Skip to main content
An eval is a function that takes in a dataset, which contains a model’s outputs, and a function to evaluate that dataset. The eval gives you a score for the model’s outputs. The score can be an int, float, bool, or categorical value (string). All evals are instances of Eval. 
from tatara import Eval
def is_cyberpunk_check(record: Record) -> bool:
    prompt = "Check that the following text is an example of cyberpunk fiction: \n\n {}\n\n If it is cyberpunk, write <CYBERPUNK>. If it is not, write <NOT_CYBERPUNK>.".format(record['output'])
    response = openai_client.chat.completions.create(
        messages=[{"role": "user", "content": prompt}],
        model=model_name,
        temperature=temperature,
        frequency_penalty=freq_penalty,
        max_tokens=max_tokens,

    )
    ret = response.choices[0].message.content
    if "<CYBERPUNK>" in ret:
        return True
    elif "<NOT_CYBERPUNK>" in ret:
        return False
    else:
        return is_cyberpunk_check(record)

  cyberpunk_check = Eval(
        name = "is_cyberpunk_check",
        description = "Checks whether the text is cyberpunk fiction. If it is, it returns True. If it is not, it returns False. If it is unsure, it will call itself again.",
        eval_fn = is_cyberpunk_check,
    )