app.py

import gradio as gr
from transformers import pipeline

# Load pre-trained text generation pipeline
generator = pipeline("text-generation", model="gpt2")

# Define the function to generate text
def generate_text(prompt):
    generated = generator(prompt, max_length=50, num_return_sequences=1)
    return generated[0]['generated_text']

# Create the Gradio interface
iface = gr.Interface(
    fn=generate_text,
    inputs="text",
    outputs="text",
    title="Text Generation",
    description="Generate text using GPT-2"
)

# Launch the interface
if __name__ == "__main__":
    iface.launch()