import * as pulumi from "@pulumi/pulumi";
import * as inputs from "../types/input";
import * as outputs from "../types/output";
/**
 * Create an Endpoint and deploy a Model Garden model to it.
 *
 * To get more information about EndpointWithModelGardenDeployment, see:
 *
 * * [API documentation](https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations/deploy)
 * * How-to Guides
 *     * [Overview of Model Garden](https://cloud.google.com/vertex-ai/generative-ai/docs/model-garden/explore-models)
 *     * [Overview of self-deployed models](https://cloud.google.com/vertex-ai/generative-ai/docs/model-garden/self-deployed-models)
 *     * [Use models in Model Garden](https://cloud.google.com/vertex-ai/generative-ai/docs/model-garden/use-models)
 *
 * ## Example Usage
 *
 * ### Vertex Ai Deploy Basic
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy", {
 *     publisherModelName: "publishers/google/models/paligemma@paligemma-224-float32",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 * });
 * ```
 * ### Vertex Ai Deploy Huggingface Model
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy", {
 *     huggingFaceModelId: "Qwen/Qwen3-0.6B",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 * });
 * ```
 * ### Vertex Ai Deploy With Configs
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy", {
 *     publisherModelName: "publishers/google/models/paligemma@paligemma-224-float32",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-16",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * });
 * ```
 * ### Vertex Ai Deploy Multiple Models In Parallel
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy_gemma_11_2b_it = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-gemma-1_1-2b-it", {
 *     publisherModelName: "publishers/google/models/gemma@gemma-1.1-2b-it",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "us-central1",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * });
 * const deploy_qwen3_06b = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-qwen3-0_6b", {
 *     huggingFaceModelId: "Qwen/Qwen3-0.6B",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * });
 * const deploy_llama_32_1b = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-llama-3_2-1b", {
 *     publisherModelName: "publishers/meta/models/llama3-2@llama-3.2-1b",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * });
 * ```
 * ### Vertex Ai Deploy Multiple Models In Sequence
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy_gemma_11_2b_it = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-gemma-1_1-2b-it", {
 *     publisherModelName: "publishers/google/models/gemma@gemma-1.1-2b-it",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * });
 * const deploy_qwen3_06b = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-qwen3-0_6b", {
 *     huggingFaceModelId: "Qwen/Qwen3-0.6B",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * }, {
 *     dependsOn: [deploy_gemma_11_2b_it],
 * });
 * const deploy_llama_32_1b = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy-llama-3_2-1b", {
 *     publisherModelName: "publishers/meta/models/llama3-2@llama-3.2-1b",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     deployConfig: {
 *         dedicatedResources: {
 *             machineSpec: {
 *                 machineType: "g2-standard-12",
 *                 acceleratorType: "NVIDIA_L4",
 *                 acceleratorCount: 1,
 *             },
 *             minReplicaCount: 1,
 *         },
 *     },
 * }, {
 *     dependsOn: [deploy_qwen3_06b],
 * });
 * ```
 * ### Vertex Ai Deploy Psc Endpoint
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const deploy = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy", {
 *     publisherModelName: "publishers/google/models/paligemma@paligemma-224-float32",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     endpointConfig: {
 *         privateServiceConnectConfig: {
 *             enablePrivateServiceConnect: true,
 *             projectAllowlists: ["my-project-id"],
 *         },
 *     },
 * });
 * ```
 * ### Vertex Ai Deploy Psc Endpoint Automated
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as gcp from "@pulumi/gcp";
 *
 * const network = new gcp.compute.Network("network", {
 *     name: "network",
 *     autoCreateSubnetworks: false,
 * });
 * const project = gcp.organizations.getProject({});
 * const deploy = new gcp.vertex.AiEndpointWithModelGardenDeployment("deploy", {
 *     publisherModelName: "publishers/google/models/paligemma@paligemma-224-float32",
 *     location: "us-central1",
 *     modelConfig: {
 *         acceptEula: true,
 *     },
 *     endpointConfig: {
 *         privateServiceConnectConfig: {
 *             enablePrivateServiceConnect: true,
 *             projectAllowlists: [project.then(project => project.id)],
 *             pscAutomationConfigs: {
 *                 projectId: project.then(project => project.id),
 *                 network: network.id,
 *             },
 *         },
 *     },
 * });
 * const subnetwork = new gcp.compute.Subnetwork("subnetwork", {
 *     name: "subnetwork",
 *     ipCidrRange: "192.168.0.0/24",
 *     region: "us-central1",
 *     network: network.id,
 * });
 * ```
 *
 * ## Import
 *
 * This resource does not support import.
