# Use FixKRetriever to avoid hang caused by the Huggingface
from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import FixKRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.openicl.icl_evaluator import AccEvaluator
from opencompass.datasets import commonsenseqaDataset
from opencompass.utils.text_postprocessors import first_capital_postprocess

commonsenseqa_reader_cfg = dict(
    input_columns=["question", "A", "B", "C", "D", "E"],
    output_column="answerKey",
    test_split="validation")

_ice_template = dict(
    type=PromptTemplate,
    template=dict(
        begin="</E>",
        round=[
            dict(
                role="HUMAN",
                prompt=
                "{question}\nA. {A}\nB. {B}\nC. {C}\nD. {D}\nE. {E}\nAnswer:",
            ),
            dict(
                role="BOT",
                prompt="{answerKey}",
            ),
        ],
    ),
    ice_token="</E>",
)

commonsenseqa_infer_cfg = dict(
    ice_template=_ice_template,
    retriever=dict(type=FixKRetriever, fix_id_list=[0, 1, 2, 3, 4, 5, 6, 7]),
    inferencer=dict(type=GenInferencer),
)

commonsenseqa_eval_cfg = dict(
    evaluator=dict(type=AccEvaluator),
    pred_postprocessor=dict(type=first_capital_postprocess),
)

commonsenseqa_datasets = [
    dict(
        abbr='commonsense_qa',
        type=commonsenseqaDataset,
        path='./data/commonsenseqa',
        reader_cfg=commonsenseqa_reader_cfg,
        infer_cfg=commonsenseqa_infer_cfg,
        eval_cfg=commonsenseqa_eval_cfg,
    )
]

del _ice_template