from dataclasses import dataclass, make_dataclass
from enum import Enum

from src.about import Tasks


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 modif is needed
@dataclass(frozen=True)
class ColumnContent:
    name: str
    type: str
    displayed_by_default: bool
    hidden: bool = False
    never_hidden: bool = False


## Leaderboard columns
auto_eval_column_dict = []
# Main columns (displayed by default, in order)
auto_eval_column_dict.append(("model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)))
auto_eval_column_dict.append(("organization", ColumnContent, ColumnContent("Organization", "str", True)))
auto_eval_column_dict.append(
    ("model_type_symbol", ColumnContent, ColumnContent("Model Type", "markdown", True, never_hidden=True))
)
# Cost/Efficiency metrics
auto_eval_column_dict.append(("agent_steps", ColumnContent, ColumnContent("Agent Steps", "number", True)))
auto_eval_column_dict.append(("cost_usd", ColumnContent, ColumnContent("Cost (USD)", "number", True)))
# Scores
for idx, task in enumerate(Tasks):
    # Only show overall ANLS (first task) by default
    displayed_by_default = idx == 0
    auto_eval_column_dict.append(
        (task.name, ColumnContent, ColumnContent(task.value.col_name, "number", displayed_by_default))
    )
# Model information (will be hidden in display but needed for filtering)
auto_eval_column_dict.append(("model_type", ColumnContent, ColumnContent("Type", "str", False, hidden=False)))
auto_eval_column_dict.append(("submission_date", ColumnContent, ColumnContent("Submission Date", "str", False)))
auto_eval_column_dict.append(("link", ColumnContent, ColumnContent("Link", "str", False, hidden=True)))

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

## For the queue columns in the submission tab
@dataclass(frozen=True)
class EvalQueueColumn:  # Queue column
    model = ColumnContent("model", "markdown", True)
    model_type = ColumnContent("model_type", "str", True)
    organization = ColumnContent("organization", "str", True)
    status = ColumnContent("status", "str", True)


## All the model information that we might need
@dataclass
class ModelDetails:
    name: str
    display_name: str = ""
    symbol: str = ""  # emoji fallback
    icon_filename: str = ""
    color: str = ""


class ModelType(Enum):
    API = ModelDetails(name="api", symbol="☁️", icon_filename="snow_cloud2.svg", color="#FF9F36")
    OpenWeight = ModelDetails(name="open-weight", symbol="🔓", icon_filename="snow_code.svg", color="#75CDD7")
    Unknown = ModelDetails(name="", symbol="?", icon_filename="", color="")

    def to_str(self, separator=" "):
        return f"{self.value.symbol}{separator}{self.value.name}"

    @staticmethod
    def from_str(type):
        if "api" in type.lower() or "🔌" in type:
            return ModelType.API
        if "open-weight" in type.lower() or "open weight" in type.lower() or "🔓" in type:
            return ModelType.OpenWeight
        return ModelType.Unknown


# Column selection
COLS = [c.name for c in fields(AutoEvalColumn) if not c.hidden]

EVAL_COLS = [c.name for c in fields(EvalQueueColumn)]
EVAL_TYPES = [c.type for c in fields(EvalQueueColumn)]

BENCHMARK_COLS = [t.value.col_name for t in Tasks]