import {z} from 'zod'

export type GoogleCloudAiplatformV1GenieSource = {baseModelUri?: string | undefined};

export type GoogleCloudAiplatformV1ModelGardenSource = {publicModelName?: string | undefined, skipHfModelCache?: boolean | undefined, versionId?: string | undefined};

export type GoogleCloudAiplatformV1ModelBaseModelSource = {genieSource?: GoogleCloudAiplatformV1GenieSource | undefined, modelGardenSource?: GoogleCloudAiplatformV1ModelGardenSource | undefined};

export type GoogleCloudAiplatformV1Checkpoint = {checkpointId?: string | undefined, epoch?: unknown | undefined, step?: unknown | undefined};

export type GoogleCloudAiplatformV1EnvVar = {name?: string | undefined, value?: string | undefined};

export type GoogleCloudAiplatformV1Port = {containerPort?: number | undefined};

export type GoogleCloudAiplatformV1ProbeExecAction = {command?: Array<string> | undefined};

export type GoogleCloudAiplatformV1ProbeGrpcAction = {port?: number | undefined, service?: string | undefined};

export type GoogleCloudAiplatformV1ProbeHttpHeader = {name?: string | undefined, value?: string | undefined};

export type GoogleCloudAiplatformV1ProbeHttpGetAction = {host?: string | undefined, httpHeaders?: Array<GoogleCloudAiplatformV1ProbeHttpHeader> | undefined, path?: string | undefined, port?: number | undefined, scheme?: string | undefined};

export type GoogleCloudAiplatformV1ProbeTcpSocketAction = {host?: string | undefined, port?: number | undefined};

export type GoogleCloudAiplatformV1Probe = {exec?: GoogleCloudAiplatformV1ProbeExecAction | undefined, failureThreshold?: number | undefined, grpc?: GoogleCloudAiplatformV1ProbeGrpcAction | undefined, httpGet?: GoogleCloudAiplatformV1ProbeHttpGetAction | undefined, initialDelaySeconds?: number | undefined, periodSeconds?: number | undefined, successThreshold?: number | undefined, tcpSocket?: GoogleCloudAiplatformV1ProbeTcpSocketAction | undefined, timeoutSeconds?: number | undefined};

export type GoogleCloudAiplatformV1ModelContainerSpec = {args?: Array<string> | undefined, command?: Array<string> | undefined, deploymentTimeout?: unknown | undefined, env?: Array<GoogleCloudAiplatformV1EnvVar> | undefined, grpcPorts?: Array<GoogleCloudAiplatformV1Port> | undefined, healthProbe?: GoogleCloudAiplatformV1Probe | undefined, healthRoute?: string | undefined, imageUri?: string | undefined, invokeRoutePrefix?: string | undefined, livenessProbe?: GoogleCloudAiplatformV1Probe | undefined, ports?: Array<GoogleCloudAiplatformV1Port> | undefined, predictRoute?: string | undefined, sharedMemorySizeMb?: unknown | undefined, startupProbe?: GoogleCloudAiplatformV1Probe | undefined};

export type GoogleCloudAiplatformV1ModelDataStats = {testAnnotationsCount?: unknown | undefined, testDataItemsCount?: unknown | undefined, trainingAnnotationsCount?: unknown | undefined, trainingDataItemsCount?: unknown | undefined, validationAnnotationsCount?: unknown | undefined, validationDataItemsCount?: unknown | undefined};

export type GoogleCloudAiplatformV1DeployedModelRef = {checkpointId?: string | undefined, deployedModelId?: string | undefined, endpoint?: string | undefined};