 */
export declare class AiEndpointWithModelGardenDeployment extends pulumi.CustomResource {
    /**
     * Get an existing AiEndpointWithModelGardenDeployment resource's state with the given name, ID, and optional extra
     * properties used to qualify the lookup.
     *
     * @param name The _unique_ name of the resulting resource.
     * @param id The _unique_ provider ID of the resource to lookup.
     * @param state Any extra arguments used during the lookup.
     * @param opts Optional settings to control the behavior of the CustomResource.
     */
    static get(name: string, id: pulumi.Input<pulumi.ID>, state?: AiEndpointWithModelGardenDeploymentState, opts?: pulumi.CustomResourceOptions): AiEndpointWithModelGardenDeployment;
    /**
     * Returns true if the given object is an instance of AiEndpointWithModelGardenDeployment.  This is designed to work even
     * when multiple copies of the Pulumi SDK have been loaded into the same process.
     */
    static isInstance(obj: any): obj is AiEndpointWithModelGardenDeployment;
    /**
     * Whether Terraform will be prevented from destroying the resource. Defaults to DELETE.
     * When a 'terraform destroy' or 'pulumi up' would delete the resource,
     * the command will fail if this field is set to "PREVENT" in Terraform state.
     * When set to "ABANDON", the command will remove the resource from Terraform
     * management without updating or deleting the resource in the API.
     * When set to "DELETE", deleting the resource is allowed.
     */
    readonly deletionPolicy: pulumi.Output<string>;
    /**
     * The deploy config to use for the deployment.
     * Structure is documented below.
     */
    readonly deployConfig: pulumi.Output<outputs.vertex.AiEndpointWithModelGardenDeploymentDeployConfig | undefined>;
    /**
     * Output only. The display name assigned to the model deployed to the endpoint.
     * This is not required to delete the resource but is used for debug logging.
     */
    readonly deployedModelDisplayName: pulumi.Output<string>;
    /**
     * Output only. The unique numeric ID that Vertex AI assigns to the model at the time it is deployed to the endpoint.
     * It is required to undeploy the model from the endpoint during resource deletion as described in
     * https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints/undeployModel.
     */
    readonly deployedModelId: pulumi.Output<string>;
    /**
     * Resource ID segment making up resource `endpoint`. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
     */
    readonly endpoint: pulumi.Output<string>;
    /**
     * The endpoint config to use for the deployment.
     * Structure is documented below.
     */
    readonly endpointConfig: pulumi.Output<outputs.vertex.AiEndpointWithModelGardenDeploymentEndpointConfig | undefined>;
    /**
     * The Hugging Face model to deploy.
     * Format: Hugging Face model ID like `google/gemma-2-2b-it`.
     */
    readonly huggingFaceModelId: pulumi.Output<string | undefined>;
    /**
     * Resource ID segment making up resource `location`. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
     */
    readonly location: pulumi.Output<string>;
    /**
     * The model config to use for the deployment.
     * Structure is documented below.
     */
    readonly modelConfig: pulumi.Output<outputs.vertex.AiEndpointWithModelGardenDeploymentModelConfig | undefined>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    readonly project: pulumi.Output<string>;
    /**
     * The Model Garden model to deploy.
     * Format:
     * `publishers/{publisher}/models/{publisher_model}@{version_id}`, or
     * `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`.
     */
    readonly publisherModelName: pulumi.Output<string | undefined>;
    /**
     * Create a AiEndpointWithModelGardenDeployment resource with the given unique name, arguments, and options.
     *
     * @param name The _unique_ name of the resource.
     * @param args The arguments to use to populate this resource's properties.
     * @param opts A bag of options that control this resource's behavior.
     */
    constructor(name: string, args: AiEndpointWithModelGardenDeploymentArgs, opts?: pulumi.CustomResourceOptions);
}
/**
 * Input properties used for looking up and filtering AiEndpointWithModelGardenDeployment resources.
