// File generated from our OpenAPI spec by Stainless.

package com.openai.models.images

import com.fasterxml.jackson.annotation.JsonAnyGetter
import com.fasterxml.jackson.annotation.JsonAnySetter
import com.fasterxml.jackson.annotation.JsonCreator
import com.fasterxml.jackson.annotation.JsonProperty
import com.fasterxml.jackson.core.JsonGenerator
import com.fasterxml.jackson.databind.SerializerProvider
import com.fasterxml.jackson.databind.annotation.JsonSerialize
import com.openai.core.BaseSerializer
import com.openai.core.Enum
import com.openai.core.ExcludeMissing
import com.openai.core.JsonField
import com.openai.core.JsonValue
import com.openai.core.MultipartField
import com.openai.core.Params
import com.openai.core.checkRequired
import com.openai.core.getOrThrow
import com.openai.core.http.Headers
import com.openai.core.http.QueryParams
import com.openai.core.toImmutable
import com.openai.errors.OpenAIInvalidDataException
import java.io.InputStream
import java.nio.file.Path
import java.util.Collections
import java.util.Objects
import java.util.Optional
import kotlin.io.path.inputStream
import kotlin.io.path.name
import kotlin.jvm.optionals.getOrNull

/**
 * Creates an edited or extended image given one or more source images and a prompt. This endpoint
 * supports GPT Image models (`gpt-image-1.5`, `gpt-image-1`, `gpt-image-1-mini`, and
 * `chatgpt-image-latest`) and `dall-e-2`.
 */
class ImageEditParams
private constructor(
    private val body: Body,
    private val additionalHeaders: Headers,
    private val additionalQueryParams: QueryParams,
) : Params {

    /**
     * The image(s) to edit. Must be a supported image file or an array of images.
     *
     * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`,
     * `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should be a `png`, `webp`,
     * or `jpg` file less than 50MB. You can provide up to 16 images.
     *
     * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
     * than 4MB.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
     *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
     */
    fun image(): Image = body.image()

    /**
     * A text description of the desired image(s). The maximum length is 1000 characters for
     * `dall-e-2`, and 32000 characters for the GPT image models.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
     *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
     */
    fun prompt(): String = body.prompt()

    /**
     * Allows to set transparency for the background of the generated image(s). This parameter is
     * only supported for GPT image models that support transparent backgrounds. Must be one of
     * `transparent`, `opaque`, or `auto` (default value). When `auto` is used, the model will
     * automatically determine the best background for the image.
     *
     * `gpt-image-2` and `gpt-image-2-2026-04-21` do not support transparent backgrounds. Requests
     * with `background` set to `transparent` will return an error for these models; use `opaque` or
     * `auto` instead.
     *
     * If `transparent`, the output format needs to support transparency, so it should be set to
     * either `png` (default value) or `webp`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun background(): Optional<Background> = body.background()

    /**
     * Control how much effort the model will exert to match the style and features, especially
     * facial features, of input images. This parameter is only supported for `gpt-image-1` and
     * `gpt-image-1.5` and later models, unsupported for `gpt-image-1-mini`. Supports `high` and
     * `low`. Defaults to `low`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun inputFidelity(): Optional<InputFidelity> = body.inputFidelity()

    /**
     * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate where
     * `image` should be edited. If there are multiple images provided, the mask will be applied on
     * the first image. Must be a valid PNG file, less than 4MB, and have the same dimensions as
     * `image`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun mask(): Optional<InputStream> = body.mask()

    /**
     * The model to use for image generation. One of `dall-e-2` or a GPT image model (`gpt-image-1`,
     * `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`, `gpt-image-2-2026-04-21`, or
     * `chatgpt-image-latest`). Defaults to `gpt-image-1.5`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun model(): Optional<ImageModel> = body.model()

    /**
     * The number of images to generate. Must be between 1 and 10.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun n(): Optional<Long> = body.n()

    /**
     * The compression level (0-100%) for the generated images. This parameter is only supported for
     * the GPT image models with the `webp` or `jpeg` output formats, and defaults to 100.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun outputCompression(): Optional<Long> = body.outputCompression()

    /**
     * The format in which the generated images are returned. This parameter is only supported for
     * the GPT image models. Must be one of `png`, `jpeg`, or `webp`. The default value is `png`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun outputFormat(): Optional<OutputFormat> = body.outputFormat()

    /**
     * The number of partial images to generate. This parameter is used for streaming responses that
     * return partial images. Value must be between 0 and 3. When set to 0, the response will be a
     * single image sent in one streaming event.
     *
     * Note that the final image may be sent before the full number of partial images are generated
     * if the full image is generated more quickly.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun partialImages(): Optional<Long> = body.partialImages()

    /**
     * The quality of the image that will be generated for GPT image models. Defaults to `auto`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun quality(): Optional<Quality> = body.quality()

    /**
     * The format in which the generated images are returned. Must be one of `url` or `b64_json`.
     * URLs are only valid for 60 minutes after the image has been generated. This parameter is only
     * supported for `dall-e-2` (default is `url` for `dall-e-2`), as GPT image models always return
     * base64-encoded images.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun responseFormat(): Optional<ResponseFormat> = body.responseFormat()

    /**
     * The size of the generated images. For `gpt-image-2` and `gpt-image-2-2026-04-21`, arbitrary
     * resolutions are supported as `WIDTHxHEIGHT` strings, for example `1536x864`. Width and height
     * must both be divisible by 16 and the requested aspect ratio must be between 1:3 and 3:1.
     * Resolutions above `2560x1440` are experimental, and the maximum supported resolution is
     * `3840x2160`. The requested size must also satisfy the model's current pixel and edge limits.
     * The standard sizes `1024x1024`, `1536x1024`, and `1024x1536` are supported by the GPT image
     * models; `auto` is supported for models that allow automatic sizing. For `dall-e-2`, use one
     * of `256x256`, `512x512`, or `1024x1024`. For `dall-e-3`, use one of `1024x1024`, `1792x1024`,
     * or `1024x1792`.
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun size(): Optional<String> = body.size()

    /**
     * A unique identifier representing your end-user, which can help OpenAI to monitor and detect
     * abuse.
     * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
     *
     * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
     *   server responded with an unexpected value).
     */
    fun user(): Optional<String> = body.user()

    /**
     * Returns the raw multipart value of [image].
     *
     * Unlike [image], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _image(): MultipartField<Image> = body._image()

    /**
     * Returns the raw multipart value of [prompt].
     *
     * Unlike [prompt], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _prompt(): MultipartField<String> = body._prompt()

    /**
     * Returns the raw multipart value of [background].
     *
     * Unlike [background], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _background(): MultipartField<Background> = body._background()

    /**
     * Returns the raw multipart value of [inputFidelity].
     *
     * Unlike [inputFidelity], this method doesn't throw if the multipart field has an unexpected
     * type.
     */
    fun _inputFidelity(): MultipartField<InputFidelity> = body._inputFidelity()

    /**
     * Returns the raw multipart value of [mask].
     *
     * Unlike [mask], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _mask(): MultipartField<InputStream> = body._mask()

    /**
     * Returns the raw multipart value of [model].
     *
     * Unlike [model], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _model(): MultipartField<ImageModel> = body._model()

    /**
     * Returns the raw multipart value of [n].
     *
     * Unlike [n], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _n(): MultipartField<Long> = body._n()

    /**
     * Returns the raw multipart value of [outputCompression].
     *
     * Unlike [outputCompression], this method doesn't throw if the multipart field has an
     * unexpected type.
     */
    fun _outputCompression(): MultipartField<Long> = body._outputCompression()

    /**
     * Returns the raw multipart value of [outputFormat].
     *
     * Unlike [outputFormat], this method doesn't throw if the multipart field has an unexpected
     * type.
     */
    fun _outputFormat(): MultipartField<OutputFormat> = body._outputFormat()

    /**
     * Returns the raw multipart value of [partialImages].
     *
     * Unlike [partialImages], this method doesn't throw if the multipart field has an unexpected
     * type.
     */
    fun _partialImages(): MultipartField<Long> = body._partialImages()

    /**
     * Returns the raw multipart value of [quality].
     *
     * Unlike [quality], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _quality(): MultipartField<Quality> = body._quality()

    /**
     * Returns the raw multipart value of [responseFormat].
     *
     * Unlike [responseFormat], this method doesn't throw if the multipart field has an unexpected
     * type.
     */
    fun _responseFormat(): MultipartField<ResponseFormat> = body._responseFormat()

    /**
     * Returns the raw multipart value of [size].
     *
     * Unlike [size], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _size(): MultipartField<String> = body._size()