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

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain = {maxValue?: number | undefined, minValue?: number | undefined, originalMean?: number | undefined, originalStddev?: number | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization = {clipPercentLowerbound?: number | undefined, clipPercentUpperbound?: number | undefined, colorMap?: ('COLOR_MAP_UNSPECIFIED' | 'PINK_GREEN' | 'VIRIDIS' | 'RED' | 'GREEN' | 'RED_GREEN' | 'PINK_WHITE_GREEN') | undefined, overlayType?: ('OVERLAY_TYPE_UNSPECIFIED' | 'NONE' | 'ORIGINAL' | 'GRAYSCALE' | 'MASK_BLACK') | undefined, polarity?: ('POLARITY_UNSPECIFIED' | 'POSITIVE' | 'NEGATIVE' | 'BOTH') | undefined, type?: ('TYPE_UNSPECIFIED' | 'PIXELS' | 'OUTLINES') | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataInputMetadata = {denseShapeTensorName?: string | undefined, encodedBaselines?: Array<unknown> | undefined, encodedTensorName?: string | undefined, encoding?: ('ENCODING_UNSPECIFIED' | 'IDENTITY' | 'BAG_OF_FEATURES' | 'BAG_OF_FEATURES_SPARSE' | 'INDICATOR' | 'COMBINED_EMBEDDING' | 'CONCAT_EMBEDDING') | undefined, featureValueDomain?: GoogleCloudAiplatformV1ExplanationMetadataInputMetadataFeatureValueDomain | undefined, groupName?: string | undefined, indexFeatureMapping?: Array<string> | undefined, indicesTensorName?: string | undefined, inputBaselines?: Array<unknown> | undefined, inputTensorName?: string | undefined, modality?: string | undefined, visualization?: GoogleCloudAiplatformV1ExplanationMetadataInputMetadataVisualization | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata = {displayNameMappingKey?: string | undefined, indexDisplayNameMapping: unknown, outputTensorName?: string | undefined};

export type GoogleCloudAiplatformV1ExplanationMetadata = {featureAttributionsSchemaUri?: string | undefined, inputs?: {[key: string]: GoogleCloudAiplatformV1ExplanationMetadataInputMetadata} | undefined, latentSpaceSource?: string | undefined, outputs?: {[key: string]: GoogleCloudAiplatformV1ExplanationMetadataOutputMetadata} | undefined};

export type GoogleCloudAiplatformV1GcsSource = {uris?: Array<string> | undefined};

export type GoogleCloudAiplatformV1ExamplesExampleGcsSource = {dataFormat?: ('DATA_FORMAT_UNSPECIFIED' | 'JSONL') | undefined, gcsSource?: GoogleCloudAiplatformV1GcsSource | undefined};

export type GoogleCloudAiplatformV1Presets = {modality?: ('MODALITY_UNSPECIFIED' | 'IMAGE' | 'TEXT' | 'TABULAR') | undefined, query?: ('PRECISE' | 'FAST') | undefined};

export type GoogleCloudAiplatformV1Examples = {exampleGcsSource?: GoogleCloudAiplatformV1ExamplesExampleGcsSource | undefined, nearestNeighborSearchConfig: unknown, neighborCount?: number | undefined, presets?: GoogleCloudAiplatformV1Presets | undefined};

export type GoogleCloudAiplatformV1BlurBaselineConfig = {maxBlurSigma?: number | undefined};

export type GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature = {name?: string | undefined, sigma?: number | undefined};

export type GoogleCloudAiplatformV1FeatureNoiseSigma = {noiseSigma?: Array<GoogleCloudAiplatformV1FeatureNoiseSigmaNoiseSigmaForFeature> | undefined};

export type GoogleCloudAiplatformV1SmoothGradConfig = {featureNoiseSigma?: GoogleCloudAiplatformV1FeatureNoiseSigma | undefined, noiseSigma?: number | undefined, noisySampleCount?: number | undefined};

export type GoogleCloudAiplatformV1IntegratedGradientsAttribution = {blurBaselineConfig?: GoogleCloudAiplatformV1BlurBaselineConfig | undefined, smoothGradConfig?: GoogleCloudAiplatformV1SmoothGradConfig | undefined, stepCount?: number | undefined};

export type GoogleCloudAiplatformV1SampledShapleyAttribution = {pathCount?: number | undefined};

export type GoogleCloudAiplatformV1XraiAttribution = {blurBaselineConfig?: GoogleCloudAiplatformV1BlurBaselineConfig | undefined, smoothGradConfig?: GoogleCloudAiplatformV1SmoothGradConfig | undefined, stepCount?: number | undefined};

export type GoogleCloudAiplatformV1ExplanationParameters = {examples?: GoogleCloudAiplatformV1Examples | undefined, integratedGradientsAttribution?: GoogleCloudAiplatformV1IntegratedGradientsAttribution | undefined, outputIndices?: Array<unknown> | undefined, sampledShapleyAttribution?: GoogleCloudAiplatformV1SampledShapleyAttribution | undefined, topK?: number | undefined, xraiAttribution?: GoogleCloudAiplatformV1XraiAttribution | undefined};

export type GoogleCloudAiplatformV1ExplanationSpec = {metadata?: GoogleCloudAiplatformV1ExplanationMetadata | undefined, parameters?: GoogleCloudAiplatformV1ExplanationParameters | undefined};

