app.py

import gradio as gr
from transformers import AutoModelForSeq2SeqLM, AutoTokenizer

# Load model and tokenizer from Hugging Face
model = AutoModelForSeq2SeqLM.from_pretrained("asritha22bce/bart-positive-tone-finetuned")
tokenizer = AutoTokenizer.from_pretrained("asritha22bce/bart-positive-tone-finetuned")

# Function to process headlines
def neutralize_headline(headline):
    inputs = tokenizer(headline, return_tensors="pt", truncation=True, padding=True)
    outputs = model.generate(**inputs)
    neutralized_text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return neutralized_text

# Create Gradio UI
iface = gr.Interface(
    fn=neutralize_headline,
    inputs=gr.Textbox(lines=2, placeholder="Enter a negative/extreme headline..."),
    outputs="text",
    title="Headline Neutralizer",
    description="Converts extreme headlines into a neutral tone.",
)

iface.launch()