import {z} from 'zod'

export type GoogleCloudAiplatformV1AutoscalingMetricSpec = {metricName?: string | undefined, target?: number | undefined};

export type GoogleCloudAiplatformV1ReservationAffinity = {key?: string | undefined, reservationAffinityType?: ('TYPE_UNSPECIFIED' | 'NO_RESERVATION' | 'ANY_RESERVATION' | 'SPECIFIC_RESERVATION') | undefined, values?: Array<string> | undefined};

export type GoogleCloudAiplatformV1MachineSpec = {acceleratorCount?: number | undefined, acceleratorType?: ('ACCELERATOR_TYPE_UNSPECIFIED' | 'NVIDIA_TESLA_K80' | 'NVIDIA_TESLA_P100' | 'NVIDIA_TESLA_V100' | 'NVIDIA_TESLA_P4' | 'NVIDIA_TESLA_T4' | 'NVIDIA_TESLA_A100' | 'NVIDIA_A100_80GB' | 'NVIDIA_L4' | 'NVIDIA_H100_80GB' | 'NVIDIA_H100_MEGA_80GB' | 'NVIDIA_H200_141GB' | 'NVIDIA_B200' | 'NVIDIA_GB200' | 'NVIDIA_RTX_PRO_6000' | 'TPU_V2' | 'TPU_V3' | 'TPU_V4_POD' | 'TPU_V5_LITEPOD') | undefined, gpuPartitionSize?: string | undefined, machineType?: string | undefined, reservationAffinity?: GoogleCloudAiplatformV1ReservationAffinity | undefined, tpuTopology?: string | undefined};

export type GoogleCloudAiplatformV1DedicatedResources = {autoscalingMetricSpecs?: Array<GoogleCloudAiplatformV1AutoscalingMetricSpec> | undefined, machineSpec?: GoogleCloudAiplatformV1MachineSpec | undefined, maxReplicaCount?: number | undefined, minReplicaCount?: number | undefined, requiredReplicaCount?: number | undefined, spot?: boolean | undefined};

export type GoogleCloudAiplatformV1DeployRequestDeployConfig = {dedicatedResources?: GoogleCloudAiplatformV1DedicatedResources | undefined, fastTryoutEnabled?: boolean | undefined, systemLabels?: {[key: string]: string} | undefined};

export type GoogleCloudAiplatformV1PSCAutomationConfig = {errorMessage?: string | undefined, forwardingRule?: string | undefined, ipAddress?: string | undefined, network?: string | undefined, projectId?: string | undefined, state?: ('PSC_AUTOMATION_STATE_UNSPECIFIED' | 'PSC_AUTOMATION_STATE_SUCCESSFUL' | 'PSC_AUTOMATION_STATE_FAILED') | undefined};

export type GoogleCloudAiplatformV1PrivateServiceConnectConfig = {enablePrivateServiceConnect?: boolean | undefined, projectAllowlist?: Array<string> | undefined, pscAutomationConfigs?: Array<GoogleCloudAiplatformV1PSCAutomationConfig> | undefined, serviceAttachment?: string | undefined};

export type GoogleCloudAiplatformV1DeployRequestEndpointConfig = {dedicatedEndpointDisabled?: boolean | undefined, dedicatedEndpointEnabled?: boolean | undefined, endpointDisplayName?: string | undefined, endpointUserId?: string | undefined, labels?: {[key: string]: string} | undefined, privateServiceConnectConfig?: GoogleCloudAiplatformV1PrivateServiceConnectConfig | 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 GoogleCloudAiplatformV1DeployRequestModelConfig = {acceptEula?: boolean | undefined, containerSpec?: GoogleCloudAiplatformV1ModelContainerSpec | undefined, huggingFaceAccessToken?: string | undefined, huggingFaceCacheEnabled?: boolean | undefined, modelDisplayName?: string | undefined, modelUserId?: string | undefined};

export type GoogleCloudAiplatformV1DeployRequest = {deployConfig?: GoogleCloudAiplatformV1DeployRequestDeployConfig | undefined, endpointConfig?: GoogleCloudAiplatformV1DeployRequestEndpointConfig | undefined, huggingFaceModelId?: string | undefined, modelConfig?: GoogleCloudAiplatformV1DeployRequestModelConfig | undefined, publisherModelName?: string | undefined};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdDeployArgs = {projectsId: string, locationsId: string, body: GoogleCloudAiplatformV1DeployRequest};

export type CreateApiV1ProjectsProjectsIdLocationsLocationsIdDeployOptions = {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
};

/**
 * Deploys a model to a new endpoint.
 * 
 * POST /v1/projects/{projectsId}/locations/{locationsId}:deploy
 * 
 * Also accepts auth: Oauth2 + Oauth2c
 */
export const createApiV1ProjectsProjectsIdLocationsLocationsIdDeploy = async (args: CreateApiV1ProjectsProjectsIdLocationsLocationsIdDeployArgs, options?: CreateApiV1ProjectsProjectsIdLocationsLocationsIdDeployOptions) => {
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))}:deploy${query.size > 0 ? `?${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())
};