Update app.py

app.py

@@ -27,14 +27,13 @@ candidate_tasks = [
 def generate_response(intent, human=True):
     if human:
         prompt = (
-            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."
+            f"Write a customer service message for intent '{intent}' using 3 clearly separated segments: "
+            "[Greeting] + [You currently have Plan X with ¥X/month. We recommend Plan Y offering XXGB at ¥Y/month.] + [Would you like to switch now?] "
+            "Use placeholder numbers and express one sentence per section."
         )
     else:
         prompt = (
-            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."
+            f"Resolve customer request: '{intent}' in one short sentence directly addressing their need. Use clear and polite tone with placeholder plan/price."
         )
     return text_generator(prompt, max_new_tokens=80, do_sample=True)[0]['generated_text']
 
@@ -81,7 +80,8 @@ if selected_customer not in st.session_state.chat_sessions:
         "chat": [],
         "system_result": None,
         "agent_reply": "",
-        "support_required": ""
+        "support_required": "",
+        "user_input": ""
     }
 session = st.session_state.chat_sessions[selected_customer]
 
@@ -95,12 +95,15 @@ for msg in session["chat"]:
 
 col1, col2 = st.columns([6,1])
 with col1:
-    user_input = st.text_input("Enter customer message:", key="user_input")
+    session["user_input"] = st.text_input("Enter customer message:", value=session["user_input"])
 with col2:
     analyze_clicked = st.button("Analyze", use_container_width=True)
 
-if analyze_clicked and user_input.strip():
+if analyze_clicked and session["user_input"].strip():
+    user_input = session["user_input"]
     session["chat"].append({"role": "user", "content": user_input})
+    session["user_input"] = ""
+
     emotion_result = emotion_classifier(user_input)
     emotion_label = get_emotion_label(emotion_result, user_input)
     emotion_score = get_emotion_score(emotion_label)
@@ -159,4 +162,5 @@ if st.button("End Conversation"):
     session["system_result"] = None
     session["agent_reply"] = ""
     session["support_required"] = ""
+    session["user_input"] = ""
     st.success("Conversation ended and cleared.")