Update app.py

app.py

@@ -1,16 +1,12 @@
 import streamlit as st
 from transformers import pipeline
 
-# Load pipelines
-emotion_classifier = pipeline(
-    "text-classification",
-    model="j-hartmann/emotion-english-distilroberta-base",
-    return_all_scores=True
-)
+# Load models
+emotion_classifier = pipeline("text-classification", model="j-hartmann/emotion-english-distilroberta-base", return_all_scores=True)
 intent_classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")
-text_generator = pipeline("text2text-generation", model="google/flan-t5-base")
-
+text_generator = pipeline("text2text-generation", model="google/flan-t5-large")
 
+# Intent categories
 candidate_tasks = [
     "change mobile plan", "top up balance", "report service outage",
     "ask for billing support", "reactivate service", "cancel subscription",
@@ -46,28 +42,19 @@ def get_emotion_score(emotion):
     else:
         return 0.2
 
+# ✅ Simplified fixed-format auto-reply
 def generate_response(intent, human=True):
     if human:
         prompt = (
-            f"You are a professional telecom support agent. The customer intends to '{intent}'. "
-            "Please generate a structured 3-part response:\n\n"
-            "1. Start with a short, polite greeting.\n"
-            "2. Mention customer is currently on a fictional plan (e.g., Plan X, ¥68/month), then recommend a better plan (e.g., Plan Y, ¥88/month, 20GB).\n"
-            "3. Ask if they'd like to proceed with the switch or need more details."
+            f"You are a telecom agent. The customer intends to '{intent}'. "
+            "Give a 3-part polite reply: 1) Greeting, 2) Mention current plan (fictional) and suggest better one, 3) Ask if want to proceed."
         )
+        result = text_generator(prompt, max_new_tokens=150, do_sample=False)
+        return result[0]['generated_text'].strip()
     else:
-        prompt = (
-            f"The user intends to '{intent}' in a telecom support context. "
-            "Generate a complete structured reply with three parts:\n\n"
-            "1. Greet the user.\n"
-            "2. Provide a fictional current plan and recommend an upgrade.\n"
-            "3. End with a follow-up question to confirm.\n\n"
-            "Do not ask what plan the user has — assume and invent fictional details clearly."
-        )
-    result = text_generator(prompt, max_new_tokens=150, do_sample=False)
-    return result[0]['generated_text'].strip()
+        return f"[Below is a link to the service you need：{intent} → https://support.example.com/{intent.replace(' ', '_')}]\\n[If your problem still can not be solved, welcome to continue to consult, we will continue to serve you!]"
 
-# Streamlit UI
+# Streamlit App
 st.set_page_config(page_title="Smart Customer Support Assistant", layout="wide")
 st.sidebar.title("📁 Customer Selector")
 
@@ -87,14 +74,14 @@ if selected_customer not in st.session_state.chat_sessions:
 session = st.session_state.chat_sessions[selected_customer]
 st.title("Smart Customer Support Assistant (for Agents Only)")
 
-# Show conversation
+# 💬 Conversation
 st.markdown("### Conversation")
 for msg in session["chat"]:
     avatar = "👤" if msg['role'] == 'user' else ("🤖" if msg.get("auto") else "👨‍💼")
     with st.chat_message(msg['role'], avatar=avatar):
         st.markdown(msg['content'])
 
-# Input + Analyze
+# 🔍 Analyze input
 col1, col2 = st.columns([6, 1])
 with col1:
     user_input = st.text_input("Enter customer message:", key="customer_input")
@@ -133,7 +120,7 @@ with col2:
                 session["agent_reply"] = ""
             st.rerun()
 
-# Priority & Agent reply
+# 🧠 Agent reply
 if session["support_required"]:
     st.markdown(f"### {session['support_required']}")
 
@@ -147,7 +134,7 @@ if st.button("Send Reply"):
         session["support_required"] = ""
         st.rerun()
 
-# Detected needs
+# 🔍 If human required
 if session["system_result"] is not None:
     st.markdown("#### Customer Status")
     st.markdown(f"- **Emotion:** {session['system_result']['emotion'].capitalize()}")
@@ -158,7 +145,6 @@ if session["system_result"] is not None:
         st.markdown(f"**• {intent.capitalize()}**")
         st.code(suggestion)
 
-# End conversation
 if st.button("End Conversation"):
     session["chat"] = []
     session["system_result"] = None