    /**
     * Returns the raw multipart value of [user].
     *
     * Unlike [user], this method doesn't throw if the multipart field has an unexpected type.
     */
    fun _user(): MultipartField<String> = body._user()

    fun _additionalBodyProperties(): Map<String, JsonValue> = body._additionalProperties()

    /** Additional headers to send with the request. */
    fun _additionalHeaders(): Headers = additionalHeaders

    /** Additional query param to send with the request. */
    fun _additionalQueryParams(): QueryParams = additionalQueryParams

    fun toBuilder() = Builder().from(this)

    companion object {

        /**
         * Returns a mutable builder for constructing an instance of [ImageEditParams].
         *
         * The following fields are required:
         * ```java
         * .image()
         * .prompt()
         * ```
         */
        @JvmStatic fun builder() = Builder()
    }

    /** A builder for [ImageEditParams]. */
    class Builder internal constructor() {

        private var body: Body.Builder = Body.builder()
        private var additionalHeaders: Headers.Builder = Headers.builder()
        private var additionalQueryParams: QueryParams.Builder = QueryParams.builder()

        @JvmSynthetic
        internal fun from(imageEditParams: ImageEditParams) = apply {
            body = imageEditParams.body.toBuilder()
            additionalHeaders = imageEditParams.additionalHeaders.toBuilder()
            additionalQueryParams = imageEditParams.additionalQueryParams.toBuilder()
        }

        /**
         * Sets the entire request body.
         *
         * This is generally only useful if you are already constructing the body separately.
         * Otherwise, it's more convenient to use the top-level setters instead:
         * - [image]
         * - [prompt]
         * - [background]
         * - [inputFidelity]
         * - [mask]
         * - etc.
         */
        fun body(body: Body) = apply { this.body = body.toBuilder() }

        /**
         * The image(s) to edit. Must be a supported image file or an array of images.
         *
         * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
         * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should
         * be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16 images.
         *
         * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
         * than 4MB.
         */
        fun image(image: Image) = apply { body.image(image) }

        /**
         * Sets [Builder.image] to an arbitrary multipart value.
         *
         * You should usually call [Builder.image] with a well-typed [Image] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun image(image: MultipartField<Image>) = apply { body.image(image) }

        /** Alias for calling [image] with `Image.ofInputStream(inputStream)`. */
        fun image(inputStream: InputStream) = apply { body.image(inputStream) }

        /**
         * The image(s) to edit. Must be a supported image file or an array of images.
         *
         * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
         * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should
         * be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16 images.
         *
         * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
         * than 4MB.
         */
        fun image(inputStream: ByteArray) = apply { body.image(inputStream) }

        /**
         * The image(s) to edit. Must be a supported image file or an array of images.
         *
         * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
         * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should
         * be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16 images.
         *
         * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
         * than 4MB.
         */
        fun image(path: Path) = apply { body.image(path) }

        /** Alias for calling [image] with `Image.ofInputStreams(inputStreams)`. */
        fun imageOfInputStreams(inputStreams: List<InputStream>) = apply {
            body.imageOfInputStreams(inputStreams)
        }

        /**
         * A text description of the desired image(s). The maximum length is 1000 characters for
         * `dall-e-2`, and 32000 characters for the GPT image models.
         */
        fun prompt(prompt: String) = apply { body.prompt(prompt) }

        /**
         * Sets [Builder.prompt] to an arbitrary multipart value.
         *
         * You should usually call [Builder.prompt] with a well-typed [String] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun prompt(prompt: MultipartField<String>) = apply { body.prompt(prompt) }

        /**
         * Allows to set transparency for the background of the generated image(s). This parameter
         * is only supported for GPT image models that support transparent backgrounds. Must be one
         * of `transparent`, `opaque`, or `auto` (default value). When `auto` is used, the model
         * will automatically determine the best background for the image.
         *
         * `gpt-image-2` and `gpt-image-2-2026-04-21` do not support transparent backgrounds.
         * Requests with `background` set to `transparent` will return an error for these models;
         * use `opaque` or `auto` instead.
         *
         * If `transparent`, the output format needs to support transparency, so it should be set to
         * either `png` (default value) or `webp`.
         */
        fun background(background: Background?) = apply { body.background(background) }

        /** Alias for calling [Builder.background] with `background.orElse(null)`. */
        fun background(background: Optional<Background>) = background(background.getOrNull())

        /**
         * Sets [Builder.background] to an arbitrary multipart value.
         *
         * You should usually call [Builder.background] with a well-typed [Background] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun background(background: MultipartField<Background>) = apply {
            body.background(background)
        }

        /**
         * Control how much effort the model will exert to match the style and features, especially
         * facial features, of input images. This parameter is only supported for `gpt-image-1` and
         * `gpt-image-1.5` and later models, unsupported for `gpt-image-1-mini`. Supports `high` and
         * `low`. Defaults to `low`.
         */
        fun inputFidelity(inputFidelity: InputFidelity?) = apply {
            body.inputFidelity(inputFidelity)
        }

        /** Alias for calling [Builder.inputFidelity] with `inputFidelity.orElse(null)`. */
        fun inputFidelity(inputFidelity: Optional<InputFidelity>) =
            inputFidelity(inputFidelity.getOrNull())

        /**
         * Sets [Builder.inputFidelity] to an arbitrary multipart value.
         *
         * You should usually call [Builder.inputFidelity] with a well-typed [InputFidelity] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun inputFidelity(inputFidelity: MultipartField<InputFidelity>) = apply {
            body.inputFidelity(inputFidelity)
        }

        /**
         * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
         * where `image` should be edited. If there are multiple images provided, the mask will be
         * applied on the first image. Must be a valid PNG file, less than 4MB, and have the same
         * dimensions as `image`.
         */
        fun mask(mask: InputStream) = apply { body.mask(mask) }

        /**
         * Sets [Builder.mask] to an arbitrary multipart value.
         *
         * You should usually call [Builder.mask] with a well-typed [InputStream] value instead.
         * This method is primarily for setting the field to an undocumented or not yet supported
         * value.
         */
        fun mask(mask: MultipartField<InputStream>) = apply { body.mask(mask) }

        /**
         * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
         * where `image` should be edited. If there are multiple images provided, the mask will be
         * applied on the first image. Must be a valid PNG file, less than 4MB, and have the same
         * dimensions as `image`.
         */
        fun mask(mask: ByteArray) = apply { body.mask(mask) }

        /**
         * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
         * where `image` should be edited. If there are multiple images provided, the mask will be
         * applied on the first image. Must be a valid PNG file, less than 4MB, and have the same
         * dimensions as `image`.
         */
        fun mask(path: Path) = apply { body.mask(path) }

        /**
         * The model to use for image generation. One of `dall-e-2` or a GPT image model
         * (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`,
         * `gpt-image-2-2026-04-21`, or `chatgpt-image-latest`). Defaults to `gpt-image-1.5`.
         */
        fun model(model: ImageModel?) = apply { body.model(model) }

        /** Alias for calling [Builder.model] with `model.orElse(null)`. */
        fun model(model: Optional<ImageModel>) = model(model.getOrNull())

        /**
         * Sets [Builder.model] to an arbitrary multipart value.
         *
         * You should usually call [Builder.model] with a well-typed [ImageModel] value instead.
         * This method is primarily for setting the field to an undocumented or not yet supported
         * value.
         */
        fun model(model: MultipartField<ImageModel>) = apply { body.model(model) }

        /**
         * Sets [model] to an arbitrary [String].
         *
         * You should usually call [model] with a well-typed [ImageModel] constant instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun model(value: String) = apply { body.model(value) }

        /** The number of images to generate. Must be between 1 and 10. */
        fun n(n: Long?) = apply { body.n(n) }

        /**
         * Alias for [Builder.n].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun n(n: Long) = n(n as Long?)

        /** Alias for calling [Builder.n] with `n.orElse(null)`. */
        fun n(n: Optional<Long>) = n(n.getOrNull())

        /**
         * Sets [Builder.n] to an arbitrary multipart value.
         *
         * You should usually call [Builder.n] with a well-typed [Long] value instead. This method
         * is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun n(n: MultipartField<Long>) = apply { body.n(n) }

        /**
         * The compression level (0-100%) for the generated images. This parameter is only supported
         * for the GPT image models with the `webp` or `jpeg` output formats, and defaults to 100.
         */
        fun outputCompression(outputCompression: Long?) = apply {
            body.outputCompression(outputCompression)
        }

        /**
         * Alias for [Builder.outputCompression].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun outputCompression(outputCompression: Long) =
            outputCompression(outputCompression as Long?)

