import * as pulumi from "@pulumi/pulumi";
import * as inputs from "./types/input";
import * as outputs from "./types/output";
/**
 * > **Note** If you have a fully automated setup with workspaces created by databricks.MwsWorkspaces or azurerm_databricks_workspace, please make sure to add dependsOn attribute in order to prevent _default auth: cannot configure default credentials_ errors.
 *
 * Retrieves the settings of databricks.MlflowModel by name.
 *
 * ## Example Usage
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as databricks from "@pulumi/databricks";
 *
 * const thisMlflowModel = new databricks.MlflowModel("this", {
 *     name: "My MLflow Model",
 *     description: "My MLflow model description",
 *     tags: [
 *         {
 *             key: "key1",
 *             value: "value1",
 *         },
 *         {
 *             key: "key2",
 *             value: "value2",
 *         },
 *     ],
 * });
 * const _this = databricks.getMlflowModel({
 *     name: "My MLflow Model",
 * });
 * export const model = _this;
 * ```
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as databricks from "@pulumi/databricks";
 *
 * const _this = databricks.getMlflowModel({
 *     name: "My MLflow Model with multiple versions",
 * });
 * const thisModelServing = new databricks.ModelServing("this", {
 *     name: "model-serving-endpoint",
 *     config: {
 *         servedModels: [{
 *             name: "model_serving_prod",
 *             modelName: _this.then(_this => _this.name),
 *             modelVersion: _this.then(_this => _this.latestVersions?.[0]?.version),
 *             workloadSize: "Small",
 *             scaleToZeroEnabled: true,
 *         }],
 *     },
 * });
 * ```
 */
export declare function getMlflowModel(args: GetMlflowModelArgs, opts?: pulumi.InvokeOptions): Promise<GetMlflowModelResult>;
/**
 * A collection of arguments for invoking getMlflowModel.
 */
export interface GetMlflowModelArgs {
    /**
     * User-specified description for the object.
     */
    description?: string;
    /**
     * Array of model versions, each the latest version for its stage.
     */
    latestVersions?: inputs.GetMlflowModelLatestVersion[];
    /**
     * Name of the registered model.
     */
    name: string;
    /**
     * Permission level of the requesting user on the object. For what is allowed at each level, see MLflow Model permissions.
     */
    permissionLevel?: string;
    /**
     * Array of tags associated with the model.
     */
    tags?: inputs.GetMlflowModelTag[];
    /**
     * The username of the user that created the object.
     */
    userId?: string;
}
/**
 * A collection of values returned by getMlflowModel.
 */
export interface GetMlflowModelResult {
    /**
     * User-specified description for the object.
     */
    readonly description: string;
    /**
     * Unique identifier for the object.
     */
    readonly id: string;
    /**
     * Array of model versions, each the latest version for its stage.
     */
    readonly latestVersions: outputs.GetMlflowModelLatestVersion[];
    /**
     * Name of the model.
     */
    readonly name: string;
    /**
     * Permission level of the requesting user on the object. For what is allowed at each level, see MLflow Model permissions.
     */
    readonly permissionLevel: string;
    /**
     * Array of tags associated with the model.
     */
    readonly tags: outputs.GetMlflowModelTag[];
    /**
     * The username of the user that created the object.
     */
    readonly userId: string;
}
/**
 * > **Note** If you have a fully automated setup with workspaces created by databricks.MwsWorkspaces or azurerm_databricks_workspace, please make sure to add dependsOn attribute in order to prevent _default auth: cannot configure default credentials_ errors.
 *
 * Retrieves the settings of databricks.MlflowModel by name.
 *
 * ## Example Usage
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as databricks from "@pulumi/databricks";
 *
 * const thisMlflowModel = new databricks.MlflowModel("this", {
 *     name: "My MLflow Model",
 *     description: "My MLflow model description",
 *     tags: [
 *         {
 *             key: "key1",
 *             value: "value1",
 *         },
 *         {
 *             key: "key2",
 *             value: "value2",
 *         },
 *     ],
 * });
 * const _this = databricks.getMlflowModel({
 *     name: "My MLflow Model",
 * });
 * export const model = _this;
 * ```
 *
 * ```typescript
 * import * as pulumi from "@pulumi/pulumi";
 * import * as databricks from "@pulumi/databricks";
 *
 * const _this = databricks.getMlflowModel({
 *     name: "My MLflow Model with multiple versions",
 * });
 * const thisModelServing = new databricks.ModelServing("this", {
 *     name: "model-serving-endpoint",
 *     config: {
 *         servedModels: [{
 *             name: "model_serving_prod",
 *             modelName: _this.then(_this => _this.name),
 *             modelVersion: _this.then(_this => _this.latestVersions?.[0]?.version),
 *             workloadSize: "Small",
 *             scaleToZeroEnabled: true,
 *         }],
 *     },
 * });
 * ```
 */
export declare function getMlflowModelOutput(args: GetMlflowModelOutputArgs, opts?: pulumi.InvokeOutputOptions): pulumi.Output<GetMlflowModelResult>;
/**
 * A collection of arguments for invoking getMlflowModel.
 */
export interface GetMlflowModelOutputArgs {
    /**
     * User-specified description for the object.
     */
    description?: pulumi.Input<string>;
    /**
     * Array of model versions, each the latest version for its stage.
     */
    latestVersions?: pulumi.Input<pulumi.Input<inputs.GetMlflowModelLatestVersionArgs>[]>;
    /**
     * Name of the registered model.
     */
    name: pulumi.Input<string>;
    /**
     * Permission level of the requesting user on the object. For what is allowed at each level, see MLflow Model permissions.
     */
    permissionLevel?: pulumi.Input<string>;
    /**
     * Array of tags associated with the model.
     */
    tags?: pulumi.Input<pulumi.Input<inputs.GetMlflowModelTagArgs>[]>;
    /**
     * The username of the user that created the object.
     */
    userId?: pulumi.Input<string>;
}