mirror of
https://github.com/wassname/openrouter-python-sdk-retry-errors.git
synced 2026-07-29 11:23:49 +08:00
420 lines
13 KiB
Python
420 lines
13 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.components import (
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datacollection as components_datacollection,
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providername as components_providername,
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providersort as components_providersort,
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quantization as components_quantization,
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)
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from openrouter.types import (
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BaseModel,
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Nullable,
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OptionalNullable,
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UNSET,
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UNSET_SENTINEL,
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UnrecognizedStr,
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)
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from openrouter.utils import get_discriminator, validate_open_enum
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from pydantic import Discriminator, Tag, model_serializer
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from pydantic.functional_validators import PlainValidator
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from typing import Any, List, Literal, Optional, Union
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from typing_extensions import Annotated, NotRequired, TypeAliasType, TypedDict
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TypeImageURL = Literal["image_url",]
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class ImageURLTypedDict(TypedDict):
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url: str
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class ImageURL(BaseModel):
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url: str
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class ContentImageURLTypedDict(TypedDict):
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type: TypeImageURL
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image_url: ImageURLTypedDict
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class ContentImageURL(BaseModel):
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type: TypeImageURL
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image_url: ImageURL
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TypeText = Literal["text",]
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class ContentTextTypedDict(TypedDict):
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type: TypeText
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text: str
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class ContentText(BaseModel):
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type: TypeText
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text: str
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ContentTypedDict = TypeAliasType(
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"ContentTypedDict", Union[ContentTextTypedDict, ContentImageURLTypedDict]
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)
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Content = Annotated[
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Union[
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Annotated[ContentText, Tag("text")],
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Annotated[ContentImageURL, Tag("image_url")],
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],
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Discriminator(lambda m: get_discriminator(m, "type", "type")),
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]
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class InputTypedDict(TypedDict):
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content: List[ContentTypedDict]
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class Input(BaseModel):
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content: List[Content]
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InputUnionTypedDict = TypeAliasType(
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"InputUnionTypedDict",
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Union[str, List[str], List[float], List[List[float]], List[InputTypedDict]],
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)
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InputUnion = TypeAliasType(
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"InputUnion", Union[str, List[str], List[float], List[List[float]], List[Input]]
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)
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EncodingFormat = Union[
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Literal[
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"float",
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"base64",
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],
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UnrecognizedStr,
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]
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OrderTypedDict = TypeAliasType(
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"OrderTypedDict", Union[components_providername.ProviderName, str]
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)
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Order = TypeAliasType(
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"Order",
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Union[
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Annotated[
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components_providername.ProviderName,
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PlainValidator(validate_open_enum(False)),
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],
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str,
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],
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)
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OnlyTypedDict = TypeAliasType(
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"OnlyTypedDict", Union[components_providername.ProviderName, str]
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)
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Only = TypeAliasType(
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"Only",
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Union[
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Annotated[
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components_providername.ProviderName,
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PlainValidator(validate_open_enum(False)),
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],
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str,
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],
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)
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IgnoreTypedDict = TypeAliasType(
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"IgnoreTypedDict", Union[components_providername.ProviderName, str]
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)
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Ignore = TypeAliasType(
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"Ignore",
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Union[
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Annotated[
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components_providername.ProviderName,
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PlainValidator(validate_open_enum(False)),
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],
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str,
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],
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)
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class MaxPriceTypedDict(TypedDict):
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r"""The object specifying the maximum price you want to pay for this request. USD price per million tokens, for prompt and completion."""
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prompt: NotRequired[Any]
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r"""A value in string or number format that is a large number"""
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completion: NotRequired[Any]
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r"""A value in string or number format that is a large number"""
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image: NotRequired[Any]
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r"""A value in string or number format that is a large number"""
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audio: NotRequired[Any]
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r"""A value in string or number format that is a large number"""
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request: NotRequired[Any]
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r"""A value in string or number format that is a large number"""
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class MaxPrice(BaseModel):
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r"""The object specifying the maximum price you want to pay for this request. USD price per million tokens, for prompt and completion."""
