"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT."""

from __future__ import annotations
from openrouter.types import BaseModel, Nullable, UNSET_SENTINEL, UnrecognizedStr
from pydantic import model_serializer
from typing import Literal, Union
from typing_extensions import TypedDict


UnifiedBenchmarksMetaSource = Union[
    Literal[
        "artificial-analysis",
        "design-arena",
    ],
    UnrecognizedStr,
]
r"""The source filter applied, or null when all sources are returned."""


UnifiedBenchmarksMetaVersion = Literal["v1",]
r"""Dataset version."""


class UnifiedBenchmarksMetaTypedDict(TypedDict):
    as_of: str
    r"""ISO-8601 timestamp of when this data was last updated."""
    citation: Nullable[str]
    r"""Required attribution when republishing this data, or null when results span multiple sources (attribute each item individually by its `source` discriminator)."""
    model_count: int
    r"""Number of unique models in the response."""
    source: Nullable[UnifiedBenchmarksMetaSource]
    r"""The source filter applied, or null when all sources are returned."""
    source_url: Nullable[str]
    r"""URL of the upstream data source, or null when results span multiple sources."""
    task_type: Nullable[str]
    r"""The task_type filter applied, or null if showing all."""
    version: UnifiedBenchmarksMetaVersion
    r"""Dataset version."""


class UnifiedBenchmarksMeta(BaseModel):
    as_of: str
    r"""ISO-8601 timestamp of when this data was last updated."""

    citation: Nullable[str]
    r"""Required attribution when republishing this data, or null when results span multiple sources (attribute each item individually by its `source` discriminator)."""

    model_count: int
    r"""Number of unique models in the response."""

    source: Nullable[UnifiedBenchmarksMetaSource]
    r"""The source filter applied, or null when all sources are returned."""

    source_url: Nullable[str]
    r"""URL of the upstream data source, or null when results span multiple sources."""

    task_type: Nullable[str]
    r"""The task_type filter applied, or null if showing all."""

    version: UnifiedBenchmarksMetaVersion
    r"""Dataset version."""

    @model_serializer(mode="wrap")
    def serialize_model(self, handler):
        serialized = handler(self)
        m = {}

        for n, f in type(self).model_fields.items():
            k = f.alias or n
            val = serialized.get(k, serialized.get(n))

            if val != UNSET_SENTINEL:
                m[k] = val

        return m