        /** Alias for calling [Builder.outputCompression] with `outputCompression.orElse(null)`. */
        fun outputCompression(outputCompression: Optional<Long>) =
            outputCompression(outputCompression.getOrNull())

        /**
         * Sets [Builder.outputCompression] to an arbitrary multipart value.
         *
         * You should usually call [Builder.outputCompression] with a well-typed [Long] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun outputCompression(outputCompression: MultipartField<Long>) = apply {
            body.outputCompression(outputCompression)
        }

        /**
         * The format in which the generated images are returned. This parameter is only supported
         * for the GPT image models. Must be one of `png`, `jpeg`, or `webp`. The default value is
         * `png`.
         */
        fun outputFormat(outputFormat: OutputFormat?) = apply { body.outputFormat(outputFormat) }

        /** Alias for calling [Builder.outputFormat] with `outputFormat.orElse(null)`. */
        fun outputFormat(outputFormat: Optional<OutputFormat>) =
            outputFormat(outputFormat.getOrNull())

        /**
         * Sets [Builder.outputFormat] to an arbitrary multipart value.
         *
         * You should usually call [Builder.outputFormat] with a well-typed [OutputFormat] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun outputFormat(outputFormat: MultipartField<OutputFormat>) = apply {
            body.outputFormat(outputFormat)
        }

        /**
         * The number of partial images to generate. This parameter is used for streaming responses
         * that return partial images. Value must be between 0 and 3. When set to 0, the response
         * will be a single image sent in one streaming event.
         *
         * Note that the final image may be sent before the full number of partial images are
         * generated if the full image is generated more quickly.
         */
        fun partialImages(partialImages: Long?) = apply { body.partialImages(partialImages) }

        /**
         * Alias for [Builder.partialImages].
         *
         * This unboxed primitive overload exists for backwards compatibility.
         */
        fun partialImages(partialImages: Long) = partialImages(partialImages as Long?)

        /** Alias for calling [Builder.partialImages] with `partialImages.orElse(null)`. */
        fun partialImages(partialImages: Optional<Long>) = partialImages(partialImages.getOrNull())

        /**
         * Sets [Builder.partialImages] to an arbitrary multipart value.
         *
         * You should usually call [Builder.partialImages] with a well-typed [Long] value instead.
         * This method is primarily for setting the field to an undocumented or not yet supported
         * value.
         */
        fun partialImages(partialImages: MultipartField<Long>) = apply {
            body.partialImages(partialImages)
        }

        /**
         * The quality of the image that will be generated for GPT image models. Defaults to `auto`.
         */
        fun quality(quality: Quality?) = apply { body.quality(quality) }

        /** Alias for calling [Builder.quality] with `quality.orElse(null)`. */
        fun quality(quality: Optional<Quality>) = quality(quality.getOrNull())

        /**
         * Sets [Builder.quality] to an arbitrary multipart value.
         *
         * You should usually call [Builder.quality] with a well-typed [Quality] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun quality(quality: MultipartField<Quality>) = apply { body.quality(quality) }

        /**
         * The format in which the generated images are returned. Must be one of `url` or
         * `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This
         * parameter is only supported for `dall-e-2` (default is `url` for `dall-e-2`), as GPT
         * image models always return base64-encoded images.
         */
        fun responseFormat(responseFormat: ResponseFormat?) = apply {
            body.responseFormat(responseFormat)
        }

        /** Alias for calling [Builder.responseFormat] with `responseFormat.orElse(null)`. */
        fun responseFormat(responseFormat: Optional<ResponseFormat>) =
            responseFormat(responseFormat.getOrNull())

        /**
         * Sets [Builder.responseFormat] to an arbitrary multipart value.
         *
         * You should usually call [Builder.responseFormat] with a well-typed [ResponseFormat] value
         * instead. This method is primarily for setting the field to an undocumented or not yet
         * supported value.
         */
        fun responseFormat(responseFormat: MultipartField<ResponseFormat>) = apply {
            body.responseFormat(responseFormat)
        }

        /**
         * The size of the generated images. For `gpt-image-2` and `gpt-image-2-2026-04-21`,
         * arbitrary resolutions are supported as `WIDTHxHEIGHT` strings, for example `1536x864`.
         * Width and height must both be divisible by 16 and the requested aspect ratio must be
         * between 1:3 and 3:1. Resolutions above `2560x1440` are experimental, and the maximum
         * supported resolution is `3840x2160`. The requested size must also satisfy the model's
         * current pixel and edge limits. The standard sizes `1024x1024`, `1536x1024`, and
         * `1024x1536` are supported by the GPT image models; `auto` is supported for models that
         * allow automatic sizing. For `dall-e-2`, use one of `256x256`, `512x512`, or `1024x1024`.
         * For `dall-e-3`, use one of `1024x1024`, `1792x1024`, or `1024x1792`.
         */
        fun size(size: String?) = apply { body.size(size) }

        /** Alias for calling [Builder.size] with `size.orElse(null)`. */
        fun size(size: Optional<String>) = size(size.getOrNull())

        /**
         * Sets [Builder.size] to an arbitrary multipart value.
         *
         * You should usually call [Builder.size] with a well-typed [String] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun size(size: MultipartField<String>) = apply { body.size(size) }

        /**
         * A unique identifier representing your end-user, which can help OpenAI to monitor and
         * detect abuse.
         * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
         */
        fun user(user: String) = apply { body.user(user) }

        /**
         * Sets [Builder.user] to an arbitrary multipart value.
         *
         * You should usually call [Builder.user] with a well-typed [String] value instead. This
         * method is primarily for setting the field to an undocumented or not yet supported value.
         */
        fun user(user: MultipartField<String>) = apply { body.user(user) }

        fun additionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) = apply {
            body.additionalProperties(additionalBodyProperties)
        }

        fun putAdditionalBodyProperty(key: String, value: JsonValue) = apply {
            body.putAdditionalProperty(key, value)
        }

        fun putAllAdditionalBodyProperties(additionalBodyProperties: Map<String, JsonValue>) =
            apply {
                body.putAllAdditionalProperties(additionalBodyProperties)
            }

        fun removeAdditionalBodyProperty(key: String) = apply { body.removeAdditionalProperty(key) }

        fun removeAllAdditionalBodyProperties(keys: Set<String>) = apply {
            body.removeAllAdditionalProperties(keys)
        }

        fun additionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.clear()
            putAllAdditionalHeaders(additionalHeaders)
        }

        fun additionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.clear()
            putAllAdditionalHeaders(additionalHeaders)
        }

        fun putAdditionalHeader(name: String, value: String) = apply {
            additionalHeaders.put(name, value)
        }

        fun putAdditionalHeaders(name: String, values: Iterable<String>) = apply {
            additionalHeaders.put(name, values)
        }

        fun putAllAdditionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.putAll(additionalHeaders)
        }

        fun putAllAdditionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.putAll(additionalHeaders)
        }

        fun replaceAdditionalHeaders(name: String, value: String) = apply {
            additionalHeaders.replace(name, value)
        }

        fun replaceAdditionalHeaders(name: String, values: Iterable<String>) = apply {
            additionalHeaders.replace(name, values)
        }

        fun replaceAllAdditionalHeaders(additionalHeaders: Headers) = apply {
            this.additionalHeaders.replaceAll(additionalHeaders)
        }

        fun replaceAllAdditionalHeaders(additionalHeaders: Map<String, Iterable<String>>) = apply {
            this.additionalHeaders.replaceAll(additionalHeaders)
        }

        fun removeAdditionalHeaders(name: String) = apply { additionalHeaders.remove(name) }

        fun removeAllAdditionalHeaders(names: Set<String>) = apply {
            additionalHeaders.removeAll(names)
        }

        fun additionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.clear()
            putAllAdditionalQueryParams(additionalQueryParams)
        }

        fun additionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) = apply {
            this.additionalQueryParams.clear()
            putAllAdditionalQueryParams(additionalQueryParams)
        }

        fun putAdditionalQueryParam(key: String, value: String) = apply {
            additionalQueryParams.put(key, value)
        }

        fun putAdditionalQueryParams(key: String, values: Iterable<String>) = apply {
            additionalQueryParams.put(key, values)
        }

        fun putAllAdditionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.putAll(additionalQueryParams)
        }

        fun putAllAdditionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) =
            apply {
                this.additionalQueryParams.putAll(additionalQueryParams)
            }

        fun replaceAdditionalQueryParams(key: String, value: String) = apply {
            additionalQueryParams.replace(key, value)
        }

        fun replaceAdditionalQueryParams(key: String, values: Iterable<String>) = apply {
            additionalQueryParams.replace(key, values)
        }

        fun replaceAllAdditionalQueryParams(additionalQueryParams: QueryParams) = apply {
            this.additionalQueryParams.replaceAll(additionalQueryParams)
        }

        fun replaceAllAdditionalQueryParams(additionalQueryParams: Map<String, Iterable<String>>) =
            apply {
                this.additionalQueryParams.replaceAll(additionalQueryParams)
            }

        fun removeAdditionalQueryParams(key: String) = apply { additionalQueryParams.remove(key) }

        fun removeAllAdditionalQueryParams(keys: Set<String>) = apply {
            additionalQueryParams.removeAll(keys)
        }

