import csv
import json
import os.path as osp

from datasets import Dataset, DatasetDict

from opencompass.registry import LOAD_DATASET

from .base import BaseDataset


@LOAD_DATASET.register_module()
class CEvalDataset(BaseDataset):

    @staticmethod
    def load(path: str, name: str):
        dataset = {}
        for split in ['dev', 'val', 'test']:
            filename = osp.join(path, split, f'{name}_{split}.csv')
            with open(filename, encoding='utf-8') as f:
                reader = csv.reader(f)
                header = next(reader)
                for row in reader:
                    item = dict(zip(header, row))
                    item.setdefault('explanation', '')
                    item.setdefault('answer', '')
                    dataset.setdefault(split, []).append(item)
        dataset = {i: Dataset.from_list(dataset[i]) for i in dataset}
        return DatasetDict(dataset)


class CEvalDatasetClean(BaseDataset):

    # load the contamination annotations of CEval from
    # https://github.com/liyucheng09/Contamination_Detector
    @staticmethod
    def load_contamination_annotations(path, split='val'):
        import requests

        assert split == 'val', 'Now we only have annotations for val set'
        annotation_cache_path = osp.join(
            path, split, 'ceval_contamination_annotations.json')
        if osp.exists(annotation_cache_path):
            with open(annotation_cache_path, 'r') as f:
                annotations = json.load(f)
            return annotations
        link_of_annotations = 'https://github.com/liyucheng09/Contamination_Detector/releases/download/v0.1.1rc/ceval_annotations.json'  # noqa
        annotations = json.loads(requests.get(link_of_annotations).text)
        with open(annotation_cache_path, 'w') as f:
            json.dump(annotations, f)
        return annotations

    @staticmethod
    def load(path: str, name: str):
        dataset = {}
        for split in ['dev', 'val', 'test']:
            if split == 'val':
                annotations = CEvalDatasetClean.load_contamination_annotations(
                    path, split)
            filename = osp.join(path, split, f'{name}_{split}.csv')
            with open(filename, encoding='utf-8') as f:
                reader = csv.reader(f)
                header = next(reader)
                for row_index, row in enumerate(reader):
                    item = dict(zip(header, row))
                    item.setdefault('explanation', '')
                    item.setdefault('answer', '')
                    if split == 'val':
                        row_id = f'{name}-{row_index}'
                        if row_id in annotations:
                            item['is_clean'] = annotations[row_id][0]
                        else:
                            item['is_clean'] = 'not labeled'
                    dataset.setdefault(split, []).append(item)
        dataset = {i: Dataset.from_list(dataset[i]) for i in dataset}
        return DatasetDict(dataset)