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4e789208b4
* `open_router.beta.responses.send()`: * `request` **Changed** **Breaking** ⚠️ * `response` **Changed** **Breaking** ⚠️ * `open_router.presets.create_presets_responses()`: `request` **Changed** **Breaking** ⚠️ * `open_router.presets.create_presets_chat_completions()`: `request` **Changed** **Breaking** ⚠️ * `open_router.chat.send()`: `request` **Changed** **Breaking** ⚠️ * `open_router.workspaces.set_budget()`: **Added** * `open_router.o_auth.create_auth_code()`: * `request.workspace_id` **Added** * `error.status[403]` **Added** * `open_router.files.download()`: **Added** * `open_router.models.get()`: **Added** * `open_router.workspaces.list_budgets()`: **Added** * `open_router.workspaces.delete_budget()`: **Added** * `open_router.datasets.get_benchmarks_artificial_analysis()`: **Added** * `open_router.beta.analytics.query_analytics()`: `response.data.warnings` **Added** * `open_router.files.delete()`: **Added** * `open_router.files.retrieve()`: **Added** * `open_router.files.upload()`: **Added** * `open_router.embeddings.list_models()`: `response.data.[].benchmarks` **Added** * `open_router.models.list()`: * `request` **Changed** * `response.data.[].benchmarks` **Added** * `open_router.models.list_for_user()`: `response.data.[].benchmarks` **Added** * `open_router.files.list()`: **Added** * `open_router.presets.create_presets_messages()`: `request` **Changed** * `open_router.datasets.get_benchmarks_design_arena()`: **Added**
119 lines
3.3 KiB
Python
119 lines
3.3 KiB
Python
"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT."""
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from __future__ import annotations
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from openrouter.types import BaseModel, Nullable, UNSET_SENTINEL
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from pydantic import model_serializer
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from typing import Literal
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from typing_extensions import TypedDict
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class EloBoundsTypedDict(TypedDict):
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r"""ELO range across all returned models for normalization."""
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max: float
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r"""Maximum ELO in the result set."""
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min: float
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r"""Minimum ELO in the result set."""
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class EloBounds(BaseModel):
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r"""ELO range across all returned models for normalization."""
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max: float
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r"""Maximum ELO in the result set."""
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min: float
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r"""Minimum ELO in the result set."""
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BenchmarksDAMetaSource = Literal["design-arena",]
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r"""Data source identifier."""
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BenchmarksDAMetaSourceURL = Literal["https://www.designarena.ai",]
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r"""URL of the upstream data source."""
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BenchmarksDAMetaVersion = Literal["v1",]
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r"""Dataset version."""
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class BenchmarksDAMetaTypedDict(TypedDict):
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arena: str
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r"""The arena filter applied."""
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as_of: str
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r"""ISO-8601 timestamp of when this data was generated."""
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category: Nullable[str]
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r"""The category filter applied, or null if showing all."""
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citation: str
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r"""Required attribution when republishing this data."""
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elo_bounds: EloBoundsTypedDict
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r"""ELO range across all returned models for normalization."""
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model_count: int
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r"""Number of unique models in the response."""
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source: BenchmarksDAMetaSource
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r"""Data source identifier."""
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source_url: BenchmarksDAMetaSourceURL
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r"""URL of the upstream data source."""
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version: BenchmarksDAMetaVersion
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r"""Dataset version."""
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class BenchmarksDAMeta(BaseModel):
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arena: str
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r"""The arena filter applied."""
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as_of: str
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r"""ISO-8601 timestamp of when this data was generated."""
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category: Nullable[str]
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r"""The category filter applied, or null if showing all."""
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citation: str
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r"""Required attribution when republishing this data."""
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elo_bounds: EloBounds
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r"""ELO range across all returned models for normalization."""
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model_count: int
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r"""Number of unique models in the response."""
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source: BenchmarksDAMetaSource
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r"""Data source identifier."""
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source_url: BenchmarksDAMetaSourceURL
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r"""URL of the upstream data source."""
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version: BenchmarksDAMetaVersion
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r"""Dataset version."""
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@model_serializer(mode="wrap")
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def serialize_model(self, handler):
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optional_fields = []
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nullable_fields = ["category"]
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null_default_fields = []
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serialized = handler(self)
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m = {}
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for n, f in type(self).model_fields.items():
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k = f.alias or n
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val = serialized.get(k)
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serialized.pop(k, None)
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optional_nullable = k in optional_fields and k in nullable_fields
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is_set = (
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self.__pydantic_fields_set__.intersection({n})
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or k in null_default_fields
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) # pylint: disable=no-member
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if val is not None and val != UNSET_SENTINEL:
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m[k] = val
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elif val != UNSET_SENTINEL and (
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not k in optional_fields or (optional_nullable and is_set)
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):
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m[k] = val
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return m
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