Update app.py

app.py

@@ -97,55 +97,54 @@ if 'system_result' not in st.session_state:
 if 'agent_reply' not in st.session_state:
     st.session_state.agent_reply = ""
 
-# Display chat history
+# Always show conversation
+st.markdown("### Conversation")
 for msg in st.session_state.chat:
     with st.chat_message(msg['role']):
         st.markdown(msg['content'])
 
-# Customer input + Analyze button
-col1, col2 = st.columns([5,1])
+# Input row with button aligned right
+col1, col2 = st.columns([6,1])
 with col1:
     user_input = st.text_input("Enter customer message:", key="user_input")
 with col2:
-    if st.button("Analyze"):
-        if user_input.strip():
-            # Run analysis pipeline
-            emotion_result = emotion_classifier(user_input)
-            emotion_label = get_emotion_label(emotion_result, user_input)
-            emotion_score = get_emotion_score(emotion_label)
-
-            intent_result = intent_classifier(user_input, candidate_tasks)
-            top_intents = [label for label, score in zip(intent_result['labels'], intent_result['scores']) if score > 0.15][:3]
-
-            content_score = 0.0
-            if any(x in user_input.lower() for x in ["out of service", "can't", "urgent", "immediately"]):
-                content_score += 0.4
-            if any(label in ["top up balance", "reactivate service"] for label in top_intents):
-                content_score += 0.4
-
-            final_score = 0.5 * emotion_score + 0.5 * content_score
-
-            # Store user message
-            st.session_state.chat.append({"role": "user", "content": user_input})
-
-            # Auto response or escalate to agent
-            if final_score < 0.5 and top_intents:
-                intent = top_intents[0]
-                response = f"Thank you for contacting us. I understand your concern. {intent_solutions[intent]} {intent_closings[intent]}"
-                st.session_state.chat.append({"role": "assistant", "content": response})
-            else:
-                st.session_state.system_result = {
-                    "emotion": emotion_label,
-                    "tone": "Urgent" if emotion_score > 0.8 else "Concerned" if emotion_score > 0.5 else "Calm",
-                    "intents": top_intents
-                }
-
-# If human support needed
+    analyze_clicked = st.button("Analyze")
+
+if analyze_clicked and user_input.strip():
+    # Run analysis pipeline
+    emotion_result = emotion_classifier(user_input)
+    emotion_label = get_emotion_label(emotion_result, user_input)
+    emotion_score = get_emotion_score(emotion_label)
+
+    intent_result = intent_classifier(user_input, candidate_tasks)
+    top_intents = [label for label, score in zip(intent_result['labels'], intent_result['scores']) if score > 0.15][:3]
+
+    content_score = 0.0
+    if any(x in user_input.lower() for x in ["out of service", "can't", "urgent", "immediately"]):
+        content_score += 0.4
+    if any(label in ["top up balance", "reactivate service"] for label in top_intents):
+        content_score += 0.4
+
+    final_score = 0.5 * emotion_score + 0.5 * content_score
+
+    st.session_state.chat.append({"role": "user", "content": user_input})
+
+    if final_score < 0.5 and top_intents:
+        intent = top_intents[0]
+        response = f"Thank you for contacting us. I understand your concern. {intent_solutions[intent]} {intent_closings[intent]}"
+        st.session_state.chat.append({"role": "assistant", "content": response})
+    else:
+        st.session_state.system_result = {
+            "emotion": emotion_label,
+            "tone": "Urgent" if emotion_score > 0.8 else "Concerned" if emotion_score > 0.5 else "Calm",
+            "intents": top_intents
+        }
+
+# Agent panel only if human support needed
 if st.session_state.system_result:
     st.markdown("---")
-    st.subheader("Agent Response Panel")
+    st.subheader("⚠️ Human Support Required")
 
-    # Agent editable response
     st.session_state.agent_reply = st.text_area("Compose your reply:", value=st.session_state.agent_reply)
     if st.button("Send Reply"):
         if st.session_state.agent_reply.strip():
@@ -153,15 +152,13 @@ if st.session_state.system_result:
             st.session_state.agent_reply = ""
             st.session_state.system_result = None
 
-    # Context info
     st.markdown("#### Customer Status")
     st.markdown(f"- **Emotion:** {st.session_state.system_result['emotion'].capitalize()}")
     st.markdown(f"- **Tone:** {st.session_state.system_result['tone']}")
 
-    # Suggested replies
     st.markdown("#### Detected Customer Needs")
     for intent in st.session_state.system_result['intents']:
-        st.markdown(f"**• {intent.capitalize()}**")
         suggestion = f"Thank you for contacting us. I understand your concern. {intent_solutions[intent]} {intent_closings[intent]}"
-        if st.button(f"Use suggestion for '{intent}'", key=intent):
+        st.markdown(f"**• {intent.capitalize()}**")
+        if st.button(suggestion, key=f"btn_{intent}"):
             st.session_state.agent_reply = suggestion