# Install required libraries before running:
# pip install gradio transformers

import gradio as gr
from transformers import pipeline

# Load a pre-trained generative model from Hugging Face (GPT-2 for text generation)
generator = pipeline("text-generation", model="gpt2")

# Define function for text generation
def generate_text(prompt):
    result = generator(prompt, max_length=100, num_return_sequences=1)
    return result[0]['generated_text']

# Create a Gradio interface
interface = gr.Interface(
    fn=generate_text,
    inputs=gr.Textbox(lines=10, placeholder="Enter a prompt here..."),
    outputs="text",
    title="Text Generator App",
    description="Generate creative text using Hugging Face GPT-2 model."
)

# Launch the app (runs locally or in Hugging Face Spaces)
interface.launch()