app.py

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

# Load pre-trained model and tokenizer
model_name = "gpt2"
model = AutoModelForSeq2SeqLM.from_pretrained(model_name)
tokenizer = AutoTokenizer.from_pretrained(model_name)

# Function to generate remix
def generate_remix(input_text):
    input_ids = tokenizer(input_text, return_tensors="pt").input_ids
    output = model.generate(input_ids)
    output_text = tokenizer.decode(output[0], skip_special_tokens=True)
    return output_text

# Create Gradio interface
inputs = gr.inputs.Textbox(lines=5, label="Input Song Lyrics")
outputs = gr.outputs.Textbox(label="Remixed Song Lyrics")
title = "Song Remixing Tool"
description = "Enter the lyrics of a song and get a remix!"
examples = [["I'm feeling good", "Feeling happy tonight"]]

gr.Interface(generate_remix, inputs, outputs, title=title, description=description, examples=examples).launch()