src/display/utils.py

from dataclasses import dataclass, make_dataclass
from enum import Enum

import pandas as pd

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 = []
# Init
auto_eval_column_dict.append(["model_type", ColumnContent, ColumnContent("Type", "str", True)])
auto_eval_column_dict.append(["model", ColumnContent, ColumnContent("Model", "markdown", True, never_hidden=True)])
#Scores
for task in Tasks:
    auto_eval_column_dict.append([task.name, ColumnContent, ColumnContent(task.value.col_name, "number", True)])
# Model information
auto_eval_column_dict.append(["params", ColumnContent, ColumnContent("#Params (B)", "number", False)])
auto_eval_column_dict.append(["license", ColumnContent, ColumnContent("Hub License", "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)

## All the model information that we might need
@dataclass(frozen=True)
class ModelDetails:
    name: str
    display_name: str = ""
    symbol: str = "" # emoji


class ModelType(Enum):
    Frontier = ModelDetails(name="Frontier", symbol="🚀")
    OpenSource = ModelDetails(name="Open Source", symbol="🟢")
    Specialized = ModelDetails(name="RTL Specialized", symbol="🔶")
    Unknown = ModelDetails(name="", symbol="?")

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

    @staticmethod
    def from_str(type):
        if "Frontier" in type or "🚀" in type:
            return ModelType.Frontier
        if "Open Source" in type or "🟢" in type:
            return ModelType.OpenSource
        if "Specialized" in type or "🔶" in type:
            return ModelType.Specialized
        return ModelType.Unknown

# Column selection
COLS = [c.name for c in fields(AutoEvalColumn)]

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