Update app.py

app.py

@@ -1,28 +1,28 @@
 import gradio as gr
 from transformers import pipeline
 
-# 🚀 Use lightweight, faster FLAN model
-generator = pipeline("text2text-generation", model="google/flan-t5-xs")
+# ✅ Fast + available model
+generator = pipeline("text2text-generation", model="google/flan-t5-small")
 
-# ✨ Prompt Template
+# 🧠 Prompt Template
 TEMPLATE = (
     "You are a polite and professional customer support agent. "
     "Please respond to the customer's message:\n\n{input}"
 )
 
-# 🎯 Response Function
+# 🔁 Generate Reply
 def generate_reply(user_input):
     prompt = TEMPLATE.format(input=user_input)
     response = generator(prompt, max_length=80, do_sample=False)[0]["generated_text"]
     return response.strip()
 
-# 🎛 Interface
+# 🎛️ 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="Fast & polite auto-replies to customer complaints using a tiny FLAN-T5 model. Perfect for CRM or helpdesk automation.",
+    description="Generate fast, polite, and professional replies to customer messages using Google's FLAN-T5.",
     examples=[
         ["I still haven't received my order and it's been 10 days."],
         ["Why was I charged twice for my subscription?"],