export type GoogleCloudAiplatformV1ModelSourceInfo = {copy?: boolean | undefined, sourceType?: ('MODEL_SOURCE_TYPE_UNSPECIFIED' | 'AUTOML' | 'CUSTOM' | 'BQML' | 'MODEL_GARDEN' | 'GENIE' | 'CUSTOM_TEXT_EMBEDDING' | 'MARKETPLACE') | undefined};

export type GoogleCloudAiplatformV1ModelOriginalModelInfo = {model?: string | undefined};

export type GoogleCloudAiplatformV1PredictSchemata = {instanceSchemaUri?: string | undefined, parametersSchemaUri?: string | undefined, predictionSchemaUri?: string | undefined};

export type GoogleCloudAiplatformV1ModelExportFormat = {exportableContents?: (Array<'EXPORTABLE_CONTENT_UNSPECIFIED' | 'ARTIFACT' | 'IMAGE'>) | undefined, id?: string | undefined};

export type GoogleCloudAiplatformV1Model = {artifactUri?: string | undefined, baseModelSource?: GoogleCloudAiplatformV1ModelBaseModelSource | undefined, checkpoints?: Array<GoogleCloudAiplatformV1Checkpoint> | undefined, containerSpec?: GoogleCloudAiplatformV1ModelContainerSpec | undefined, createTime?: unknown | undefined, dataStats?: GoogleCloudAiplatformV1ModelDataStats | undefined, defaultCheckpointId?: string | undefined, deployedModels?: Array<GoogleCloudAiplatformV1DeployedModelRef> | undefined, description?: string | undefined, displayName?: string | undefined, encryptionSpec?: GoogleCloudAiplatformV1EncryptionSpec | undefined, etag?: string | undefined, explanationSpec?: GoogleCloudAiplatformV1ExplanationSpec | undefined, labels?: {[key: string]: string} | undefined, metadata: unknown, metadataArtifact?: string | undefined, metadataSchemaUri?: string | undefined, modelSourceInfo?: GoogleCloudAiplatformV1ModelSourceInfo | undefined, name?: string | undefined, originalModelInfo?: GoogleCloudAiplatformV1ModelOriginalModelInfo | undefined, pipelineJob?: string | undefined, predictSchemata?: GoogleCloudAiplatformV1PredictSchemata | undefined, satisfiesPzi?: boolean | undefined, satisfiesPzs?: boolean | undefined, supportedDeploymentResourcesTypes?: (Array<'DEPLOYMENT_RESOURCES_TYPE_UNSPECIFIED' | 'DEDICATED_RESOURCES' | 'AUTOMATIC_RESOURCES' | 'SHARED_RESOURCES'>) | undefined, supportedExportFormats?: Array<GoogleCloudAiplatformV1ModelExportFormat> | undefined, supportedInputStorageFormats?: Array<string> | undefined, supportedOutputStorageFormats?: Array<string> | undefined, trainingPipeline?: string | undefined, updateTime?: unknown | undefined, versionAliases?: Array<string> | undefined, versionCreateTime?: unknown | undefined, versionDescription?: string | undefined, versionId?: string | undefined, versionUpdateTime?: unknown | undefined};

export type GoogleCloudAiplatformV1UploadModelRequest = {model?: GoogleCloudAiplatformV1Model | undefined, modelId?: string | undefined, parentModel?: string | undefined, serviceAccount?: string | undefined};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdModelsUploadArgs = {projectsId: string, locationsId: string, body: GoogleCloudAiplatformV1UploadModelRequest};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdModelsUploadOptions = {baseUrl?: string | undefined, Oauth2?: string | undefined, Oauth2c?: string | undefined, fetch?: typeof fetch | undefined};

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 googleLongrunningOperation = z.object({done: z.boolean().optional(), error: googleRpcStatus.optional(), metadata: z.record(z.string(), z.unknown()).optional(), name: z.string().optional(), response: z.record(z.string(), z.unknown()).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
};

/**
 * Uploads a Model artifact into Vertex AI.
 * 
 * POST /v1/projects/{projectsId}/locations/{locationsId}/models:upload
 * 
 * Also accepts auth: Oauth2 + Oauth2c
 */
export const createApiV1ProjectsProjectsIdLocationsLocationsIdModelsUpload = async (args: CreateApiV1ProjectsProjectsIdLocationsLocationsIdModelsUploadArgs, options?: CreateApiV1ProjectsProjectsIdLocationsLocationsIdModelsUploadOptions) => {
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))}/models:upload${query.size > 0 ? `?${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(googleLongrunningOperation, await res.json())
};