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Create app.py
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import gradio as gr
from transformers import pipeline
# Load conversational model
generator = pipeline("text-generation", model="microsoft/DialoGPT-medium")
# Template for polite brand-consistent tone
TEMPLATE = (
"You are a helpful and professional customer support agent. "
"Respond politely and concisely to the following customer complaint or question:\n\n"
"Customer: {input}\nSupport:"
)
def generate_reply(user_input):
prompt = TEMPLATE.format(input=user_input)
response = generator(prompt, max_length=100, do_sample=True, top_k=50, top_p=0.95)[0]['generated_text']
# Extract only the agent's reply
support_response = response.split("Support:")[-1].strip()
return support_response
iface = gr.Interface(
fn=generate_reply,
inputs=gr.Textbox(lines=6, placeholder="Enter customer message here..."),
outputs=gr.Textbox(label="Auto-Generated Reply"),
title="🤖 Auto-Reply Generator for Customer Support",
description="Generate polite and brand-consistent replies to customer questions using AI."
)
iface.launch()