from dataclasses import dataclass, make_dataclass

from src.benchmarks import BenchmarksQA, BenchmarksLongDoc


def fields(raw_class):
    return [v for k, v in raw_class.__dict__.items() if k[:2] != "__" and k[-2:] != "__"]


# These classes are for user facing column names,
# to avoid having to change them all around the code
# when a modification is needed
@dataclass
class ColumnContent:
    name: str
    type: str
    displayed_by_default: bool
    hidden: bool = False
    never_hidden: bool = False


COL_NAME_AVG = "Average ⬆️"
COL_NAME_RETRIEVAL_MODEL = "Retrieval Method"
COL_NAME_RERANKING_MODEL = "Reranking Model"
COL_NAME_RETRIEVAL_MODEL_LINK = "Retrieval Model LINK"
COL_NAME_RERANKING_MODEL_LINK = "Reranking Model LINK"
COL_NAME_RANK = "Rank 🏆"
COL_NAME_REVISION = "Revision"
COL_NAME_TIMESTAMP = "Submission Date"
COL_NAME_IS_ANONYMOUS = "Anonymous Submission"


def get_default_auto_eval_column_dict():
    auto_eval_column_dict = []
    # Init
    auto_eval_column_dict.append(
        ["rank", ColumnContent, ColumnContent(COL_NAME_RANK, "number", True)]
    )
    auto_eval_column_dict.append(
        ["retrieval_model", ColumnContent, ColumnContent(COL_NAME_RETRIEVAL_MODEL, "markdown", True, hidden=False, never_hidden=True)]
    )
    auto_eval_column_dict.append(
        ["reranking_model", ColumnContent, ColumnContent(COL_NAME_RERANKING_MODEL, "markdown", True, hidden=False, never_hidden=True)]
    )
    auto_eval_column_dict.append(
        ["revision", ColumnContent, ColumnContent(COL_NAME_REVISION, "markdown", True, never_hidden=True)]
    )
    auto_eval_column_dict.append(
        ["timestamp", ColumnContent, ColumnContent(COL_NAME_TIMESTAMP, "date", True, never_hidden=True)]
    )
    auto_eval_column_dict.append(
        ["average", ColumnContent, ColumnContent(COL_NAME_AVG, "number", True)]
    )
    auto_eval_column_dict.append(
        ["retrieval_model_link", ColumnContent, ColumnContent(COL_NAME_RETRIEVAL_MODEL_LINK, "markdown", False, hidden=True, never_hidden=False)]
    )
    auto_eval_column_dict.append(
        ["reranking_model_link", ColumnContent, ColumnContent(COL_NAME_RERANKING_MODEL_LINK, "markdown", False, hidden=True, never_hidden=False)]
    )
    auto_eval_column_dict.append(
        ["is_anonymous", ColumnContent, ColumnContent(COL_NAME_IS_ANONYMOUS, "bool", False, hidden=True)]
    )
    return auto_eval_column_dict


def make_autoevalcolumn(cls_name="BenchmarksQA", benchmarks=BenchmarksQA):
    auto_eval_column_dict = get_default_auto_eval_column_dict()
    ## Leaderboard columns
    for benchmark in benchmarks:
        auto_eval_column_dict.append(
            [benchmark.name, ColumnContent, ColumnContent(benchmark.value.col_name, "number", True)]
        )

    # We use make dataclass to dynamically fill the scores from Tasks
    return make_dataclass(cls_name, auto_eval_column_dict, frozen=True)


AutoEvalColumnQA = make_autoevalcolumn(
    "AutoEvalColumnQA", BenchmarksQA)
AutoEvalColumnLongDoc = make_autoevalcolumn(
    "AutoEvalColumnLongDoc", BenchmarksLongDoc)


# Column selection
COLS_QA = [c.name for c in fields(AutoEvalColumnQA) if not c.hidden]
COLS_LONG_DOC = [c.name for c in fields(AutoEvalColumnLongDoc) if not c.hidden]
TYPES_QA = [c.type for c in fields(AutoEvalColumnQA) if not c.hidden]
TYPES_LONG_DOC = [c.type for c in fields(AutoEvalColumnLongDoc) if not c.hidden]
COLS_LITE = [c.name for c in fields(AutoEvalColumnQA) if c.displayed_by_default and not c.hidden]

QA_BENCHMARK_COLS = [t.value.col_name for t in BenchmarksQA]

LONG_DOC_BENCHMARK_COLS = [t.value.col_name for t in BenchmarksLongDoc]