Update app.py

app.py

@@ -1,28 +1,30 @@
 import gradio as gr
 from transformers import pipeline
 
-# ✅ Fast + available model
+# ✅ Use Google's FLAN-T5 small (fast + publicly available)
 generator = pipeline("text2text-generation", model="google/flan-t5-small")
 
-# 🧠 Prompt Template
+# 🧠 Refined Prompt Template for Polite, Humble Tone
 TEMPLATE = (
-    "You are a polite and professional customer support agent. "
-    "Please respond to the customer's message:\n\n{input}"
+    "You are a courteous, humble, and professional customer support agent. "
+    "Please write a polite and helpful response to this customer message:\n\n"
+    "{input}\n\nResponse:"
 )
 
-# 🔁 Generate Reply
+# 🔁 Generate Reply Function
 def generate_reply(user_input):
     prompt = TEMPLATE.format(input=user_input)
-    response = generator(prompt, max_length=80, do_sample=False)[0]["generated_text"]
+    response = generator(prompt, max_length=100, do_sample=False)[0]["generated_text"]
+    
     return response.strip()
 
-# 🎛️ Interface
+# 🎛️ Gradio Interface
 iface = gr.Interface(
     fn=generate_reply,
     inputs=gr.Textbox(lines=6, label="Customer Message", placeholder="Enter complaint or question..."),
-    outputs=gr.Textbox(label="Support Reply"),
-    title="⚡ Fast Auto-Reply Generator for Customer Support",
-    description="Generate fast, polite, and professional replies to customer messages using Google's FLAN-T5.",
+    outputs=gr.Textbox(label="Polite Support Reply"),
+    title="💬 Polite Auto-Reply Generator for Customer Support",
+    description="Generate humble, polite, and brand-consistent replies using FLAN-T5. Ideal for CRM and helpdesk automation.",
     examples=[
         ["I still haven't received my order and it's been 10 days."],
         ["Why was I charged twice for my subscription?"],