"""NLUCat dataset."""


import json

import datasets


_HOMEPAGE = ""

_CITATION = """\

"""

_DESCRIPTION = """\
NLUCat - Natural Language Understanding in Catalan
"""

_TRAIN_FILE = "train.json"
_DEV_FILE = "dev.json"
_TEST_FILE = "test.json"

class Nlucat(datasets.GeneratorBasedBuilder):

    VERSION = datasets.Version("1.0.0")

    def _info(self):
        return datasets.DatasetInfo(
            description=_DESCRIPTION,
            features=datasets.Features(
                {
                    "example": datasets.Value("string"),
                    "intent": datasets.Value("string"),
                    "slot_text": datasets.Sequence(datasets.Value("string")), 
                    "slot_tag": datasets.Sequence(datasets.Value("string")), 
                    "start_char": datasets.Sequence(datasets.Value("string")), 
                    "end_char": datasets.Sequence(datasets.Value("string"))
        
                }
            ),
            homepage=_HOMEPAGE,
            citation=_CITATION,
        )

    
    def _split_generators(self, dl_manager):
        """Returns SplitGenerators."""
        urls_to_download = {
            "train": f"{_TRAIN_FILE}",
            "dev": f"{_DEV_FILE}",
            "test": f"{_TEST_FILE}",
        }
        downloaded_files = dl_manager.download_and_extract(urls_to_download)

        return [
            datasets.SplitGenerator(name=datasets.Split.TRAIN, gen_kwargs={"filepath": downloaded_files["train"], "split": "train"}),
            datasets.SplitGenerator(name=datasets.Split.VALIDATION, gen_kwargs={"filepath": downloaded_files["dev"], "split": "validation"}),
            datasets.SplitGenerator(name=datasets.Split.TEST, gen_kwargs={"filepath": downloaded_files["test"], "split": "test"}),
        ]

    def _generate_examples(self, filepath, split):
        """Yields examples."""
        with open(filepath, encoding="utf-8") as f:
            dataset = json.load(f)
            for row in dataset["data"]:
                example = row["example"]
                intent = row["annotation"]["intent"]
                slot_text = [slot["Text"] for slot in row["annotation"]["slots"]]
                slot_tag = [slot["Tag"] for slot in row["annotation"]["slots"]]
                
                start_char = [answer["Start_char"] for answer in row["annotation"]["slots"]]
                end_char = [answer["End_char"] for answer in row["annotation"]["slots"]]
                
                yield row["id"], {
                    "example": example,
                    "intent": intent, 
                    "slot_text": slot_text, 
                    "slot_tag": slot_tag, 
                    "start_char": start_char, 
                    "end_char": end_char
                }