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openrouter-python-sdk-retry…/src/openrouter/components/unifiedbenchmarksmeta.py
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Python

"""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