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):
    generated = generator(
        prompt,
        max_length=30,           # Limit the output length
        do_sample=True,          # Enable sampling for more natural responses
        temperature=0.3,         # Lower temperature for less randomness
        repetition_penalty=1.5,  # Penalize repeated tokens
        no_repeat_ngram_size=2   # Avoid repeating any 2-word sequences
    )
    return generated[0]['generated_text']

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, factual answer."
)

iface.launch()