Create app.py

app.py

@@ -0,0 +1,30 @@
+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()