import {z} from 'zod'

export type GoogleCloudAiplatformV1SampleConfig = {followingBatchSamplePercentage?: number | undefined, initialBatchSamplePercentage?: number | undefined, sampleStrategy?: ('SAMPLE_STRATEGY_UNSPECIFIED' | 'UNCERTAINTY') | undefined};

export type GoogleCloudAiplatformV1TrainingConfig = {timeoutTrainingMilliHours?: unknown | undefined};

export type GoogleCloudAiplatformV1ActiveLearningConfig = {maxDataItemCount?: unknown | undefined, maxDataItemPercentage?: number | undefined, sampleConfig?: GoogleCloudAiplatformV1SampleConfig | undefined, trainingConfig?: GoogleCloudAiplatformV1TrainingConfig | undefined};

export type GoogleTypeMoney = {currencyCode?: string | undefined, nanos?: number | undefined, units?: unknown | undefined};

export type GoogleCloudAiplatformV1EncryptionSpec = {kmsKeyName?: string | undefined};

export type GoogleRpcStatus = {code?: number | undefined, details?: Array<{[key: string]: unknown}> | undefined, message?: string | undefined};

export type GoogleCloudAiplatformV1DataLabelingJob = {activeLearningConfig?: GoogleCloudAiplatformV1ActiveLearningConfig | undefined, annotationLabels?: {[key: string]: string} | undefined, createTime?: unknown | undefined, currentSpend?: GoogleTypeMoney | undefined, datasets?: Array<string> | undefined, displayName?: string | undefined, encryptionSpec?: GoogleCloudAiplatformV1EncryptionSpec | undefined, error?: GoogleRpcStatus | undefined, inputs: unknown, inputsSchemaUri?: string | undefined, instructionUri?: string | undefined, labelerCount?: number | undefined, labelingProgress?: number | undefined, labels?: {[key: string]: string} | undefined, name?: string | undefined, specialistPools?: Array<string> | undefined, state?: ('JOB_STATE_UNSPECIFIED' | 'JOB_STATE_QUEUED' | 'JOB_STATE_PENDING' | 'JOB_STATE_RUNNING' | 'JOB_STATE_SUCCEEDED' | 'JOB_STATE_FAILED' | 'JOB_STATE_CANCELLING' | 'JOB_STATE_CANCELLED' | 'JOB_STATE_PAUSED' | 'JOB_STATE_EXPIRED' | 'JOB_STATE_UPDATING' | 'JOB_STATE_PARTIALLY_SUCCEEDED') | undefined, updateTime?: unknown | undefined};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdDataLabelingJobsArgs = {projectsId: string, locationsId: string, body: GoogleCloudAiplatformV1DataLabelingJob};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdDataLabelingJobsOptions = {baseUrl?: string | undefined, Oauth2?: string | undefined, Oauth2c?: string | undefined, fetch?: typeof fetch | undefined};

export const googleCloudAiplatformV1SampleConfig = z.object({followingBatchSamplePercentage: z.number().int().optional(), initialBatchSamplePercentage: z.number().int().optional(), sampleStrategy: z.enum(["SAMPLE_STRATEGY_UNSPECIFIED", "UNCERTAINTY"]).optional()});

export const googleCloudAiplatformV1TrainingConfig = z.object({timeoutTrainingMilliHours: z.string().optional()});

export const googleCloudAiplatformV1ActiveLearningConfig = z.object({maxDataItemCount: z.string().optional(), maxDataItemPercentage: z.number().int().optional(), sampleConfig: googleCloudAiplatformV1SampleConfig.optional(), trainingConfig: googleCloudAiplatformV1TrainingConfig.optional()});

export const googleTypeMoney = z.object({currencyCode: z.string().optional(), nanos: z.number().int().optional(), units: z.string().optional()});

export const googleCloudAiplatformV1EncryptionSpec = z.object({kmsKeyName: z.string().optional()});