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prompt: Optional[Any] = None
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r"""A value in string or number format that is a large number"""
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completion: Optional[Any] = None
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r"""A value in string or number format that is a large number"""
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image: Optional[Any] = None
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r"""A value in string or number format that is a large number"""
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audio: Optional[Any] = None
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r"""A value in string or number format that is a large number"""
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request: Optional[Any] = None
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r"""A value in string or number format that is a large number"""
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class CreateEmbeddingsProviderTypedDict(TypedDict):
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allow_fallbacks: NotRequired[Nullable[bool]]
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r"""Whether to allow backup providers to serve requests
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- true: (default) when the primary provider (or your custom providers in \"order\") is unavailable, use the next best provider.
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- false: use only the primary/custom provider, and return the upstream error if it's unavailable.
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"""
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require_parameters: NotRequired[Nullable[bool]]
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r"""Whether to filter providers to only those that support the parameters you've provided. If this setting is omitted or set to false, then providers will receive only the parameters they support, and ignore the rest."""
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data_collection: NotRequired[Nullable[components_datacollection.DataCollection]]
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r"""Data collection setting. If no available model provider meets the requirement, your request will return an error.
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- allow: (default) allow providers which store user data non-transiently and may train on it
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- deny: use only providers which do not collect user data.
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"""
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zdr: NotRequired[Nullable[bool]]
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r"""Whether to restrict routing to only ZDR (Zero Data Retention) endpoints. When true, only endpoints that do not retain prompts will be used."""
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enforce_distillable_text: NotRequired[Nullable[bool]]
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r"""Whether to restrict routing to only models that allow text distillation. When true, only models where the author has allowed distillation will be used."""
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order: NotRequired[Nullable[List[OrderTypedDict]]]
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r"""An ordered list of provider slugs. The router will attempt to use the first provider in the subset of this list that supports your requested model, and fall back to the next if it is unavailable. If no providers are available, the request will fail with an error message."""
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only: NotRequired[Nullable[List[OnlyTypedDict]]]
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r"""List of provider slugs to allow. If provided, this list is merged with your account-wide allowed provider settings for this request."""
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ignore: NotRequired[Nullable[List[IgnoreTypedDict]]]
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r"""List of provider slugs to ignore. If provided, this list is merged with your account-wide ignored provider settings for this request."""
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quantizations: NotRequired[Nullable[List[components_quantization.Quantization]]]
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r"""A list of quantization levels to filter the provider by."""
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sort: NotRequired[Nullable[components_providersort.ProviderSort]]
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r"""The sorting strategy to use for this request, if \"order\" is not specified. When set, no load balancing is performed."""
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max_price: NotRequired[MaxPriceTypedDict]
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r"""The object specifying the maximum price you want to pay for this request. USD price per million tokens, for prompt and completion."""
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class CreateEmbeddingsProvider(BaseModel):
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allow_fallbacks: OptionalNullable[bool] = UNSET
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r"""Whether to allow backup providers to serve requests
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- true: (default) when the primary provider (or your custom providers in \"order\") is unavailable, use the next best provider.
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- false: use only the primary/custom provider, and return the upstream error if it's unavailable.
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"""
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require_parameters: OptionalNullable[bool] = UNSET
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r"""Whether to filter providers to only those that support the parameters you've provided. If this setting is omitted or set to false, then providers will receive only the parameters they support, and ignore the rest."""
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data_collection: Annotated[
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OptionalNullable[components_datacollection.DataCollection],
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PlainValidator(validate_open_enum(False)),
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] = UNSET
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r"""Data collection setting. If no available model provider meets the requirement, your request will return an error.
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- allow: (default) allow providers which store user data non-transiently and may train on it
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- deny: use only providers which do not collect user data.
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"""
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zdr: OptionalNullable[bool] = UNSET
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r"""Whether to restrict routing to only ZDR (Zero Data Retention) endpoints. When true, only endpoints that do not retain prompts will be used."""
