import gradio as gr
from transformers import pipeline

# Create a text-generation pipeline using GPT-2 with modified parameters
generator = pipeline('text-generation', model='gpt2')

def generate_text(prompt):
    # Use a lower temperature and limit the max_length for concise output
    generated = generator(
        prompt,
        max_length=30,       # Limit the maximum length of the output
        do_sample=False,     # Disable sampling for deterministic output
        temperature=0.2      # Lower temperature to reduce randomness
    )
    return generated[0]['generated_text']

# Create a Gradio interface
iface = gr.Interface(
    fn=generate_text,
    inputs="text",
    outputs="text",
    title="Simple LLM with Hugging Face & Gradio",
    description="Enter a prompt and get a concise text generated by GPT-2."
)

# Launch the interface
iface.launch()