app.py

import gradio as gr
from transformers import pipeline

# Load model
pipe = pipeline("text-generation", model="gpt2")  # Replace with your Hugging Face model ID

def generate_response(prompt, max_length, temperature):
    output = pipe(
        prompt,
        max_length=max_length,
        temperature=temperature,
        do_sample=True,
        pad_token_id=pipe.tokenizer.eos_token_id
    )
    return output[0]["generated_text"]

# Gradio Interface
with gr.Blocks(theme=gr.themes.Soft()) as demo:
    gr.Markdown("# 📝 AI Text Generator")
    gr.Markdown("Enter your prompt and generate creative text using a Hugging Face model.")

    with gr.Row():
        with gr.Column(scale=2):
            prompt = gr.Textbox(
                label="Prompt",
                placeholder="Type your prompt here...",
                lines=4
            )
            max_length = gr.Slider(20, 500, value=200, step=10, label="Max Length")
            temperature = gr.Slider(0.1, 1.5, value=0.7, step=0.1, label="Temperature")
            generate_btn = gr.Button("Generate")

        with gr.Column(scale=3):
            output = gr.Textbox(label="Generated Output", lines=10)

    generate_btn.click(
        fn=generate_response,
        inputs=[prompt, max_length, temperature],
        outputs=[output]
    )

demo.launch()