        /**
         * Returns an immutable instance of [ImageEditParams].
         *
         * Further updates to this [Builder] will not mutate the returned instance.
         *
         * The following fields are required:
         * ```java
         * .image()
         * .prompt()
         * ```
         *
         * @throws IllegalStateException if any required field is unset.
         */
        fun build(): ImageEditParams =
            ImageEditParams(body.build(), additionalHeaders.build(), additionalQueryParams.build())
    }

    fun _body(): Map<String, MultipartField<*>> =
        (mapOf(
                "image" to _image(),
                "prompt" to _prompt(),
                "background" to _background(),
                "input_fidelity" to _inputFidelity(),
                "mask" to _mask(),
                "model" to _model(),
                "n" to _n(),
                "output_compression" to _outputCompression(),
                "output_format" to _outputFormat(),
                "partial_images" to _partialImages(),
                "quality" to _quality(),
                "response_format" to _responseFormat(),
                "size" to _size(),
                "user" to _user(),
            ) + _additionalBodyProperties().mapValues { (_, value) -> MultipartField.of(value) })
            .toImmutable()

    override fun _headers(): Headers = additionalHeaders

    override fun _queryParams(): QueryParams = additionalQueryParams

    class Body
    private constructor(
        private val image: MultipartField<Image>,
        private val prompt: MultipartField<String>,
        private val background: MultipartField<Background>,
        private val inputFidelity: MultipartField<InputFidelity>,
        private val mask: MultipartField<InputStream>,
        private val model: MultipartField<ImageModel>,
        private val n: MultipartField<Long>,
        private val outputCompression: MultipartField<Long>,
        private val outputFormat: MultipartField<OutputFormat>,
        private val partialImages: MultipartField<Long>,
        private val quality: MultipartField<Quality>,
        private val responseFormat: MultipartField<ResponseFormat>,
        private val size: MultipartField<String>,
        private val user: MultipartField<String>,
        private val additionalProperties: MutableMap<String, JsonValue>,
    ) {

        /**
         * The image(s) to edit. Must be a supported image file or an array of images.
         *
         * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
         * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should
         * be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16 images.
         *
         * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
         * than 4MB.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
         *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
         */
        fun image(): Image = image.value.getRequired("image")

        /**
         * A text description of the desired image(s). The maximum length is 1000 characters for
         * `dall-e-2`, and 32000 characters for the GPT image models.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type or is
         *   unexpectedly missing or null (e.g. if the server responded with an unexpected value).
         */
        fun prompt(): String = prompt.value.getRequired("prompt")

        /**
         * Allows to set transparency for the background of the generated image(s). This parameter
         * is only supported for GPT image models that support transparent backgrounds. Must be one
         * of `transparent`, `opaque`, or `auto` (default value). When `auto` is used, the model
         * will automatically determine the best background for the image.
         *
         * `gpt-image-2` and `gpt-image-2-2026-04-21` do not support transparent backgrounds.
         * Requests with `background` set to `transparent` will return an error for these models;
         * use `opaque` or `auto` instead.
         *
         * If `transparent`, the output format needs to support transparency, so it should be set to
         * either `png` (default value) or `webp`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun background(): Optional<Background> = background.value.getOptional("background")

        /**
         * Control how much effort the model will exert to match the style and features, especially
         * facial features, of input images. This parameter is only supported for `gpt-image-1` and
         * `gpt-image-1.5` and later models, unsupported for `gpt-image-1-mini`. Supports `high` and
         * `low`. Defaults to `low`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun inputFidelity(): Optional<InputFidelity> =
            inputFidelity.value.getOptional("input_fidelity")

        /**
         * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
         * where `image` should be edited. If there are multiple images provided, the mask will be
         * applied on the first image. Must be a valid PNG file, less than 4MB, and have the same
         * dimensions as `image`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun mask(): Optional<InputStream> = mask.value.getOptional("mask")

        /**
         * The model to use for image generation. One of `dall-e-2` or a GPT image model
         * (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`,
         * `gpt-image-2-2026-04-21`, or `chatgpt-image-latest`). Defaults to `gpt-image-1.5`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun model(): Optional<ImageModel> = model.value.getOptional("model")

        /**
         * The number of images to generate. Must be between 1 and 10.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun n(): Optional<Long> = n.value.getOptional("n")

        /**
         * The compression level (0-100%) for the generated images. This parameter is only supported
         * for the GPT image models with the `webp` or `jpeg` output formats, and defaults to 100.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun outputCompression(): Optional<Long> =
            outputCompression.value.getOptional("output_compression")

        /**
         * The format in which the generated images are returned. This parameter is only supported
         * for the GPT image models. Must be one of `png`, `jpeg`, or `webp`. The default value is
         * `png`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun outputFormat(): Optional<OutputFormat> = outputFormat.value.getOptional("output_format")

        /**
         * The number of partial images to generate. This parameter is used for streaming responses
         * that return partial images. Value must be between 0 and 3. When set to 0, the response
         * will be a single image sent in one streaming event.
         *
         * Note that the final image may be sent before the full number of partial images are
         * generated if the full image is generated more quickly.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun partialImages(): Optional<Long> = partialImages.value.getOptional("partial_images")

        /**
         * The quality of the image that will be generated for GPT image models. Defaults to `auto`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun quality(): Optional<Quality> = quality.value.getOptional("quality")

        /**
         * The format in which the generated images are returned. Must be one of `url` or
         * `b64_json`. URLs are only valid for 60 minutes after the image has been generated. This
         * parameter is only supported for `dall-e-2` (default is `url` for `dall-e-2`), as GPT
         * image models always return base64-encoded images.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun responseFormat(): Optional<ResponseFormat> =
            responseFormat.value.getOptional("response_format")

        /**
         * The size of the generated images. For `gpt-image-2` and `gpt-image-2-2026-04-21`,
         * arbitrary resolutions are supported as `WIDTHxHEIGHT` strings, for example `1536x864`.
         * Width and height must both be divisible by 16 and the requested aspect ratio must be
         * between 1:3 and 3:1. Resolutions above `2560x1440` are experimental, and the maximum
         * supported resolution is `3840x2160`. The requested size must also satisfy the model's
         * current pixel and edge limits. The standard sizes `1024x1024`, `1536x1024`, and
         * `1024x1536` are supported by the GPT image models; `auto` is supported for models that
         * allow automatic sizing. For `dall-e-2`, use one of `256x256`, `512x512`, or `1024x1024`.
         * For `dall-e-3`, use one of `1024x1024`, `1792x1024`, or `1024x1792`.
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun size(): Optional<String> = size.value.getOptional("size")

        /**
         * A unique identifier representing your end-user, which can help OpenAI to monitor and
         * detect abuse.
         * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
         *
         * @throws OpenAIInvalidDataException if the JSON field has an unexpected type (e.g. if the
         *   server responded with an unexpected value).
         */
        fun user(): Optional<String> = user.value.getOptional("user")

        /**
         * Returns the raw multipart value of [image].
         *
         * Unlike [image], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("image") @ExcludeMissing fun _image(): MultipartField<Image> = image

        /**
         * Returns the raw multipart value of [prompt].
         *
         * Unlike [prompt], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("prompt") @ExcludeMissing fun _prompt(): MultipartField<String> = prompt

        /**
         * Returns the raw multipart value of [background].
         *
         * Unlike [background], this method doesn't throw if the multipart field has an unexpected
         * type.
         */
        @JsonProperty("background")
        @ExcludeMissing
        fun _background(): MultipartField<Background> = background

        /**
         * Returns the raw multipart value of [inputFidelity].
         *
         * Unlike [inputFidelity], this method doesn't throw if the multipart field has an
         * unexpected type.
         */
        @JsonProperty("input_fidelity")
        @ExcludeMissing
        fun _inputFidelity(): MultipartField<InputFidelity> = inputFidelity

        /**
         * Returns the raw multipart value of [mask].
         *
         * Unlike [mask], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("mask") @ExcludeMissing fun _mask(): MultipartField<InputStream> = mask

        /**
         * Returns the raw multipart value of [model].
         *
         * Unlike [model], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("model") @ExcludeMissing fun _model(): MultipartField<ImageModel> = model

        /**
         * Returns the raw multipart value of [n].
         *
         * Unlike [n], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("n") @ExcludeMissing fun _n(): MultipartField<Long> = n

        /**
         * Returns the raw multipart value of [outputCompression].
         *
         * Unlike [outputCompression], this method doesn't throw if the multipart field has an
         * unexpected type.
         */
        @JsonProperty("output_compression")
        @ExcludeMissing
        fun _outputCompression(): MultipartField<Long> = outputCompression

