app.py

import gradio as gr
from transformers import pipeline

news_classifier = pipeline(task="text-classification",
                                    model='kozy9/news_classification_file',
                                    top_k=1,
                                    batch_size=32)


def chat_interface(user_text):
  if not user_text.strip():
    return "⚠️ Please type something."


  result = news_classifier(user_text)[0]
  label = result[0]['label']
  score = result[0]['score']

  # Format output nicely
  output = f"📰 Category: {label}\n"
  output += f"🎯 Confidence: {score:.2%}\n"

  return output

demo = gr.Interface(
fn=chat_interface,
title ="📰 News Article Classifier",
description = """This model classifies news articles into 4 categories:
    - 🌍 World
    - ⚽ Sports
    - 💼 Business
    - 🔬 Sci/Tech""",
inputs=gr.Textbox(lines=10,label="📝 Enter news headline or description", placeholder="Type or paste news text here..."),
outputs=gr.Textbox(lines=3, label="🏷️ Prediction"),
examples=[
        ["Scientists discover new planet in distant solar system"],
        ["Manchester United wins the championship"],
        ["Stock market reaches all-time high"],
        ["Peace talks begin between conflicting nations"],
        ["new chip was invinted to develope AI"]
    ]
)

demo.launch()