import datasets
import os

_DESCRIPTION = """\
Dataset of meeting transcriptions and summaries of AMI courpus.
"""

_CITATION = """\
@InProceedings{Zhu_2015_ICCV,
    title = {AMI for summarization task},
    author = {Filipp Abapolov},
    month = {Fubruary},
    year = {2023}
}
"""

_REPO = "https://huggingface.co/datasets/pheepa/ami-summary/resolve/main"
_URL = f"{_REPO}/data/ami-summary.tar.gz"


class AmiSummary(datasets.GeneratorBasedBuilder):
    """AmiSummary dataset."""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name='ami-summary',
            version=datasets.Version("1.0.0"),
            description=_DESCRIPTION
        )
    ]

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "text": datasets.Value("string"),
                    "summary": datasets.Value("string")
                }
            ),
            supervised_keys=None,
            citation=_CITATION
        )

    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        data_dir = dl_manager.download_and_extract(_URL)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,
                gen_kwargs={"filepath": os.path.join(data_dir, "train_ami.txt")}
            ),
            datasets.SplitGenerator(
                name=datasets.Split.TEST,
                gen_kwargs={"filepath": os.path.join(data_dir, "test_ami.txt")}
            )
        ]

    def _generate_examples(self, filepath):
        """Yields examples."""
        with open(filepath, 'r') as f:
            lines = f.read().split('\n')
        pairs = []
        for i in range(0, len(lines[:-1]), 2):
            pairs.append((lines[i], lines[i + 1]))

        for i, comment in enumerate(pairs):
            yield i, {'text': pairs[0], 'summary': pairs[1]}