# Copyright 2023 Allen Institute for AI
#
# 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,
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# limitations under the License.

# Lint as: python3
"""Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research"""


from pathlib import Path

import datasets
import os

logger = datasets.logging.get_logger(__name__)


_DESCRIPTION = """\
Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research
"""

_URL_LISTS = {
    "v1": "urls/v1.txt",
    "v1_5r1": "urls/v1_5r1.txt",
    "v1_5r1-sample": "urls/v1_5r1-sample.txt",
    "v1_5r2": "urls/v1_5r2.txt",
}
_VERSIONS = {
    "v1": "1.0.0",
    "v1_5r1": "1.5.0",
    "v1_5r1-sample": "1.5.0",
    "v1_5r2": "1.5.0",
}
_DATES = {
    "v1": "(Aug 2023)",
    "v1_5r1": "(Oct 2023)",
    "v1_5r1-sample": "(Oct 2023)",
    "v1_5r2": "Dolma v1.5r2 (Dec 2023)",
}
_BASE_URL = "https://olmo-data.org"

_DATA_DIR = os.environ.get("DOLMA_DATA_DIR", None)

_CITATION = """\
@article{dolma,
  title = {{Dolma: An Open Corpus of Three Trillion Tokens for Language Model Pretraining Research}},
  author = {
        Luca Soldaini and Rodney Kinney and Akshita Bhagia and Dustin Schwenk and David Atkinson and
        Russell Authur and Ben Bogin and Khyathi Chandu and Jennifer Dumas and Yanai Elazar and
        Valentin Hofmann and Ananya Harsh Jha and Sachin Kumar and Li Lucy and Xinxi Lyu and Ian Magnusson and
        Jacob Morrison and Niklas Muennighoff and Aakanksha Naik and Crystal Nam and Matthew E. Peters and
        Abhilasha Ravichander and Kyle Richardson and Zejiang Shen and Emma Strubell and Nishant Subramani and
        Oyvind Tafjord and Evan Pete Walsh and Hannaneh Hajishirzi and Noah A. Smith and Luke Zettlemoyer and
        Iz Beltagy and Dirk Groeneveld and Jesse Dodge and Kyle Lo
    },
  year = {2024},
  journal={arXiv preprint},
}
"""


class Dolma(datasets.GeneratorBasedBuilder):
    """Dolma: an Open Corpus of Three Trillion Tokens for Language Model Pretraining Research"""

    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=name,
            version=_VERSIONS[name],
            description=f"{_DESCRIPTION} {_DATES[name]}",
        )
        for name in _URL_LISTS.keys()
    ]

    DEFAULT_CONFIG_NAME = "v1_5r2"

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "id": datasets.Value("string"),
                    "text": datasets.Value("string"),
                    "metadata": datasets.Value("string"),
                    "added": datasets.Value("string"),
                    # "metadata": datasets.Value("")
                }
            ),
            supervised_keys=None,
        )

    def _split_generators(self, dl_manager):
        with open(_URL_LISTS[self.config.name], mode="rt", encoding="utf-8") as f:
            subset_urls = f.read().splitlines()

        breakpoint()

        subset_files = dl_manager.download(subset_urls)

        return [
            datasets.SplitGenerator(
                name=datasets.Split.TRAIN,  # type: ignore[assignment]
                gen_kwargs={"files": subset_files},
            )
        ]

    def _generate_examples(self, files):
        """This function returns the examples in the raw (text) form."""
        raise NotImplementedError("Dolma is a streaming dataset")