app.py

import gradio as gr
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

# Load PEGASUS model
model_name = "tuner007/pegasus_paraphrase"
tokenizer = AutoTokenizer.from_pretrained(model_name)
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)

# Initialize pipeline
paraphrase_pipeline = pipeline("text2text-generation", model=model, tokenizer=tokenizer, truncation=True)

# Paraphrase function
def paraphrase_text(text):
    sentences = text.split(". ")  # Simple sentence split
    paraphrased_sentences = [paraphrase_pipeline(sentence, max_length=60, do_sample=False)[0]['generated_text'] for sentence in sentences]
    return " ".join(paraphrased_sentences)

# Gradio interface
demo = gr.Interface(fn=paraphrase_text, inputs="text", outputs="text", title="Text Paraphraser")

# Launch app
demo.launch()