export const googleRpcStatus = z.object({code: z.number().int().optional(), details: z.array(z.record(z.string(), z.unknown())).optional(), message: z.string().optional()});

export const googleCloudAiplatformV1DataLabelingJob = z.object({activeLearningConfig: googleCloudAiplatformV1ActiveLearningConfig.optional(), annotationLabels: z.record(z.string(), z.string()).optional(), createTime: z.string().optional(), currentSpend: googleTypeMoney.optional(), datasets: z.array(z.string()).optional(), displayName: z.string().optional(), encryptionSpec: googleCloudAiplatformV1EncryptionSpec.optional(), error: googleRpcStatus.optional(), inputs: z.unknown(), inputsSchemaUri: z.string().optional(), instructionUri: z.string().optional(), labelerCount: z.number().int().optional(), labelingProgress: z.number().int().optional(), labels: z.record(z.string(), z.string()).optional(), name: z.string().optional(), specialistPools: z.array(z.string()).optional(), state: z.enum(["JOB_STATE_UNSPECIFIED", "JOB_STATE_QUEUED", "JOB_STATE_PENDING", "JOB_STATE_RUNNING", "JOB_STATE_SUCCEEDED", "JOB_STATE_FAILED", "JOB_STATE_CANCELLING", "JOB_STATE_CANCELLED", "JOB_STATE_PAUSED", "JOB_STATE_EXPIRED", "JOB_STATE_UPDATING", "JOB_STATE_PARTIALLY_SUCCEEDED"]).optional(), updateTime: z.string().optional()});

export const validateResponse = async <Output>(
  schema: {
    readonly '~standard': {
      readonly validate: (value: unknown) => ({ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }) | Promise<{ readonly value: Output; readonly issues?: undefined } | { readonly issues: ReadonlyArray<{ readonly message: string; readonly path?: ReadonlyArray<PropertyKey | { readonly key: PropertyKey }> | undefined }> }>
    }
  },
  value: unknown
): Promise<Output> => {
  const result = await schema['~standard'].validate(value)

  if (result.issues !== undefined) {
    const detail = result.issues
      .map(({ message, path }) =>
        path?.length
          ? `${path.map((segment) => String(typeof segment === 'object' ? segment.key : segment)).join('.')}: ${message}`
          : message
      )
      .join('; ')

    throw new Error(`Response does not match the schema: ${detail}`, { cause: { issues: result.issues } })
  }

  return result.value
};

/**
 * Creates a DataLabelingJob.
 * 
 * POST /v1/projects/{projectsId}/locations/{locationsId}/dataLabelingJobs
 */
export const createApiV1ProjectsProjectsIdLocationsLocationsIdDataLabelingJobs = async (args: CreateApiV1ProjectsProjectsIdLocationsLocationsIdDataLabelingJobsArgs, options?: CreateApiV1ProjectsProjectsIdLocationsLocationsIdDataLabelingJobsOptions) => {
const {baseUrl = "https://aiplatform.googleapis.com", fetch: fetchFn = fetch, Oauth2, Oauth2c} = options ?? {}

const query = new URLSearchParams()
const headers = new Headers()
headers.set('content-type', "application/json")
headers.set('accept', "application/json")

if (Oauth2 !== undefined) headers.set('authorization', `Bearer ${Oauth2}`)
if (Oauth2c !== undefined) headers.set('authorization', `Bearer ${Oauth2c}`)

const url = `${baseUrl.replace(/\/+$/, '')}/v1/projects/${encodeURIComponent(String(args.projectsId))}/locations/${encodeURIComponent(String(args.locationsId))}/dataLabelingJobs${query.size > 0 ? `?${query}` : ''}`

const res = await fetchFn(url, {method: "POST", headers, body: JSON.stringify(args.body)})

if (!res.ok) throw new Error(`Request failed with status ${res.status}`, {cause: {status: res.status, body: await res.text()}})

return validateResponse(googleCloudAiplatformV1DataLabelingJob, await res.json())
};