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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**
271 lines
11 KiB
Python
271 lines
11 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 datetime import datetime
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from openrouter.types import BaseModel, UnrecognizedStr
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from openrouter.utils import (
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FieldMetadata,
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HeaderMetadata,
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RequestMetadata,
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validate_open_enum,
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)
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import pydantic
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from pydantic.functional_validators import PlainValidator
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from typing import List, Literal, Optional, Union
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from typing_extensions import Annotated, NotRequired, TypeAliasType, TypedDict
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class QueryAnalyticsGlobalsTypedDict(TypedDict):
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http_referer: NotRequired[str]
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r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
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This is used to track API usage per application.
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"""
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x_open_router_title: NotRequired[str]
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r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.
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"""
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x_open_router_categories: NotRequired[str]
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r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.
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"""
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class QueryAnalyticsGlobals(BaseModel):
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http_referer: Annotated[
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Optional[str],
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pydantic.Field(alias="HTTP-Referer"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
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This is used to track API usage per application.
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"""
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x_open_router_title: Annotated[
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Optional[str],
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pydantic.Field(alias="X-OpenRouter-Title"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.
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"""
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x_open_router_categories: Annotated[
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Optional[str],
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pydantic.Field(alias="X-OpenRouter-Categories"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.
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"""
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Value2TypedDict = TypeAliasType("Value2TypedDict", Union[str, float])
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Value2 = TypeAliasType("Value2", Union[str, float])
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Value1TypedDict = TypeAliasType(
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"Value1TypedDict", Union[str, float, List[Value2TypedDict]]
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)
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r"""Filter value (scalar or array depending on operator). Several dimensions are enriched in responses (returned as human-readable labels), but filters must use the underlying ID: `api_key_id` — numeric ID (from generation metadata) or key hash (64-char hex from GET /api/v1/keys, resolved server-side); `user` — Clerk user ID (e.g. \"user_abc123\"), not the display name; `workspace` — workspace UUID, not the workspace name; `app` — numeric app ID, not the app title; `model` — permaslug (e.g. \"openai/gpt-4o\"), not the display name. Other dimensions (provider, origin, country, etc.) are not enriched and accept the value as returned."""
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Value1 = TypeAliasType("Value1", Union[str, float, List[Value2]])
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r"""Filter value (scalar or array depending on operator). Several dimensions are enriched in responses (returned as human-readable labels), but filters must use the underlying ID: `api_key_id` — numeric ID (from generation metadata) or key hash (64-char hex from GET /api/v1/keys, resolved server-side); `user` — Clerk user ID (e.g. \"user_abc123\"), not the display name; `workspace` — workspace UUID, not the workspace name; `app` — numeric app ID, not the app title; `model` — permaslug (e.g. \"openai/gpt-4o\"), not the display name. Other dimensions (provider, origin, country, etc.) are not enriched and accept the value as returned."""
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class FilterTypedDict(TypedDict):
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field: str
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r"""Dimension to filter on. Use the /meta endpoint for available dimensions."""
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operator: str
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r"""Filter operator"""
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value: Value1TypedDict
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r"""Filter value (scalar or array depending on operator). Several dimensions are enriched in responses (returned as human-readable labels), but filters must use the underlying ID: `api_key_id` — numeric ID (from generation metadata) or key hash (64-char hex from GET /api/v1/keys, resolved server-side); `user` — Clerk user ID (e.g. \"user_abc123\"), not the display name; `workspace` — workspace UUID, not the workspace name; `app` — numeric app ID, not the app title; `model` — permaslug (e.g. \"openai/gpt-4o\"), not the display name. Other dimensions (provider, origin, country, etc.) are not enriched and accept the value as returned."""
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class Filter(BaseModel):
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field: str
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r"""Dimension to filter on. Use the /meta endpoint for available dimensions."""
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operator: str
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r"""Filter operator"""
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value: Value1
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r"""Filter value (scalar or array depending on operator). Several dimensions are enriched in responses (returned as human-readable labels), but filters must use the underlying ID: `api_key_id` — numeric ID (from generation metadata) or key hash (64-char hex from GET /api/v1/keys, resolved server-side); `user` — Clerk user ID (e.g. \"user_abc123\"), not the display name; `workspace` — workspace UUID, not the workspace name; `app` — numeric app ID, not the app title; `model` — permaslug (e.g. \"openai/gpt-4o\"), not the display name. Other dimensions (provider, origin, country, etc.) are not enriched and accept the value as returned."""
