# Copyright 2020 The HuggingFace Datasets Authors and the current dataset script contributor.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
#     http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

import os
import datasets
import pandas as pd


_CITATION = """\
@misc{wei2024aceval,
      title={AC-EVAL: Evaluating Ancient Chinese Language Understanding in Large Language Models}, 
      author={Yuting Wei and Yuanxing Xu and Xinru Wei and Simin Yang and Yangfu Zhu and Yuqing Li and Di Liu and Bin Wu},
      year={2024},
      eprint={2403.06574},
      archivePrefix={arXiv},
      primaryClass={cs.CL}
}
"""

_DESCRIPTION = """\
AC-EVAL presents a thorough evaluation suite for Large Language Models (LLMs) focusing on ancient Chinese, covering eras from the Pre-Qin period to the Qing dynasty. This suite includes 3245 multi-choice questions across 3 levels of difficulty and 13 diverse tasks.
"""

_HOMEPAGE = "https://github.com/yuting-wei/AC-EVAL"

_LICENSE = "Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License"

_URL = r"https://huggingface.co/datasets/yuting-wei/aceval/resolve/main/aceval.zip"

task_list = [
    'historical_facts', 
    'geography',
    'social_customs',
    'art_and_cultural_heritage',
    'philosophy_and_religion',
    'lexical_pragmatics_analysis',
    'allusions_and_idioms',
    'word_sense_disambiguation',
    'translation',
    'event_extraction',
    'sentence_pauses',
    'summarization_and_analysis',
    'poetry_appreciation'
]


class ACEVALConfig(datasets.BuilderConfig):
    def __init__(self, **kwargs):
        super().__init__(version=datasets.Version("1.0.0"), **kwargs)


class ACEVAL(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        ACEVALConfig(
            name=task_name
        ) 
        for task_name in task_list
    ]

    def _info(self):
        features = datasets.Features(
            {
                "Question": datasets.Value("string"),
                "A": datasets.Value("string"),
                "B": datasets.Value("string"),
                "C": datasets.Value("string"),
                "D": datasets.Value("string"),
                "Answer": datasets.Value("string"),
                "Explanation":datasets.Value("string"),
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
            license=_LICENSE,
            citation=_CITATION,
        )

    def _split_generators(self, dl_manager):
        data_dir = dl_manager.download_and_extract(_URL)
        task_name = self.config.name
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": os.path.join(data_dir, f"test/{task_name}.csv"),
                },
            ),
            datasets.SplitGenerator(
                name=datasets.Split("dev"),
                gen_kwargs={
                    "filepath": os.path.join(data_dir, f"dev/{task_name}.csv"),
                },
            ),
        ]

    def _generate_examples(self, filepath):
        df = pd.read_csv(filepath, header=0, index_col=0, encoding="utf-8")
        for i, instance in enumerate(df.to_dict(orient="records")):
            if "Answer" not in instance.keys():
                instance["Answer"]=""
            if "Explanation" not in instance.keys():
                instance["Explanation"]=""
            yield i, instance