app.py

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

# Load tokenizer and model
tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
model = AutoModelForCausalLM.from_pretrained("openai-community/gpt2")

# Function to generate text
def generate_text(prompt, max_length=100):
    inputs = tokenizer(prompt, return_tensors="pt")
    outputs = model.generate(**inputs, max_length=max_length, do_sample=True, temperature=0.7)
    return tokenizer.decode(outputs[0], skip_special_tokens=True)

# Gradio Interface
interface = gr.Interface(
    fn=generate_text,
    inputs=[
        gr.Textbox(label="Prompt", placeholder="Enter your text here..."),
        gr.Slider(10, 200, value=100, step=10, label="Max Length")
    ],
    outputs="text",
    title="GPT-2 Text Generator",
    description="This app uses the `openai-community/gpt2` model to generate text."
)

if __name__ == "__main__":
    interface.launch()