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Direction = Union[
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Literal[
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"asc",
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"desc",
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],
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UnrecognizedStr,
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]
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class OrderByTypedDict(TypedDict):
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direction: Direction
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field: str
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r"""Field to order by"""
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class OrderBy(BaseModel):
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direction: Annotated[Direction, PlainValidator(validate_open_enum(False))]
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field: str
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r"""Field to order by"""
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class TimeRangeTypedDict(TypedDict):
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end: datetime
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start: datetime
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class TimeRange(BaseModel):
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end: datetime
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start: datetime
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class QueryAnalyticsRequestBodyTypedDict(TypedDict):
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metrics: List[str]
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dimensions: NotRequired[List[str]]
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filters: NotRequired[List[FilterTypedDict]]
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granularity: NotRequired[str]
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r"""Time granularity"""
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group_limit: NotRequired[int]
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r"""Maximum rows per distinct combination of dimensions. When omitted on time-series queries (granularity + dimensions), auto-computed to avoid truncating time windows. Explicit values override the default and may truncate time buckets if set lower than the number of buckets in the range. Ignored when no dimensions are specified."""
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limit: NotRequired[int]
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r"""Maximum total rows returned. Defaults to 1000. On time-series queries with dimensions and no explicit group_limit, the server may raise this to accommodate the expected number of unique time-bucket/dimension combinations."""
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order_by: NotRequired[OrderByTypedDict]
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time_range: NotRequired[TimeRangeTypedDict]
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class QueryAnalyticsRequestBody(BaseModel):
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metrics: List[str]
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dimensions: Optional[List[str]] = None
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filters: Optional[List[Filter]] = None
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granularity: Optional[str] = None
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r"""Time granularity"""
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group_limit: Optional[int] = None
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r"""Maximum rows per distinct combination of dimensions. When omitted on time-series queries (granularity + dimensions), auto-computed to avoid truncating time windows. Explicit values override the default and may truncate time buckets if set lower than the number of buckets in the range. Ignored when no dimensions are specified."""
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limit: Optional[int] = None
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r"""Maximum total rows returned. Defaults to 1000. On time-series queries with dimensions and no explicit group_limit, the server may raise this to accommodate the expected number of unique time-bucket/dimension combinations."""
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order_by: Optional[OrderBy] = None
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time_range: Optional[TimeRange] = None
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class QueryAnalyticsRequestTypedDict(TypedDict):
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request_body: QueryAnalyticsRequestBodyTypedDict
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http_referer: NotRequired[str]
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r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
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This is used to track API usage per application.
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"""
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x_open_router_title: NotRequired[str]
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r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.
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"""
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x_open_router_categories: NotRequired[str]
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r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.
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"""
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class QueryAnalyticsRequest(BaseModel):
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request_body: Annotated[
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QueryAnalyticsRequestBody,
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FieldMetadata(request=RequestMetadata(media_type="application/json")),
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]
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http_referer: Annotated[
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Optional[str],
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pydantic.Field(alias="HTTP-Referer"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""The app identifier should be your app's URL and is used as the primary identifier for rankings.
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This is used to track API usage per application.
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"""
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x_open_router_title: Annotated[
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Optional[str],
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pydantic.Field(alias="X-OpenRouter-Title"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard.
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"""
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x_open_router_categories: Annotated[
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Optional[str],
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pydantic.Field(alias="X-OpenRouter-Categories"),
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FieldMetadata(header=HeaderMetadata(style="simple", explode=False)),
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] = None
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r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings.
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"""
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class QueryAnalyticsData1TypedDict(TypedDict):
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r"""A row of analytics data with metric/dimension values"""
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class QueryAnalyticsData1(BaseModel):
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r"""A row of analytics data with metric/dimension values"""
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class MetadataTypedDict(TypedDict):
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query_time_ms: float
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row_count: int
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truncated: bool
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class Metadata(BaseModel):
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query_time_ms: float
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row_count: int
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truncated: bool
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class QueryAnalyticsData2TypedDict(TypedDict):
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data: List[QueryAnalyticsData1TypedDict]
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metadata: MetadataTypedDict
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cached_at: NotRequired[float]
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warnings: NotRequired[List[str]]
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r"""Warnings about filter resolution issues (e.g. unresolvable api_key_id hashes). The query still runs normally; these inform the caller that some filter values could not be resolved."""
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class QueryAnalyticsData2(BaseModel):
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data: List[QueryAnalyticsData1]
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metadata: Metadata
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cached_at: Annotated[Optional[float], pydantic.Field(alias="cachedAt")] = None
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warnings: Optional[List[str]] = None
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r"""Warnings about filter resolution issues (e.g. unresolvable api_key_id hashes). The query still runs normally; these inform the caller that some filter values could not be resolved."""
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class QueryAnalyticsResponseTypedDict(TypedDict):
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r"""Analytics query results"""
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data: QueryAnalyticsData2TypedDict
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class QueryAnalyticsResponse(BaseModel):
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r"""Analytics query results"""
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data: QueryAnalyticsData2
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