Testing and CI/CD

After identifying the right evaluation/validation function for the outputs, you can easily create unit tests and add them to your CI/CD workflow.

Unit tests in prompttools are called prompttests. They use the @prompttest annotation to transform a completion function into an efficient unit test. The prompttest framework executes and evaluates experiments so you can test prompts over time. For example:

import prompttools.prompttest as prompttest

@prompttest.prompttest(
    metric_name="is_valid_json",
    eval_fn=validate_json.evaluate,
    prompts=[create_json_prompt()],
)
def json_completion_fn(prompt: str):
    response = None
    if os.getenv("DEBUG", default=False):
        response = mock_openai_completion_fn(**{"prompt": prompt})
    else:
        response = openai.Completion.create(prompt)
    return response["choices"][0]["text"]

In the file, be sure to call the main() method of prompttest like you would for unittest.

if __name__ == "__main__":
    prompttest.main()