# 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 json
import os

import datasets


_DESCRIPTION = """\
RareBench is a pioneering benchmark designed to systematically evaluate the capabilities of LLMs within the realm of rare diseases.
"""

_HOMEPAGE = "https://github.com/chenxz1111/RareBench"

_URL = r"https://huggingface.co/datasets/chenxz/RareBench/resolve/main/data.zip"

data_list = [
    "RAMEDIS",
    "HMS",
    "MME",
    "LIRICAL",
    "PUMCH_ADM"
]

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


class RareBench(datasets.GeneratorBasedBuilder):
    BUILDER_CONFIGS = [
        RareBenchConfig(
            name=data_name,
        )
        for data_name in data_list
    ]
    
    def _info(self):
        features = datasets.Features(
            {
                "Phenotype": [datasets.Value("string")], 
                "RareDisease": [datasets.Value("string")],
                "Department": datasets.Value("string"), 
            }
        )
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=features,
            homepage=_HOMEPAGE,
        )

    def _split_generators(self, dl_manager):
        data_dir = dl_manager.download_and_extract(_URL)
        data_name = self.config.name
        return [
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={
                    "filepath": os.path.join(
                        data_dir, "data", f"{data_name}.jsonl"
                    ),
                },
            )
        ]

    def _generate_examples(self, filepath):
        with open(filepath, encoding="utf-8") as f:
            for idx, line in enumerate(f):
                key = f"{self.config.name}-{idx}"
                item = json.loads(line)
                yield key, {
                    "Phenotype": item["Phenotype"],
                    "RareDisease": item["RareDisease"],
                    "Department": item["Department"],
                }