
-# Emotion categories (updated)
+# Emotion scoring
 urgent_emotions = {"anger", "frustration", "anxiety", "urgency", "afraid", "annoyed"}
-moderate_emotions = {"confused", "sad", "tired", "concerned"}
+moderate_emotions = {"confused", "sad", "tired", "concerned", "sadness"}
 
-def get_emotion_label(emotion_result):
+# ⬇️ 情绪判断（融合模型输出 + 语言信号）
+def get_emotion_label(emotion_result, text):
     sorted_emotions = sorted(emotion_result[0], key=lambda x: x['score'], reverse=True)
-    return sorted_emotions[0]['label']
+    top_emotion = sorted_emotions[0]['label']
+    return refine_emotion_label(text, top_emotion)
+
+def refine_emotion_label(text, model_emotion):
+    text_lower = text.lower()
+    urgent_keywords = ["fix", "now", "immediately", "urgent", "can't", "need", "asap"]
+    exclamations = text.count("!")
+    upper_words = sum(1 for word in text.split() if word.isupper())
+
+    signal_score = 0
+    if any(word in text_lower for word in urgent_keywords):
+        signal_score += 1
+    if exclamations >= 2:
+        signal_score += 1
+    if upper_words >= 1:
+        signal_score += 1
+
+    if model_emotion.lower() in {"joy", "neutral", "sadness"} and signal_score >= 2:
+        return "urgency"
+    return model_emotion
 
 def get_emotion_score(emotion):
     if emotion.lower() in urgent_emotions:
@@ -50,7 +70,6 @@ def get_content_score(text, top_intents):
     return min(score + 0.1, 1.0)
 
 def generate_reply(input_text, intent):
-    # Intent-specific suggestion sentences
     intent_solutions = {
         "top up balance": "Your balance is ¥12. Current promo: recharge ¥100 get ¥5 bonus.",
         "reactivate service": "Your service is suspended due to unpaid ¥38. Recharge to restore within 30 mins.",
@@ -61,8 +80,6 @@ def generate_reply(input_text, intent):
         "upgrade device": "You're eligible for upgrade. New iPhone plan starts at ¥399/month.",
         "report service outage": "We're detecting signal issues in your area (ZIP: XXX). Engineers notified."
     }
-
-    # Intent-specific closing question
     intent_closings = {
         "top up balance": "Would you like to proceed with a recharge now?",
         "reactivate service": "Shall I help you restart your service now?",
@@ -77,10 +94,9 @@ def generate_reply(input_text, intent):
     solution = intent_solutions.get(intent.lower(), "Here's how we can assist you with this issue.")
     closing = intent_closings.get(intent.lower(), "Is there anything else I can help with?")
     opening = "Thank you for contacting us. I understand your concern."
-
     return f"{opening} {solution} {closing}"
 
-# Streamlit UI
+# UI
 st.set_page_config(page_title="Customer Support Assistant", layout="centered")
 st.title("📞 Smart Customer Support Assistant (for Agents Only)")
 
@@ -92,9 +108,9 @@ if st.button("Analyze Message"):
     else:
         with st.spinner("Processing..."):
 
-            # Emotion detection (updated)
+            # Emotion detection (model + rule)
             emotion_result = emotion_classifier(user_input)
-            emotion_label = get_emotion_label(emotion_result)
+            emotion_label = get_emotion_label(emotion_result, user_input)
             emotion_score = get_emotion_score(emotion_label)
 
             # Intent detection