"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT.""" from __future__ import annotations import io from openrouter.types import BaseModel, UNSET_SENTINEL, UnrecognizedStr from openrouter.utils import ( FieldMetadata, HeaderMetadata, MultipartFormMetadata, RequestMetadata, ) import pydantic from pydantic import model_serializer from typing import IO, List, Literal, Optional, Union from typing_extensions import Annotated, NotRequired, TypedDict class CreateAudioTranscriptionsMultipartGlobalsTypedDict(TypedDict): http_referer: NotRequired[str] r"""The app identifier should be your app's URL and is used as the primary identifier for rankings. This is used to track API usage per application. """ x_open_router_title: NotRequired[str] r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard. """ x_open_router_categories: NotRequired[str] r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings. """ class CreateAudioTranscriptionsMultipartGlobals(BaseModel): http_referer: Annotated[ Optional[str], pydantic.Field(alias="HTTP-Referer"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""The app identifier should be your app's URL and is used as the primary identifier for rankings. This is used to track API usage per application. """ x_open_router_title: Annotated[ Optional[str], pydantic.Field(alias="X-OpenRouter-Title"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard. """ x_open_router_categories: Annotated[ Optional[str], pydantic.Field(alias="X-OpenRouter-Categories"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings. """ @model_serializer(mode="wrap") def serialize_model(self, handler): optional_fields = set( ["HTTP-Referer", "X-OpenRouter-Title", "X-OpenRouter-Categories"] ) 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: if val is not None or k not in optional_fields: m[k] = val return m class CreateAudioTranscriptionsMultipartFileTypedDict(TypedDict): file_name: str content: Union[bytes, IO[bytes], io.IOBase] content_type: NotRequired[str] class CreateAudioTranscriptionsMultipartFile(BaseModel): file_name: Annotated[ str, pydantic.Field(alias="fileName"), FieldMetadata(multipart=True) ] content: Annotated[ Union[bytes, IO[bytes], io.IOBase], pydantic.Field(alias=""), FieldMetadata(multipart=MultipartFormMetadata(content=True)), ] content_type: Annotated[ Optional[str], pydantic.Field(alias="Content-Type"), FieldMetadata(multipart=True), ] = None @model_serializer(mode="wrap") def serialize_model(self, handler): optional_fields = set(["contentType"]) 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: if val is not None or k not in optional_fields: m[k] = val return m ResponseFormat = Union[ Literal[ "json", "verbose_json", ], UnrecognizedStr, ] r"""The response format. \"json\" (default) returns { text, usage }; \"verbose_json\" additionally returns task, language, duration, and segment-level timestamps (OpenAI-compatible providers only).""" TimestampGranularities = Union[ Literal[ "word", "segment", ], UnrecognizedStr, ] class CreateAudioTranscriptionsMultipartRequestBodyTypedDict(TypedDict): file: CreateAudioTranscriptionsMultipartFileTypedDict r"""The audio file to transcribe. The format is derived from the filename extension or the file part content type. Max 25 MB; send larger files as base64 JSON via input_audio.""" model: str r"""The model to use for transcription.""" language: NotRequired[str] r"""The language of the input audio (ISO-639-1).""" response_format: NotRequired[ResponseFormat] r"""The response format. \"json\" (default) returns { text, usage }; \"verbose_json\" additionally returns task, language, duration, and segment-level timestamps (OpenAI-compatible providers only).""" temperature: NotRequired[float] r"""The sampling temperature.""" timestamp_granularities: NotRequired[List[TimestampGranularities]] r"""Timestamp detail levels to include when response_format is \"verbose_json\". \"word\" additionally returns word-level timestamps in the words array.""" class CreateAudioTranscriptionsMultipartRequestBody(BaseModel): file: Annotated[ CreateAudioTranscriptionsMultipartFile, FieldMetadata(multipart=MultipartFormMetadata(file=True)), ] r"""The audio file to transcribe. The format is derived from the filename extension or the file part content type. Max 25 MB; send larger files as base64 JSON via input_audio.""" model: Annotated[str, FieldMetadata(multipart=True)] r"""The model to use for transcription.""" language: Annotated[Optional[str], FieldMetadata(multipart=True)] = None r"""The language of the input audio (ISO-639-1).""" response_format: Annotated[ Optional[ResponseFormat], FieldMetadata(multipart=True) ] = None r"""The response format. \"json\" (default) returns { text, usage }; \"verbose_json\" additionally returns task, language, duration, and segment-level timestamps (OpenAI-compatible providers only).""" temperature: Annotated[Optional[float], FieldMetadata(multipart=True)] = None r"""The sampling temperature.""" timestamp_granularities: Annotated[ Optional[List[TimestampGranularities]], pydantic.Field(alias="timestamp_granularities[]"), FieldMetadata(multipart=True), ] = None r"""Timestamp detail levels to include when response_format is \"verbose_json\". \"word\" additionally returns word-level timestamps in the words array.""" @model_serializer(mode="wrap") def serialize_model(self, handler): optional_fields = set( ["language", "response_format", "temperature", "timestamp_granularities[]"] ) 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: if val is not None or k not in optional_fields: m[k] = val return m class CreateAudioTranscriptionsMultipartRequestTypedDict(TypedDict): request_body: CreateAudioTranscriptionsMultipartRequestBodyTypedDict http_referer: NotRequired[str] r"""The app identifier should be your app's URL and is used as the primary identifier for rankings. This is used to track API usage per application. """ x_open_router_title: NotRequired[str] r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard. """ x_open_router_categories: NotRequired[str] r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings. """ class CreateAudioTranscriptionsMultipartRequest(BaseModel): request_body: Annotated[ CreateAudioTranscriptionsMultipartRequestBody, FieldMetadata(request=RequestMetadata(media_type="multipart/form-data")), ] http_referer: Annotated[ Optional[str], pydantic.Field(alias="HTTP-Referer"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""The app identifier should be your app's URL and is used as the primary identifier for rankings. This is used to track API usage per application. """ x_open_router_title: Annotated[ Optional[str], pydantic.Field(alias="X-OpenRouter-Title"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""The app display name allows you to customize how your app appears in OpenRouter's dashboard. """ x_open_router_categories: Annotated[ Optional[str], pydantic.Field(alias="X-OpenRouter-Categories"), FieldMetadata(header=HeaderMetadata(style="simple", explode=False)), ] = None r"""Comma-separated list of app categories (e.g. \"cli-agent,cloud-agent\"). Used for marketplace rankings. """ @model_serializer(mode="wrap") def serialize_model(self, handler): optional_fields = set( ["HTTP-Referer", "X-OpenRouter-Title", "X-OpenRouter-Categories"] ) 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: if val is not None or k not in optional_fields: m[k] = val return m