## Python SDK Changes:

* `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**

src/openrouter/components/benchmarksdameta.py

@@ -0,0 +1,118 @@
+"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT."""
+
+from __future__ import annotations
+from openrouter.types import BaseModel, Nullable, UNSET_SENTINEL
+from pydantic import model_serializer
+from typing import Literal
+from typing_extensions import TypedDict
+
+
+class EloBoundsTypedDict(TypedDict):
+    r"""ELO range across all returned models for normalization."""
+
+    max: float
+    r"""Maximum ELO in the result set."""
+    min: float
+    r"""Minimum ELO in the result set."""
+
+
+class EloBounds(BaseModel):
+    r"""ELO range across all returned models for normalization."""
+
+    max: float
+    r"""Maximum ELO in the result set."""
+
+    min: float
+    r"""Minimum ELO in the result set."""
+
+
+BenchmarksDAMetaSource = Literal["design-arena",]
+r"""Data source identifier."""
+
+
+BenchmarksDAMetaSourceURL = Literal["https://www.designarena.ai",]
+r"""URL of the upstream data source."""
+
+
+BenchmarksDAMetaVersion = Literal["v1",]
+r"""Dataset version."""
+
+
+class BenchmarksDAMetaTypedDict(TypedDict):
+    arena: str
+    r"""The arena filter applied."""
+    as_of: str
+    r"""ISO-8601 timestamp of when this data was generated."""
+    category: Nullable[str]
+    r"""The category filter applied, or null if showing all."""
+    citation: str
+    r"""Required attribution when republishing this data."""
+    elo_bounds: EloBoundsTypedDict
+    r"""ELO range across all returned models for normalization."""
+    model_count: int
+    r"""Number of unique models in the response."""
+    source: BenchmarksDAMetaSource
+    r"""Data source identifier."""
+    source_url: BenchmarksDAMetaSourceURL
+    r"""URL of the upstream data source."""
+    version: BenchmarksDAMetaVersion
+    r"""Dataset version."""
+
+
+class BenchmarksDAMeta(BaseModel):
+    arena: str
+    r"""The arena filter applied."""
+
+    as_of: str
+    r"""ISO-8601 timestamp of when this data was generated."""
+
+    category: Nullable[str]
+    r"""The category filter applied, or null if showing all."""
+
+    citation: str
+    r"""Required attribution when republishing this data."""
+
+    elo_bounds: EloBounds
+    r"""ELO range across all returned models for normalization."""
+
+    model_count: int
+    r"""Number of unique models in the response."""
+
+    source: BenchmarksDAMetaSource
+    r"""Data source identifier."""
+
+    source_url: BenchmarksDAMetaSourceURL
+    r"""URL of the upstream data source."""
+
+    version: BenchmarksDAMetaVersion
+    r"""Dataset version."""
+
+    @model_serializer(mode="wrap")
+    def serialize_model(self, handler):
+        optional_fields = []
+        nullable_fields = ["category"]
+        null_default_fields = []
+
+        serialized = handler(self)
+
+        m = {}
+
+        for n, f in type(self).model_fields.items():
+            k = f.alias or n
+            val = serialized.get(k)
+            serialized.pop(k, None)
+
+            optional_nullable = k in optional_fields and k in nullable_fields
+            is_set = (
+                self.__pydantic_fields_set__.intersection({n})
+                or k in null_default_fields
+            )  # pylint: disable=no-member
+
+            if val is not None and val != UNSET_SENTINEL:
+                m[k] = val
+            elif val != UNSET_SENTINEL and (
+                not k in optional_fields or (optional_nullable and is_set)
+            ):
+                m[k] = val
+
+        return m