        /**
         * Returns the raw multipart value of [outputFormat].
         *
         * Unlike [outputFormat], this method doesn't throw if the multipart field has an unexpected
         * type.
         */
        @JsonProperty("output_format")
        @ExcludeMissing
        fun _outputFormat(): MultipartField<OutputFormat> = outputFormat

        /**
         * Returns the raw multipart value of [partialImages].
         *
         * Unlike [partialImages], this method doesn't throw if the multipart field has an
         * unexpected type.
         */
        @JsonProperty("partial_images")
        @ExcludeMissing
        fun _partialImages(): MultipartField<Long> = partialImages

        /**
         * Returns the raw multipart value of [quality].
         *
         * Unlike [quality], this method doesn't throw if the multipart field has an unexpected
         * type.
         */
        @JsonProperty("quality") @ExcludeMissing fun _quality(): MultipartField<Quality> = quality

        /**
         * Returns the raw multipart value of [responseFormat].
         *
         * Unlike [responseFormat], this method doesn't throw if the multipart field has an
         * unexpected type.
         */
        @JsonProperty("response_format")
        @ExcludeMissing
        fun _responseFormat(): MultipartField<ResponseFormat> = responseFormat

        /**
         * Returns the raw multipart value of [size].
         *
         * Unlike [size], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("size") @ExcludeMissing fun _size(): MultipartField<String> = size

        /**
         * Returns the raw multipart value of [user].
         *
         * Unlike [user], this method doesn't throw if the multipart field has an unexpected type.
         */
        @JsonProperty("user") @ExcludeMissing fun _user(): MultipartField<String> = user

        @JsonAnySetter
        private fun putAdditionalProperty(key: String, value: JsonValue) {
            additionalProperties.put(key, value)
        }

        @JsonAnyGetter
        @ExcludeMissing
        fun _additionalProperties(): Map<String, JsonValue> =
            Collections.unmodifiableMap(additionalProperties)

        fun toBuilder() = Builder().from(this)

        companion object {

            /**
             * Returns a mutable builder for constructing an instance of [Body].
             *
             * The following fields are required:
             * ```java
             * .image()
             * .prompt()
             * ```
             */
            @JvmStatic fun builder() = Builder()
        }

        /** A builder for [Body]. */
        class Builder internal constructor() {

            private var image: MultipartField<Image>? = null
            private var prompt: MultipartField<String>? = null
            private var background: MultipartField<Background> = MultipartField.of(null)
            private var inputFidelity: MultipartField<InputFidelity> = MultipartField.of(null)
            private var mask: MultipartField<InputStream> = MultipartField.of(null)
            private var model: MultipartField<ImageModel> = MultipartField.of(null)
            private var n: MultipartField<Long> = MultipartField.of(null)
            private var outputCompression: MultipartField<Long> = MultipartField.of(null)
            private var outputFormat: MultipartField<OutputFormat> = MultipartField.of(null)
            private var partialImages: MultipartField<Long> = MultipartField.of(null)
            private var quality: MultipartField<Quality> = MultipartField.of(null)
            private var responseFormat: MultipartField<ResponseFormat> = MultipartField.of(null)
            private var size: MultipartField<String> = MultipartField.of(null)
            private var user: MultipartField<String> = MultipartField.of(null)
            private var additionalProperties: MutableMap<String, JsonValue> = mutableMapOf()

            @JvmSynthetic
            internal fun from(body: Body) = apply {
                image = body.image
                prompt = body.prompt
                background = body.background
                inputFidelity = body.inputFidelity
                mask = body.mask
                model = body.model
                n = body.n
                outputCompression = body.outputCompression
                outputFormat = body.outputFormat
                partialImages = body.partialImages
                quality = body.quality
                responseFormat = body.responseFormat
                size = body.size
                user = body.user
                additionalProperties = body.additionalProperties.toMutableMap()
            }

            /**
             * The image(s) to edit. Must be a supported image file or an array of images.
             *
             * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
             * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image
             * should be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16
             * images.
             *
             * For `dall-e-2`, you can only provide one image, and it should be a square `png` file
             * less than 4MB.
             */
            fun image(image: Image) =
                image(
                    MultipartField.builder<Image>()
                        .value(image)
                        .contentType("application/octet-stream")
                        .build()
                )

            /**
             * Sets [Builder.image] to an arbitrary multipart value.
             *
             * You should usually call [Builder.image] with a well-typed [Image] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun image(image: MultipartField<Image>) = apply { this.image = image }

            /** Alias for calling [image] with `Image.ofInputStream(inputStream)`. */
            fun image(inputStream: InputStream) = image(Image.ofInputStream(inputStream))

            /**
             * The image(s) to edit. Must be a supported image file or an array of images.
             *
             * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
             * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image
             * should be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16
             * images.
             *
             * For `dall-e-2`, you can only provide one image, and it should be a square `png` file
             * less than 4MB.
             */
            fun image(inputStream: ByteArray) = image(inputStream.inputStream())

            /**
             * The image(s) to edit. Must be a supported image file or an array of images.
             *
             * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`,
             * `gpt-image-2`, `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image
             * should be a `png`, `webp`, or `jpg` file less than 50MB. You can provide up to 16
             * images.
             *
             * For `dall-e-2`, you can only provide one image, and it should be a square `png` file
             * less than 4MB.
             */
            fun image(path: Path) =
                image(
                    MultipartField.builder<Image>()
                        .value(Image.ofInputStream(path.inputStream()))
                        .contentType("application/octet-stream")
                        .filename(path.name)
                        .build()
                )

            /** Alias for calling [image] with `Image.ofInputStreams(inputStreams)`. */
            fun imageOfInputStreams(inputStreams: List<InputStream>) =
                image(Image.ofInputStreams(inputStreams))

            /**
             * A text description of the desired image(s). The maximum length is 1000 characters for
             * `dall-e-2`, and 32000 characters for the GPT image models.
             */
            fun prompt(prompt: String) = prompt(MultipartField.of(prompt))

            /**
             * Sets [Builder.prompt] to an arbitrary multipart value.
             *
             * You should usually call [Builder.prompt] with a well-typed [String] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun prompt(prompt: MultipartField<String>) = apply { this.prompt = prompt }

            /**
             * Allows to set transparency for the background of the generated image(s). This
             * parameter is only supported for GPT image models that support transparent
             * backgrounds. Must be one of `transparent`, `opaque`, or `auto` (default value). When
             * `auto` is used, the model will automatically determine the best background for the
             * image.
             *
             * `gpt-image-2` and `gpt-image-2-2026-04-21` do not support transparent backgrounds.
             * Requests with `background` set to `transparent` will return an error for these
             * models; use `opaque` or `auto` instead.
             *
             * If `transparent`, the output format needs to support transparency, so it should be
             * set to either `png` (default value) or `webp`.
             */
            fun background(background: Background?) = background(MultipartField.of(background))

            /** Alias for calling [Builder.background] with `background.orElse(null)`. */
            fun background(background: Optional<Background>) = background(background.getOrNull())

            /**
             * Sets [Builder.background] to an arbitrary multipart value.
             *
             * You should usually call [Builder.background] with a well-typed [Background] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun background(background: MultipartField<Background>) = apply {
                this.background = background
            }

            /**
             * Control how much effort the model will exert to match the style and features,
             * especially facial features, of input images. This parameter is only supported for
             * `gpt-image-1` and `gpt-image-1.5` and later models, unsupported for
             * `gpt-image-1-mini`. Supports `high` and `low`. Defaults to `low`.
             */
            fun inputFidelity(inputFidelity: InputFidelity?) =
                inputFidelity(MultipartField.of(inputFidelity))

            /** Alias for calling [Builder.inputFidelity] with `inputFidelity.orElse(null)`. */
            fun inputFidelity(inputFidelity: Optional<InputFidelity>) =
                inputFidelity(inputFidelity.getOrNull())

            /**
             * Sets [Builder.inputFidelity] to an arbitrary multipart value.
             *
             * You should usually call [Builder.inputFidelity] with a well-typed [InputFidelity]
             * value instead. This method is primarily for setting the field to an undocumented or
             * not yet supported value.
             */
            fun inputFidelity(inputFidelity: MultipartField<InputFidelity>) = apply {
                this.inputFidelity = inputFidelity
            }

            /**
             * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
             * where `image` should be edited. If there are multiple images provided, the mask will
             * be applied on the first image. Must be a valid PNG file, less than 4MB, and have the
             * same dimensions as `image`.
             */
            fun mask(mask: InputStream) = mask(MultipartField.of(mask))

