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 hellaswagDatasetwithICE
from opencompass.utils.text_postprocessors import first_option_postprocess

hellaswag_reader_cfg = dict(
    input_columns=["ctx", "A", "B", "C", "D"],
    output_column="label",
    train_split="train",
    test_split="val",
)

hellaswag_infer_cfg = dict(
    ice_template=dict(
        type=PromptTemplate,
        template=dict(
            round=[
                dict(role="HUMAN", prompt=f"{{ctx}}\nA) {{A}}\nB) {{B}}\nC) {{C}}\nD) {{D}}\nWhat is the right option?"),
                dict(role="BOT", prompt="{label}\n"),
            ]
        ),
    ),
    prompt_template=dict(
        type=PromptTemplate,
        template=dict(
            begin=[
                dict(role="HUMAN", prompt="Continue the following text without adding any additional information or formatting:\n"),
                "</E>",
            ],
            round=[
                dict(role="HUMAN", prompt=f"{{ctx}}\nA) {{A}}\nB) {{B}}\nC) {{C}}\nD) {{D}}\nWhat is the right option?"),
                dict(role="BOT", prompt="{label}\n"),
            ],
        ),
        ice_token="</E>",
    ),
    retriever=dict(type=FixKRetriever, fix_id_list=list(range(10))),
    inferencer=dict(type=GenInferencer),
)

hellaswag_eval_cfg = dict(
    evaluator=dict(type=AccEvaluator),
    pred_role="BOT",
    pred_postprocessor=dict(type=first_option_postprocess, options="ABCD"),
)

hellaswag_datasets = [
    dict(
        abbr="hellaswag",
        type=hellaswagDatasetwithICE,
        path="./data/hellaswag/",
        reader_cfg=hellaswag_reader_cfg,
        infer_cfg=hellaswag_infer_cfg,
        eval_cfg=hellaswag_eval_cfg,
    )
]