 */
export interface AiEndpointWithModelGardenDeploymentState {
    /**
     * Whether Terraform will be prevented from destroying the resource. Defaults to DELETE.
     * When a 'terraform destroy' or 'pulumi up' would delete the resource,
     * the command will fail if this field is set to "PREVENT" in Terraform state.
     * When set to "ABANDON", the command will remove the resource from Terraform
     * management without updating or deleting the resource in the API.
     * When set to "DELETE", deleting the resource is allowed.
     */
    deletionPolicy?: pulumi.Input<string | undefined>;
    /**
     * The deploy config to use for the deployment.
     * Structure is documented below.
     */
    deployConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentDeployConfig | undefined>;
    /**
     * Output only. The display name assigned to the model deployed to the endpoint.
     * This is not required to delete the resource but is used for debug logging.
     */
    deployedModelDisplayName?: pulumi.Input<string | undefined>;
    /**
     * Output only. The unique numeric ID that Vertex AI assigns to the model at the time it is deployed to the endpoint.
     * It is required to undeploy the model from the endpoint during resource deletion as described in
     * https://cloud.google.com/vertex-ai/docs/reference/rest/v1/projects.locations.endpoints/undeployModel.
     */
    deployedModelId?: pulumi.Input<string | undefined>;
    /**
     * Resource ID segment making up resource `endpoint`. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
     */
    endpoint?: pulumi.Input<string | undefined>;
    /**
     * The endpoint config to use for the deployment.
     * Structure is documented below.
     */
    endpointConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentEndpointConfig | undefined>;
    /**
     * The Hugging Face model to deploy.
     * Format: Hugging Face model ID like `google/gemma-2-2b-it`.
     */
    huggingFaceModelId?: pulumi.Input<string | undefined>;
    /**
     * Resource ID segment making up resource `location`. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
     */
    location?: pulumi.Input<string | undefined>;
    /**
     * The model config to use for the deployment.
     * Structure is documented below.
     */
    modelConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentModelConfig | undefined>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    project?: pulumi.Input<string | undefined>;
    /**
     * The Model Garden model to deploy.
     * Format:
     * `publishers/{publisher}/models/{publisher_model}@{version_id}`, or
     * `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`.
     */
    publisherModelName?: pulumi.Input<string | undefined>;
}
/**
 * The set of arguments for constructing a AiEndpointWithModelGardenDeployment resource.
 */
export interface AiEndpointWithModelGardenDeploymentArgs {
    /**
     * Whether Terraform will be prevented from destroying the resource. Defaults to DELETE.
     * When a 'terraform destroy' or 'pulumi up' would delete the resource,
     * the command will fail if this field is set to "PREVENT" in Terraform state.
     * When set to "ABANDON", the command will remove the resource from Terraform
     * management without updating or deleting the resource in the API.
     * When set to "DELETE", deleting the resource is allowed.
     */
    deletionPolicy?: pulumi.Input<string | undefined>;
    /**
     * The deploy config to use for the deployment.
     * Structure is documented below.
     */
    deployConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentDeployConfig | undefined>;
    /**
     * The endpoint config to use for the deployment.
     * Structure is documented below.
     */
    endpointConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentEndpointConfig | undefined>;
    /**
     * The Hugging Face model to deploy.
     * Format: Hugging Face model ID like `google/gemma-2-2b-it`.
     */
    huggingFaceModelId?: pulumi.Input<string | undefined>;
    /**
     * Resource ID segment making up resource `location`. It identifies the resource within its parent collection as described in https://google.aip.dev/122.
     */
    location: pulumi.Input<string>;
    /**
     * The model config to use for the deployment.
     * Structure is documented below.
     */
    modelConfig?: pulumi.Input<inputs.vertex.AiEndpointWithModelGardenDeploymentModelConfig | undefined>;
    /**
     * The ID of the project in which the resource belongs.
     * If it is not provided, the provider project is used.
     */
    project?: pulumi.Input<string | undefined>;
    /**
     * The Model Garden model to deploy.
     * Format:
     * `publishers/{publisher}/models/{publisher_model}@{version_id}`, or
     * `publishers/hf-{hugging-face-author}/models/{hugging-face-model-name}@001`.
     */
    publisherModelName?: pulumi.Input<string | undefined>;
}
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