            /**
             * Sets [Builder.mask] to an arbitrary multipart value.
             *
             * You should usually call [Builder.mask] with a well-typed [InputStream] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun mask(mask: MultipartField<InputStream>) = apply { this.mask = mask }

            /**
             * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
             * where `image` should be edited. If there are multiple images provided, the mask will
             * be applied on the first image. Must be a valid PNG file, less than 4MB, and have the
             * same dimensions as `image`.
             */
            fun mask(mask: ByteArray) = mask(mask.inputStream())

            /**
             * An additional image whose fully transparent areas (e.g. where alpha is zero) indicate
             * where `image` should be edited. If there are multiple images provided, the mask will
             * be applied on the first image. Must be a valid PNG file, less than 4MB, and have the
             * same dimensions as `image`.
             */
            fun mask(path: Path) =
                mask(
                    MultipartField.builder<InputStream>()
                        .value(path.inputStream())
                        .filename(path.name)
                        .build()
                )

            /**
             * The model to use for image generation. One of `dall-e-2` or a GPT image model
             * (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`,
             * `gpt-image-2-2026-04-21`, or `chatgpt-image-latest`). Defaults to `gpt-image-1.5`.
             */
            fun model(model: ImageModel?) = model(MultipartField.of(model))

            /** Alias for calling [Builder.model] with `model.orElse(null)`. */
            fun model(model: Optional<ImageModel>) = model(model.getOrNull())

            /**
             * Sets [Builder.model] to an arbitrary multipart value.
             *
             * You should usually call [Builder.model] with a well-typed [ImageModel] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun model(model: MultipartField<ImageModel>) = apply { this.model = model }

            /**
             * Sets [model] to an arbitrary [String].
             *
             * You should usually call [model] with a well-typed [ImageModel] constant instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun model(value: String) = model(ImageModel.of(value))

            /** The number of images to generate. Must be between 1 and 10. */
            fun n(n: Long?) = n(MultipartField.of(n))

            /**
             * Alias for [Builder.n].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun n(n: Long) = n(n as Long?)

            /** Alias for calling [Builder.n] with `n.orElse(null)`. */
            fun n(n: Optional<Long>) = n(n.getOrNull())

            /**
             * Sets [Builder.n] to an arbitrary multipart value.
             *
             * You should usually call [Builder.n] with a well-typed [Long] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun n(n: MultipartField<Long>) = apply { this.n = n }

            /**
             * The compression level (0-100%) for the generated images. This parameter is only
             * supported for the GPT image models with the `webp` or `jpeg` output formats, and
             * defaults to 100.
             */
            fun outputCompression(outputCompression: Long?) =
                outputCompression(MultipartField.of(outputCompression))

            /**
             * Alias for [Builder.outputCompression].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun outputCompression(outputCompression: Long) =
                outputCompression(outputCompression as Long?)

            /**
             * Alias for calling [Builder.outputCompression] with `outputCompression.orElse(null)`.
             */
            fun outputCompression(outputCompression: Optional<Long>) =
                outputCompression(outputCompression.getOrNull())

            /**
             * Sets [Builder.outputCompression] to an arbitrary multipart value.
             *
             * You should usually call [Builder.outputCompression] with a well-typed [Long] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun outputCompression(outputCompression: MultipartField<Long>) = apply {
                this.outputCompression = outputCompression
            }

            /**
             * The format in which the generated images are returned. This parameter is only
             * supported for the GPT image models. Must be one of `png`, `jpeg`, or `webp`. The
             * default value is `png`.
             */
            fun outputFormat(outputFormat: OutputFormat?) =
                outputFormat(MultipartField.of(outputFormat))

            /** Alias for calling [Builder.outputFormat] with `outputFormat.orElse(null)`. */
            fun outputFormat(outputFormat: Optional<OutputFormat>) =
                outputFormat(outputFormat.getOrNull())

            /**
             * Sets [Builder.outputFormat] to an arbitrary multipart value.
             *
             * You should usually call [Builder.outputFormat] with a well-typed [OutputFormat] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun outputFormat(outputFormat: MultipartField<OutputFormat>) = apply {
                this.outputFormat = outputFormat
            }

            /**
             * The number of partial images to generate. This parameter is used for streaming
             * responses that return partial images. Value must be between 0 and 3. When set to 0,
             * the response will be a single image sent in one streaming event.
             *
             * Note that the final image may be sent before the full number of partial images are
             * generated if the full image is generated more quickly.
             */
            fun partialImages(partialImages: Long?) =
                partialImages(MultipartField.of(partialImages))

            /**
             * Alias for [Builder.partialImages].
             *
             * This unboxed primitive overload exists for backwards compatibility.
             */
            fun partialImages(partialImages: Long) = partialImages(partialImages as Long?)

            /** Alias for calling [Builder.partialImages] with `partialImages.orElse(null)`. */
            fun partialImages(partialImages: Optional<Long>) =
                partialImages(partialImages.getOrNull())

            /**
             * Sets [Builder.partialImages] to an arbitrary multipart value.
             *
             * You should usually call [Builder.partialImages] with a well-typed [Long] value
             * instead. This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun partialImages(partialImages: MultipartField<Long>) = apply {
                this.partialImages = partialImages
            }

            /**
             * The quality of the image that will be generated for GPT image models. Defaults to
             * `auto`.
             */
            fun quality(quality: Quality?) = quality(MultipartField.of(quality))

            /** Alias for calling [Builder.quality] with `quality.orElse(null)`. */
            fun quality(quality: Optional<Quality>) = quality(quality.getOrNull())

            /**
             * Sets [Builder.quality] to an arbitrary multipart value.
             *
             * You should usually call [Builder.quality] with a well-typed [Quality] value instead.
             * This method is primarily for setting the field to an undocumented or not yet
             * supported value.
             */
            fun quality(quality: MultipartField<Quality>) = apply { this.quality = quality }

            /**
             * The format in which the generated images are returned. Must be one of `url` or
             * `b64_json`. URLs are only valid for 60 minutes after the image has been generated.
             * This parameter is only supported for `dall-e-2` (default is `url` for `dall-e-2`), as
             * GPT image models always return base64-encoded images.
             */
            fun responseFormat(responseFormat: ResponseFormat?) =
                responseFormat(MultipartField.of(responseFormat))

            /** Alias for calling [Builder.responseFormat] with `responseFormat.orElse(null)`. */
            fun responseFormat(responseFormat: Optional<ResponseFormat>) =
                responseFormat(responseFormat.getOrNull())

            /**
             * Sets [Builder.responseFormat] to an arbitrary multipart value.
             *
             * You should usually call [Builder.responseFormat] with a well-typed [ResponseFormat]
             * value instead. This method is primarily for setting the field to an undocumented or
             * not yet supported value.
             */
            fun responseFormat(responseFormat: MultipartField<ResponseFormat>) = apply {
                this.responseFormat = responseFormat
            }

            /**
             * The size of the generated images. For `gpt-image-2` and `gpt-image-2-2026-04-21`,
             * arbitrary resolutions are supported as `WIDTHxHEIGHT` strings, for example
             * `1536x864`. Width and height must both be divisible by 16 and the requested aspect
             * ratio must be between 1:3 and 3:1. Resolutions above `2560x1440` are experimental,
             * and the maximum supported resolution is `3840x2160`. The requested size must also
             * satisfy the model's current pixel and edge limits. The standard sizes `1024x1024`,
             * `1536x1024`, and `1024x1536` are supported by the GPT image models; `auto` is
             * supported for models that allow automatic sizing. For `dall-e-2`, use one of
             * `256x256`, `512x512`, or `1024x1024`. For `dall-e-3`, use one of `1024x1024`,
             * `1792x1024`, or `1024x1792`.
             */
            fun size(size: String?) = size(MultipartField.of(size))

            /** Alias for calling [Builder.size] with `size.orElse(null)`. */
            fun size(size: Optional<String>) = size(size.getOrNull())

            /**
             * Sets [Builder.size] to an arbitrary multipart value.
             *
             * You should usually call [Builder.size] with a well-typed [String] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun size(size: MultipartField<String>) = apply { this.size = size }

            /**
             * A unique identifier representing your end-user, which can help OpenAI to monitor and
             * detect abuse.
             * [Learn more](https://platform.openai.com/docs/guides/safety-best-practices#end-user-ids).
             */
            fun user(user: String) = user(MultipartField.of(user))

