Update app.py

app.py

@@ -1,21 +1,19 @@
 import gradio as gr
 from transformers import pipeline
 
-# ✅ Use Google's FLAN-T5 small (fast + publicly available)
+# ✅ Fast model
 generator = pipeline("text2text-generation", model="google/flan-t5-small")
 
-# 🧠 Refined Prompt Template for Polite, Humble Tone
+# 🧠 Prompt Template
 TEMPLATE = (
-    "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:"
+    "You are a polite, humble, and professional customer support agent. "
+    "Respond to the following customer message:\n\n{input}\n\nReply:"
 )
 
-# 🔁 Generate Reply Function
+# 🔁 Generate Reply
 def generate_reply(user_input):
     prompt = TEMPLATE.format(input=user_input)
-    response = generator(prompt, max_length=100, do_sample=False)[0]["generated_text"]
-    
+    response = generator(prompt, max_length=60, do_sample=False)[0]["generated_text"]
     return response.strip()
 
 # 🎛️ Gradio Interface
@@ -23,8 +21,8 @@ iface = gr.Interface(
     fn=generate_reply,
     inputs=gr.Textbox(lines=6, label="Customer Message", placeholder="Enter complaint or question..."),
     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.",
+    title="⚡ Ultra-Fast Auto-Reply Generator for Customer Support",
+    description="Get polite, helpful replies in seconds using FLAN-T5-small. Built for speed + tone.",
     examples=[
         ["I still haven't received my order and it's been 10 days."],
         ["Why was I charged twice for my subscription?"],