src/display/utils.py

from dataclasses import dataclass, make_dataclass, field
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:] != "__"]

# Define ColumnContent class
@dataclass
class ColumnContent:
    name: str
    type: str
    displayed_by_default: bool
    hidden: bool = False
    never_hidden: bool = False

# Define auto_eval_column_dict with correct structure
auto_eval_column_dict = [
    ("model", ColumnContent, field(default_factory=lambda: ColumnContent("Model", "markdown", True, never_hidden=True))),
    ("org", ColumnContent, field(default_factory=lambda: ColumnContent("Organization", "str", True))),
    ("average", ColumnContent, field(default_factory=lambda: ColumnContent("Aiera Score ⬆️", "number", True))),
]

# Add task-specific columns
for task in Tasks:
    auto_eval_column_dict.append(
        (task.value.benchmark, ColumnContent, field(default_factory=lambda task=task: ColumnContent(task.value.col_name, "number", True)))
    )

# Add remaining columns
auto_eval_column_dict.extend([
    ("params", ColumnContent, field(default_factory=lambda: ColumnContent("#Params (B)", "number", False))),
    ("still_on_hub", ColumnContent, field(default_factory=lambda: ColumnContent("Available on the hub", "bool", False))),
    ("license", ColumnContent, field(default_factory=lambda: ColumnContent("License", "str", False))),
])

# Dynamically create the AutoEvalColumn dataclass
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)
    private = ColumnContent("private", "bool", False)
    status = ColumnContent("status", "str", True)

@dataclass(frozen=True)
class FailedEvalQueueColumn:  # Queue column
    model = ColumnContent("model", "markdown", True)
    private = ColumnContent("private", "bool", False)
    status = ColumnContent("status", "str", True)
    reason = ColumnContent("reason", "str", True)

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

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

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

FAILED_EVAL_COLS = [c.name for c in fields(FailedEvalQueueColumn)]
FAILED_EVAL_TYPES = [c.type for c in fields(FailedEvalQueueColumn)]

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