            /**
             * Sets [Builder.user] to an arbitrary multipart value.
             *
             * You should usually call [Builder.user] with a well-typed [String] value instead. This
             * method is primarily for setting the field to an undocumented or not yet supported
             * value.
             */
            fun user(user: MultipartField<String>) = apply { this.user = user }

            fun additionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.clear()
                putAllAdditionalProperties(additionalProperties)
            }

            fun putAdditionalProperty(key: String, value: JsonValue) = apply {
                additionalProperties.put(key, value)
            }

            fun putAllAdditionalProperties(additionalProperties: Map<String, JsonValue>) = apply {
                this.additionalProperties.putAll(additionalProperties)
            }

            fun removeAdditionalProperty(key: String) = apply { additionalProperties.remove(key) }

            fun removeAllAdditionalProperties(keys: Set<String>) = apply {
                keys.forEach(::removeAdditionalProperty)
            }

            /**
             * Returns an immutable instance of [Body].
             *
             * Further updates to this [Builder] will not mutate the returned instance.
             *
             * The following fields are required:
             * ```java
             * .image()
             * .prompt()
             * ```
             *
             * @throws IllegalStateException if any required field is unset.
             */
            fun build(): Body =
                Body(
                    checkRequired("image", image),
                    checkRequired("prompt", prompt),
                    background,
                    inputFidelity,
                    mask,
                    model,
                    n,
                    outputCompression,
                    outputFormat,
                    partialImages,
                    quality,
                    responseFormat,
                    size,
                    user,
                    additionalProperties.toMutableMap(),
                )
        }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): Body = apply {
            if (validated) {
                return@apply
            }

            image().validate()
            prompt()
            background().ifPresent { it.validate() }
            inputFidelity().ifPresent { it.validate() }
            mask()
            model().ifPresent { it.validate() }
            n()
            outputCompression()
            outputFormat().ifPresent { it.validate() }
            partialImages()
            quality().ifPresent { it.validate() }
            responseFormat().ifPresent { it.validate() }
            size()
            user()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is Body &&
                image == other.image &&
                prompt == other.prompt &&
                background == other.background &&
                inputFidelity == other.inputFidelity &&
                mask == other.mask &&
                model == other.model &&
                n == other.n &&
                outputCompression == other.outputCompression &&
                outputFormat == other.outputFormat &&
                partialImages == other.partialImages &&
                quality == other.quality &&
                responseFormat == other.responseFormat &&
                size == other.size &&
                user == other.user &&
                additionalProperties == other.additionalProperties
        }

        private val hashCode: Int by lazy {
            Objects.hash(
                image,
                prompt,
                background,
                inputFidelity,
                mask,
                model,
                n,
                outputCompression,
                outputFormat,
                partialImages,
                quality,
                responseFormat,
                size,
                user,
                additionalProperties,
            )
        }

        override fun hashCode(): Int = hashCode

        override fun toString() =
            "Body{image=$image, prompt=$prompt, background=$background, inputFidelity=$inputFidelity, mask=$mask, model=$model, n=$n, outputCompression=$outputCompression, outputFormat=$outputFormat, partialImages=$partialImages, quality=$quality, responseFormat=$responseFormat, size=$size, user=$user, additionalProperties=$additionalProperties}"
    }

    /**
     * The image(s) to edit. Must be a supported image file or an array of images.
     *
     * For the GPT image models (`gpt-image-1`, `gpt-image-1-mini`, `gpt-image-1.5`, `gpt-image-2`,
     * `gpt-image-2-2026-04-21`, and `chatgpt-image-latest`), each image should be a `png`, `webp`,
     * or `jpg` file less than 50MB. You can provide up to 16 images.
     *
     * For `dall-e-2`, you can only provide one image, and it should be a square `png` file less
     * than 4MB.
     */
    @JsonSerialize(using = Image.Serializer::class)
    class Image
    private constructor(
        private val inputStream: InputStream? = null,
        private val inputStreams: List<InputStream>? = null,
        private val _json: JsonValue? = null,
    ) {

        fun inputStream(): Optional<InputStream> = Optional.ofNullable(inputStream)

        fun inputStreams(): Optional<List<InputStream>> = Optional.ofNullable(inputStreams)

        fun isInputStream(): Boolean = inputStream != null

        fun isInputStreams(): Boolean = inputStreams != null

        fun asInputStream(): InputStream = inputStream.getOrThrow("inputStream")

        fun asInputStreams(): List<InputStream> = inputStreams.getOrThrow("inputStreams")

        fun _json(): Optional<JsonValue> = Optional.ofNullable(_json)

        /**
         * Maps this instance's current variant to a value of type [T] using the given [visitor].
         *
         * Note that this method is _not_ forwards compatible with new variants from the API, unless
         * [visitor] overrides [Visitor.unknown]. To handle variants not known to this version of
         * the SDK gracefully, consider overriding [Visitor.unknown]:
         * ```java
         * import com.openai.core.JsonValue;
         * import java.util.Optional;
         *
         * Optional<String> result = image.accept(new Image.Visitor<Optional<String>>() {
         *     @Override
         *     public Optional<String> visitInputStream(InputStream inputStream) {
         *         return Optional.of(inputStream.toString());
         *     }
         *
         *     // ...
         *
         *     @Override
         *     public Optional<String> unknown(JsonValue json) {
         *         // Or inspect the `json`.
         *         return Optional.empty();
         *     }
         * });
         * ```
         *
         * @throws OpenAIInvalidDataException if [Visitor.unknown] is not overridden in [visitor]
         *   and the current variant is unknown.
         */
        fun <T> accept(visitor: Visitor<T>): T =
            when {
                inputStream != null -> visitor.visitInputStream(inputStream)
                inputStreams != null -> visitor.visitInputStreams(inputStreams)
                else -> visitor.unknown(_json)
            }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): Image = apply {
            if (validated) {
                return@apply
            }

            accept(
                object : Visitor<Unit> {
                    override fun visitInputStream(inputStream: InputStream) {}

                    override fun visitInputStreams(inputStreams: List<InputStream>) {}
                }
            )
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is Image &&
                inputStream == other.inputStream &&
                inputStreams == other.inputStreams
        }

        override fun hashCode(): Int = Objects.hash(inputStream, inputStreams)

        override fun toString(): String =
            when {
                inputStream != null -> "Image{inputStream=$inputStream}"
                inputStreams != null -> "Image{inputStreams=$inputStreams}"
                _json != null -> "Image{_unknown=$_json}"
                else -> throw IllegalStateException("Invalid Image")
            }

        companion object {

            @JvmStatic
            fun ofInputStream(inputStream: InputStream) = Image(inputStream = inputStream)

            @JvmStatic
            fun ofInputStreams(inputStreams: List<InputStream>) =
                Image(inputStreams = inputStreams.toImmutable())
        }

        /** An interface that defines how to map each variant of [Image] to a value of type [T]. */
        interface Visitor<out T> {

            fun visitInputStream(inputStream: InputStream): T

            fun visitInputStreams(inputStreams: List<InputStream>): T

            /**
             * Maps an unknown variant of [Image] to a value of type [T].
             *
             * An instance of [Image] can contain an unknown variant if it was deserialized from
             * data that doesn't match any known variant. For example, if the SDK is on an older
             * version than the API, then the API may respond with new variants that the SDK is
             * unaware of.
             *
             * @throws OpenAIInvalidDataException in the default implementation.
             */
            fun unknown(json: JsonValue?): T {
                throw OpenAIInvalidDataException("Unknown Image: $json")
            }
        }

        internal class Serializer : BaseSerializer<Image>(Image::class) {

            override fun serialize(
                value: Image,
                generator: JsonGenerator,
                provider: SerializerProvider,
            ) {
                when {
                    value.inputStream != null -> generator.writeObject(value.inputStream)
                    value.inputStreams != null -> generator.writeObject(value.inputStreams)
                    value._json != null -> generator.writeObject(value._json)
                    else -> throw IllegalStateException("Invalid Image")
                }
            }
        }
    }

    /**
     * Allows to set transparency for the background of the generated image(s). This parameter is
     * only supported for GPT image models that support transparent backgrounds. Must be one of
     * `transparent`, `opaque`, or `auto` (default value). When `auto` is used, the model will
     * automatically determine the best background for the image.
     *
     * `gpt-image-2` and `gpt-image-2-2026-04-21` do not support transparent backgrounds. Requests
     * with `background` set to `transparent` will return an error for these models; use `opaque` or
     * `auto` instead.
     *
     * If `transparent`, the output format needs to support transparency, so it should be set to
     * either `png` (default value) or `webp`.
     */
    class Background @JsonCreator private constructor(private val value: JsonField<String>) : Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val TRANSPARENT = of("transparent")

            @JvmField val OPAQUE = of("opaque")

            @JvmField val AUTO = of("auto")

            @JvmStatic fun of(value: String) = Background(JsonField.of(value))
        }

        /** An enum containing [Background]'s known values. */
        enum class Known {
            TRANSPARENT,
            OPAQUE,
            AUTO,
        }