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enforce_distillable_text: OptionalNullable[bool] = UNSET
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r"""Whether to restrict routing to only models that allow text distillation. When true, only models where the author has allowed distillation will be used."""
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order: OptionalNullable[List[Order]] = UNSET
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r"""An ordered list of provider slugs. The router will attempt to use the first provider in the subset of this list that supports your requested model, and fall back to the next if it is unavailable. If no providers are available, the request will fail with an error message."""
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only: OptionalNullable[List[Only]] = UNSET
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r"""List of provider slugs to allow. If provided, this list is merged with your account-wide allowed provider settings for this request."""
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ignore: OptionalNullable[List[Ignore]] = UNSET
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r"""List of provider slugs to ignore. If provided, this list is merged with your account-wide ignored provider settings for this request."""
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quantizations: OptionalNullable[
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List[
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Annotated[
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components_quantization.Quantization,
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PlainValidator(validate_open_enum(False)),
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]
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]
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] = UNSET
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r"""A list of quantization levels to filter the provider by."""
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sort: Annotated[
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OptionalNullable[components_providersort.ProviderSort],
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PlainValidator(validate_open_enum(False)),
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] = UNSET
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r"""The sorting strategy to use for this request, if \"order\" is not specified. When set, no load balancing is performed."""
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max_price: Optional[MaxPrice] = None
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r"""The object specifying the maximum price you want to pay for this request. USD price per million tokens, for prompt and completion."""
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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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"allow_fallbacks",
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"require_parameters",
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"data_collection",
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"zdr",
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"enforce_distillable_text",
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"order",
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"only",
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"ignore",
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"quantizations",
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"sort",
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"max_price",
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]
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nullable_fields = [
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"allow_fallbacks",
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"require_parameters",
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"data_collection",
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"zdr",
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"enforce_distillable_text",
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"order",
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"only",
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"ignore",
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"quantizations",
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"sort",
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]
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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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class CreateEmbeddingsRequestTypedDict(TypedDict):
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input: InputUnionTypedDict
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model: str
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encoding_format: NotRequired[EncodingFormat]
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dimensions: NotRequired[int]
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user: NotRequired[str]
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provider: NotRequired[CreateEmbeddingsProviderTypedDict]
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input_type: NotRequired[str]
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class CreateEmbeddingsRequest(BaseModel):
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input: InputUnion
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model: str
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encoding_format: Annotated[
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Optional[EncodingFormat], PlainValidator(validate_open_enum(False))
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] = None
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dimensions: Optional[int] = None
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user: Optional[str] = None
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provider: Optional[CreateEmbeddingsProvider] = None
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input_type: Optional[str] = None
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Object = Literal["list",]
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ObjectEmbedding = Literal["embedding",]
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EmbeddingTypedDict = TypeAliasType("EmbeddingTypedDict", Union[List[float], str])
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Embedding = TypeAliasType("Embedding", Union[List[float], str])
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class CreateEmbeddingsDataTypedDict(TypedDict):
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object: ObjectEmbedding
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embedding: EmbeddingTypedDict
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index: NotRequired[float]
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class CreateEmbeddingsData(BaseModel):
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object: ObjectEmbedding
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embedding: Embedding
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index: Optional[float] = None
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class UsageTypedDict(TypedDict):
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prompt_tokens: float
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total_tokens: float
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cost: NotRequired[float]
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class Usage(BaseModel):
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prompt_tokens: float
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total_tokens: float
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cost: Optional[float] = None
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class CreateEmbeddingsResponseTypedDict(TypedDict):
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r"""Embedding response"""
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object: Object
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data: List[CreateEmbeddingsDataTypedDict]
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model: str
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id: NotRequired[str]
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usage: NotRequired[UsageTypedDict]
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class CreateEmbeddingsResponse(BaseModel):
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r"""Embedding response"""
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object: Object
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data: List[CreateEmbeddingsData]
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model: str
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id: Optional[str] = None
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usage: Optional[Usage] = None
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