from transformers import GPT2LMHeadModel, GPT2Tokenizer

def generate_text(prompt, max_length=50):
    model_name = "gpt2"
    tokenizer = GPT2Tokenizer.from_pretrained(model_name)
    model = GPT2LMHeadModel.from_pretrained(model_name)

    inputs = tokenizer.encode(prompt, return_tensors="pt")
    outputs = model.generate(inputs, max_length=max_length, num_return_sequences=1)
    text = tokenizer.decode(outputs[0], skip_special_tokens=True)
    return text