from llamafactory.data import Role
from llamafactory.data.converter import get_dataset_converter
from llamafactory.data.parser import DatasetAttr
from llamafactory.hparams import DataArguments


def test_alpaca_converter():
    dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset")
    data_args = DataArguments()
    example = {
        "instruction": "Solve the math problem.",
        "input": "3 + 4",
        "output": "The answer is 7.",
    }
    dataset_converter = get_dataset_converter("alpaca", dataset_attr, data_args)
    assert dataset_converter(example) == {
        "_prompt": [{"role": Role.USER.value, "content": "Solve the math problem.\n3 + 4"}],
        "_response": [{"role": Role.ASSISTANT.value, "content": "The answer is 7."}],
        "_system": "",
        "_tools": "",
        "_images": None,
        "_videos": None,
        "_audios": None,
    }


def test_sharegpt_converter():
    dataset_attr = DatasetAttr("hf_hub", "llamafactory/tiny-supervised-dataset")
    data_args = DataArguments()
    example = {
        "conversations": [
            {"from": "system", "value": "You are a helpful assistant."},
            {"from": "human", "value": "Solve the math problem.\n3 + 4"},
            {"from": "gpt", "value": "The answer is 7."},
        ]
    }
    dataset_converter = get_dataset_converter("sharegpt", dataset_attr, data_args)
    assert dataset_converter(example) == {
        "_prompt": [{"role": Role.USER.value, "content": "Solve the math problem.\n3 + 4"}],
        "_response": [{"role": Role.ASSISTANT.value, "content": "The answer is 7."}],
        "_system": "You are a helpful assistant.",
        "_tools": "",
        "_images": None,
        "_videos": None,
        "_audios": None,
    }