app.py

import gradio as gr
from transformers import pipeline

# Load the text generation model
model_id = "gpt2"  # You can replace this with any model of your choice
generator = pipeline("text-generation", model=model_id)

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

# Create the Gradio interface
iface = gr.Interface(
    fn=generate_text,
    inputs=gr.inputs.Textbox(lines=2, placeholder="Enter your prompt here..."),
    outputs="text",
    title="Text Generation",
    description="Enter a prompt and the model will generate text based on it."
)

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