import gradio as gr
from transformers import pipeline

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

def generate_text(prompt):
    # Adjust temperature to make output more focused
    generated = generator(
        prompt,
        max_length=50,
        num_return_sequences=1,
        temperature=0.2,  # Lower temperature for less randomness
        top_k=50,         # Optional: limit the number of choices
        top_p=0.95        # Optional: nucleus sampling
    )
    return generated[0]['generated_text']


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

# Launch the interface
iface.launch()