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