app.py

from transformers import pipeline
import gradio as gr

classifier = pipeline("zero-shot-classification", model="facebook/bart-large-mnli")

labels = ["service request", "complaint", "general discussion"]

def classify_text(text):
    result = classifier(text, labels)
    return {label: round(score, 4) for label, score in zip(result["labels"], result["scores"])}

demo = gr.Interface(
    fn=classify_text,
    inputs=gr.Textbox(lines=4, placeholder="Enter text to classify..."),
    outputs=gr.Label(num_top_classes=3),  # Display top 3 results
    title="Zero-Shot Text Classifier",
    description="Classify text into 'service request', 'complaint', or 'general discussion' using Hugging Face's zero-shot classification pipeline.",
)

if __name__ == "__main__":
    demo.launch(share=True)