        /**
         * An enum containing [Background]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [Background] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            TRANSPARENT,
            OPAQUE,
            AUTO,
            /**
             * An enum member indicating that [Background] was instantiated with an unknown value.
             */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                TRANSPARENT -> Value.TRANSPARENT
                OPAQUE -> Value.OPAQUE
                AUTO -> Value.AUTO
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                TRANSPARENT -> Known.TRANSPARENT
                OPAQUE -> Known.OPAQUE
                AUTO -> Known.AUTO
                else -> throw OpenAIInvalidDataException("Unknown Background: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): Background = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is Background && value == other.value
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    /**
     * Control how much effort the model will exert to match the style and features, especially
     * facial features, of input images. This parameter is only supported for `gpt-image-1` and
     * `gpt-image-1.5` and later models, unsupported for `gpt-image-1-mini`. Supports `high` and
     * `low`. Defaults to `low`.
     */
    class InputFidelity @JsonCreator private constructor(private val value: JsonField<String>) :
        Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val HIGH = of("high")

            @JvmField val LOW = of("low")

            @JvmStatic fun of(value: String) = InputFidelity(JsonField.of(value))
        }

        /** An enum containing [InputFidelity]'s known values. */
        enum class Known {
            HIGH,
            LOW,
        }

        /**
         * An enum containing [InputFidelity]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [InputFidelity] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            HIGH,
            LOW,
            /**
             * An enum member indicating that [InputFidelity] was instantiated with an unknown
             * value.
             */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                HIGH -> Value.HIGH
                LOW -> Value.LOW
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                HIGH -> Known.HIGH
                LOW -> Known.LOW
                else -> throw OpenAIInvalidDataException("Unknown InputFidelity: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): InputFidelity = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is InputFidelity && value == other.value
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    /**
     * The format in which the generated images are returned. This parameter is only supported for
     * the GPT image models. Must be one of `png`, `jpeg`, or `webp`. The default value is `png`.
     */
    class OutputFormat @JsonCreator private constructor(private val value: JsonField<String>) :
        Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val PNG = of("png")

            @JvmField val JPEG = of("jpeg")

            @JvmField val WEBP = of("webp")

            @JvmStatic fun of(value: String) = OutputFormat(JsonField.of(value))
        }

        /** An enum containing [OutputFormat]'s known values. */
        enum class Known {
            PNG,
            JPEG,
            WEBP,
        }

        /**
         * An enum containing [OutputFormat]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [OutputFormat] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            PNG,
            JPEG,
            WEBP,
            /**
             * An enum member indicating that [OutputFormat] was instantiated with an unknown value.
             */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                PNG -> Value.PNG
                JPEG -> Value.JPEG
                WEBP -> Value.WEBP
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                PNG -> Known.PNG
                JPEG -> Known.JPEG
                WEBP -> Known.WEBP
                else -> throw OpenAIInvalidDataException("Unknown OutputFormat: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): OutputFormat = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is OutputFormat && value == other.value
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    /** The quality of the image that will be generated for GPT image models. Defaults to `auto`. */
    class Quality @JsonCreator private constructor(private val value: JsonField<String>) : Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val STANDARD = of("standard")

            @JvmField val LOW = of("low")

            @JvmField val MEDIUM = of("medium")

            @JvmField val HIGH = of("high")

            @JvmField val AUTO = of("auto")

            @JvmStatic fun of(value: String) = Quality(JsonField.of(value))
        }

        /** An enum containing [Quality]'s known values. */
        enum class Known {
            STANDARD,
            LOW,
            MEDIUM,
            HIGH,
            AUTO,
        }

        /**
         * An enum containing [Quality]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [Quality] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            STANDARD,
            LOW,
            MEDIUM,
            HIGH,
            AUTO,
            /** An enum member indicating that [Quality] was instantiated with an unknown value. */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                STANDARD -> Value.STANDARD
                LOW -> Value.LOW
                MEDIUM -> Value.MEDIUM
                HIGH -> Value.HIGH
                AUTO -> Value.AUTO
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                STANDARD -> Known.STANDARD
                LOW -> Known.LOW
                MEDIUM -> Known.MEDIUM
                HIGH -> Known.HIGH
                AUTO -> Known.AUTO
                else -> throw OpenAIInvalidDataException("Unknown Quality: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): Quality = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is Quality && value == other.value
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    /**
     * The format in which the generated images are returned. Must be one of `url` or `b64_json`.
     * URLs are only valid for 60 minutes after the image has been generated. This parameter is only
     * supported for `dall-e-2` (default is `url` for `dall-e-2`), as GPT image models always return
     * base64-encoded images.
     */
    class ResponseFormat @JsonCreator private constructor(private val value: JsonField<String>) :
        Enum {

        /**
         * Returns this class instance's raw value.
         *
         * This is usually only useful if this instance was deserialized from data that doesn't
         * match any known member, and you want to know that value. For example, if the SDK is on an
         * older version than the API, then the API may respond with new members that the SDK is
         * unaware of.
         */
        @com.fasterxml.jackson.annotation.JsonValue fun _value(): JsonField<String> = value

        companion object {

            @JvmField val URL = of("url")

            @JvmField val B64_JSON = of("b64_json")

            @JvmStatic fun of(value: String) = ResponseFormat(JsonField.of(value))
        }

        /** An enum containing [ResponseFormat]'s known values. */
        enum class Known {
            URL,
            B64_JSON,
        }

        /**
         * An enum containing [ResponseFormat]'s known values, as well as an [_UNKNOWN] member.
         *
         * An instance of [ResponseFormat] can contain an unknown value in a couple of cases:
         * - It was deserialized from data that doesn't match any known member. For example, if the
         *   SDK is on an older version than the API, then the API may respond with new members that
         *   the SDK is unaware of.
         * - It was constructed with an arbitrary value using the [of] method.
         */
        enum class Value {
            URL,
            B64_JSON,
            /**
             * An enum member indicating that [ResponseFormat] was instantiated with an unknown
             * value.
             */
            _UNKNOWN,
        }

        /**
         * Returns an enum member corresponding to this class instance's value, or [Value._UNKNOWN]
         * if the class was instantiated with an unknown value.
         *
         * Use the [known] method instead if you're certain the value is always known or if you want
         * to throw for the unknown case.
         */
        fun value(): Value =
            when (this) {
                URL -> Value.URL
                B64_JSON -> Value.B64_JSON
                else -> Value._UNKNOWN
            }

        /**
         * Returns an enum member corresponding to this class instance's value.
         *
         * Use the [value] method instead if you're uncertain the value is always known and don't
         * want to throw for the unknown case.
         *
         * @throws OpenAIInvalidDataException if this class instance's value is a not a known
         *   member.
         */
        fun known(): Known =
            when (this) {
                URL -> Known.URL
                B64_JSON -> Known.B64_JSON
                else -> throw OpenAIInvalidDataException("Unknown ResponseFormat: $value")
            }

        /**
         * Returns this class instance's primitive wire representation.
         *
         * This differs from the [toString] method because that method is primarily for debugging
         * and generally doesn't throw.
         *
         * @throws OpenAIInvalidDataException if this class instance's value does not have the
         *   expected primitive type.
         */
        fun asString(): String =
            _value().asString().orElseThrow { OpenAIInvalidDataException("Value is not a String") }

        private var validated: Boolean = false

        /**
         * Validates that the types of all values in this object match their expected types
         * recursively.
         *
         * This method is _not_ forwards compatible with new types from the API for existing fields.
         *
         * @throws OpenAIInvalidDataException if any value type in this object doesn't match its
         *   expected type.
         */
        fun validate(): ResponseFormat = apply {
            if (validated) {
                return@apply
            }

            known()
            validated = true
        }

        fun isValid(): Boolean =
            try {
                validate()
                true
            } catch (e: OpenAIInvalidDataException) {
                false
            }

        /**
         * Returns a score indicating how many valid values are contained in this object
         * recursively.
         *
         * Used for best match union deserialization.
         */
        @JvmSynthetic internal fun validity(): Int = if (value() == Value._UNKNOWN) 0 else 1

        override fun equals(other: Any?): Boolean {
            if (this === other) {
                return true
            }

            return other is ResponseFormat && value == other.value
        }

        override fun hashCode() = value.hashCode()

        override fun toString() = value.toString()
    }

    override fun equals(other: Any?): Boolean {
        if (this === other) {
            return true
        }

        return other is ImageEditParams &&
            body == other.body &&
            additionalHeaders == other.additionalHeaders &&
            additionalQueryParams == other.additionalQueryParams
    }

    override fun hashCode(): Int = Objects.hash(body, additionalHeaders, additionalQueryParams)

    override fun toString() =
        "ImageEditParams{body=$body, additionalHeaders=$additionalHeaders, additionalQueryParams=$additionalQueryParams}"
}
