import json

import datasets


class JMTEBlite(datasets.GeneratorBasedBuilder):
    # Define builder configs directly in the class
    BUILDER_CONFIGS = [
        datasets.BuilderConfig(
            name=name,
            description=f"JMTEB-lite dataset configuration for {name}",
        )
        for name in [
            "livedoor_news",
            "mewsc16_ja",
            "sib200_japanese_clustering",
            "amazon_review_classification",
            "amazon_counterfactual_classification",
            "massive_intent_classification",
            "massive_scenario_classification",
            "japanese_sentiment_classification",
            "sib200_japanese_classification",
            "wrime_classification",
            "jsts",
            "jsick",
            "jaqket-query",
            "jaqket-corpus",  # lightweight
            "mrtydi-query",
            "mrtydi-corpus",  # lightweight
            "jagovfaqs_22k-query",
            "jagovfaqs_22k-corpus",
            "nlp_journal_title_abs-query",
            "nlp_journal_title_abs-corpus",
            "nlp_journal_title_intro-query",
            "nlp_journal_title_intro-corpus",
            "nlp_journal_abs_intro-query",
            "nlp_journal_abs_intro-corpus",
            "nlp_journal_abs_article-query",
            "nlp_journal_abs_article-corpus",
            "jacwir-retrieval-query",
            "jacwir-retrieval-corpus",  # lightweight
            "miracl-retrieval-query",
            "miracl-retrieval-corpus",  # lightweight
            "mldr-retrieval-query",
            "mldr-retrieval-corpus",
            "mintaka-retrieval-query",
            "mintaka-retrieval-corpus",
            "esci-query",
            "esci-corpus",
            "jqara-query",
            "jqara-corpus",  # lightweight
            "jacwir-reranking-query",
            "jacwir-reranking-corpus",  # lightweight
            "miracl-reranking-query",
            "miracl-reranking-corpus",
            "mldr-reranking-query",
            "mldr-reranking-corpus",
        ]
    ]

    def _info(self):
        builder = datasets.load_dataset_builder(
            "sbintuitions/JMTEB",
            self.config.name,
            trust_remote_code=True,
        )
        return datasets.DatasetInfo(
            description=f"{self.config.name} in JMTEB-lite:" + builder.info.description,
            citation=builder.info.citation,
            homepage=builder.info.homepage,
            license=builder.info.license,
            features=builder.info.features,
        )

    def _split_generators(self, dl_manager):
        if self.config.name in [
            "jacwir-retrieval-corpus",
            "jaqket-corpus",
            "miracl-retrieval-corpus",
            "mrtydi-corpus",
        ]:
            filename = self.config.name.replace("corpus", "lite-corpus")
            data_file = dl_manager.download(f"Retrieval-lite-data/{filename}.jsonl")
            return [
                datasets.SplitGenerator(
                    name="corpus", gen_kwargs={"filepath": data_file, "split": "corpus"}
                )
            ]

        if self.config.name in ["jacwir-reranking-corpus", "jqara-corpus"]:
            filename = self.config.name.replace("corpus", "lite-corpus")
            data_file = dl_manager.download(f"Reranking-lite-data/{filename}.jsonl")
            return [
                datasets.SplitGenerator(
                    name="corpus", gen_kwargs={"filepath": data_file, "split": "corpus"}
                )
            ]

        if self.config.name in ["jacwir-reranking-query", "jqara-query"]:
            filename = self.config.name.replace("query", "lite-query-{split}.jsonl")
            return [
                datasets.SplitGenerator(
                    name=split,
                    gen_kwargs={
                        "filepath": dl_manager.download(
                            f"Reranking-lite-data/{filename.format(split=split)}"
                        ),
                        "split": split,
                    },
                )
                for split in ["validation", "test"]
            ]

        original = datasets.load_dataset(
            "sbintuitions/JMTEB", self.config.name, trust_remote_code=True
        )
        return [
            datasets.SplitGenerator(name=split, gen_kwargs={"split": split})
            for split in original.keys()
        ]

    def _generate_examples(self, split, filepath=None):
        if filepath:
            with open(filepath, "r", encoding="utf-8") as f:
                for i, line in enumerate(f):
                    example = json.loads(line.strip())
                    yield i, example
        else:
            original_split = datasets.load_dataset(
                "sbintuitions/JMTEB",
                self.config.name,
                split=split,
                trust_remote_code=True,
            )
            for i, example in enumerate(original_split):
                yield i, example