Update app.py

app.py

@@ -27,16 +27,16 @@ candidate_tasks = [
 def generate_response(intent, human=True):
     if human:
         prompt = (
-            f"Write a customer service message for intent '{intent}'. Structure into: "
-            "1. Greeting, 2. Description of customer's current service (Plan X ¥X/GB, etc.) and a suitable new option, "
-            "3. A polite closing question. Use placeholder data (Plan X, ¥X, etc.)."
+            f"Write a customer service message for intent '{intent}' in 3 sentences only. Each sentence must represent: "
+            "1. Greeting, 2. One-sentence description of customer's current service and a suitable option, "
+            "3. A short and polite question asking if the customer would like to proceed. Use placeholders like Plan X, ¥X, etc."
         )
     else:
         prompt = (
-            f"Reply to the following user request automatically: '{intent}'. Directly resolve the request in one helpful message. "
-            "If it's plan change, suggest suitable options. Use placeholders (Plan A ¥X/5GB, Plan B ¥Y/15GB, etc.)."
+            f"Automatically resolve the customer request: '{intent}' in one helpful and polite sentence."
+            " Use direct language and include relevant details like plan options or links, with placeholder values."
         )
-    return text_generator(prompt, max_new_tokens=100, do_sample=True)[0]['generated_text']
+    return text_generator(prompt, max_new_tokens=80, do_sample=True)[0]['generated_text']
 
 urgent_emotions = {"anger", "frustration", "anxiety", "urgency", "afraid", "annoyed"}
 moderate_emotions = {"confused", "sad", "tired", "concerned", "sadness"}
@@ -100,6 +100,7 @@ with col2:
     analyze_clicked = st.button("Analyze", use_container_width=True)
 
 if analyze_clicked and user_input.strip():
+    session["chat"].append({"role": "user", "content": user_input})
     emotion_result = emotion_classifier(user_input)
     emotion_label = get_emotion_label(emotion_result, user_input)
     emotion_score = get_emotion_score(emotion_label)
@@ -114,7 +115,6 @@ if analyze_clicked and user_input.strip():
         content_score += 0.4
 
     final_score = 0.5 * emotion_score + 0.5 * content_score
-    session["chat"].append({"role": "user", "content": user_input})
 
     if final_score < 0.5 and top_intents:
         intent = top_intents[0]
@@ -129,6 +129,7 @@ if analyze_clicked and user_input.strip():
             "intents": top_intents
         }
         session["support_required"] = "🔴 Human support required."
+        session["agent_reply"] = ""
 
 if session["support_required"]:
     st.markdown(f"### {session['support_required']}")