"""Code generated by Speakeasy (https://speakeasy.com). DO NOT EDIT.""" from __future__ import annotations from openrouter.types import ( BaseModel, Nullable, OptionalNullable, UNSET, UNSET_SENTINEL, UnrecognizedStr, ) from openrouter.utils import validate_open_enum from pydantic import model_serializer from pydantic.functional_validators import PlainValidator from typing import Literal, Optional, Union from typing_extensions import Annotated, NotRequired, TypedDict OpenResponsesImageGenerationToolType = Literal["image_generation",] Background = Union[ Literal[ "transparent", "opaque", "auto", ], UnrecognizedStr, ] InputFidelity = Union[ Literal[ "high", "low", ], UnrecognizedStr, ] class InputImageMaskTypedDict(TypedDict): image_url: NotRequired[str] file_id: NotRequired[str] class InputImageMask(BaseModel): image_url: Optional[str] = None file_id: Optional[str] = None ModelEnum = Union[ Literal[ "gpt-image-1", "gpt-image-1-mini", ], UnrecognizedStr, ] Moderation = Union[ Literal[ "auto", "low", ], UnrecognizedStr, ] OutputFormat = Union[ Literal[ "png", "webp", "jpeg", ], UnrecognizedStr, ] Quality = Union[ Literal[ "low", "medium", "high", "auto", ], UnrecognizedStr, ] Size = Union[ Literal[ "1024x1024", "1024x1536", "1536x1024", "auto", ], UnrecognizedStr, ] class OpenResponsesImageGenerationToolTypedDict(TypedDict): r"""Image generation tool configuration""" type: OpenResponsesImageGenerationToolType background: NotRequired[Background] input_fidelity: NotRequired[Nullable[InputFidelity]] input_image_mask: NotRequired[InputImageMaskTypedDict] model: NotRequired[ModelEnum] moderation: NotRequired[Moderation] output_compression: NotRequired[float] output_format: NotRequired[OutputFormat] partial_images: NotRequired[float] quality: NotRequired[Quality] size: NotRequired[Size] class OpenResponsesImageGenerationTool(BaseModel): r"""Image generation tool configuration""" type: OpenResponsesImageGenerationToolType background: Annotated[ Optional[Background], PlainValidator(validate_open_enum(False)) ] = None input_fidelity: Annotated[ OptionalNullable[InputFidelity], PlainValidator(validate_open_enum(False)) ] = UNSET input_image_mask: Optional[InputImageMask] = None model: Annotated[Optional[ModelEnum], PlainValidator(validate_open_enum(False))] = ( None ) moderation: Annotated[ Optional[Moderation], PlainValidator(validate_open_enum(False)) ] = None output_compression: Optional[float] = None output_format: Annotated[ Optional[OutputFormat], PlainValidator(validate_open_enum(False)) ] = None partial_images: Optional[float] = None quality: Annotated[Optional[Quality], PlainValidator(validate_open_enum(False))] = ( None ) size: Annotated[Optional[Size], PlainValidator(validate_open_enum(False))] = None @model_serializer(mode="wrap") def serialize_model(self, handler): optional_fields = [ "background", "input_fidelity", "input_image_mask", "model", "moderation", "output_compression", "output_format", "partial_images", "quality", "size", ] nullable_fields = ["input_fidelity"] 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