from opencompass.openicl.icl_prompt_template import PromptTemplate
from opencompass.openicl.icl_retriever import ZeroRetriever
from opencompass.openicl.icl_inferencer import GenInferencer
from opencompass.datasets import MATHDataset, MATHEvaluator, math_postprocess_v2, normalize_final_answer

math_reader_cfg = dict(input_columns=["problem"], output_column="solution")

math_infer_cfg = dict(
    prompt_template=dict(
        type=PromptTemplate,
        template=dict(
            round=[
                dict(role="HUMAN", prompt="{problem}\nPlease reason step by step, and put your final answer within \\boxed{}."),
            ]
        ),
    ),
    retriever=dict(type=ZeroRetriever),
    inferencer=dict(type=GenInferencer, max_out_len=1024),
)

# postprocess v2
math_eval_cfg = dict(
    evaluator=dict(type=MATHEvaluator, version="v2"), pred_postprocessor=dict(type=math_postprocess_v2),
)

math_datasets = [
    dict(
        type=MATHDataset,
        abbr="math",
        path="./data/math/math.json",
        reader_cfg=math_reader_cfg,
        infer_cfg=math_infer_cfg,
        eval_cfg=math_eval_cfg,
    )
]
