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DataRobot v0.4.5 published on Monday, Nov 18, 2024 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.CustomModel

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DataRobot v0.4.5 published on Monday, Nov 18, 2024 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

    Data set from file

    Example Usage

    import * as pulumi from "@pulumi/pulumi";
import * as datarobot from "@datarobot/pulumi-datarobot";

const exampleRemoteRepository = new datarobot.RemoteRepository("exampleRemoteRepository", {
    description: "GitHub repository with Datarobot user models",
    location: "https://github.com/datarobot/datarobot-user-models",
    sourceType: "github",
});
// set the credential id for private repositories
// credential_id = datarobot_api_token_credential.example.id
const exampleCustomModel = new datarobot.CustomModel("exampleCustomModel", {
    description: "An example custom model from GitHub repository",
    files: [
        "file1.py",
        "file2.py",
    ],
    targetType: "Binary",
    targetName: "my_label",
    baseEnvironmentId: "65f9b27eab986d30d4c64268",
});
// Optional
// source_remote_repositories = [
//   {
//     id  = datarobot_remote_repository.example.id
//     ref = "master"
//     source_paths = [
//       "model_templates/python3_dummy_binary",
//     ]
//   }
// ]
// guard_configurations = [
//   {
//     template_name = "Rouge 1"
//     name          = "Rouge 1 response"
//     stages        = ["response"]
//     intervention = {
//       action  = "block"
//       message = "response has been blocked by Rogue 1 guard"
//       condition = jsonencode({
//         "comparand": 0.5, 
//         "comparator": "greaterThan"
//       })
//     }
//   },
// ]
// overall_moderation_configuration = {
//   timeout_sec    = 120
//   timeout_action = "score"
// }
// memory_mb      = 512
// replicas       = 2
// network_access = "NONE"
export const exampleId = exampleCustomModel.id;

    import pulumi
import pulumi_datarobot as datarobot

example_remote_repository = datarobot.RemoteRepository("exampleRemoteRepository",
    description="GitHub repository with Datarobot user models",
    location="https://github.com/datarobot/datarobot-user-models",
    source_type="github")
# set the credential id for private repositories
# credential_id = datarobot_api_token_credential.example.id
example_custom_model = datarobot.CustomModel("exampleCustomModel",
    description="An example custom model from GitHub repository",
    files=[
        "file1.py",
        "file2.py",
    ],
    target_type="Binary",
    target_name="my_label",
    base_environment_id="65f9b27eab986d30d4c64268")
# Optional
# source_remote_repositories = [
#   {
#     id  = datarobot_remote_repository.example.id
#     ref = "master"
#     source_paths = [
#       "model_templates/python3_dummy_binary",
#     ]
#   }
# ]
# guard_configurations = [
#   {
#     template_name = "Rouge 1"
#     name          = "Rouge 1 response"
#     stages        = ["response"]
#     intervention = {
#       action  = "block"
#       message = "response has been blocked by Rogue 1 guard"
#       condition = jsonencode({
#         "comparand": 0.5, 
#         "comparator": "greaterThan"
#       })
#     }
#   },
# ]
# overall_moderation_configuration = {
#   timeout_sec    = 120
#   timeout_action = "score"
# }
# memory_mb      = 512
# replicas       = 2
# network_access = "NONE"
pulumi.export("exampleId", example_custom_model.id)

    package main

import (
	"github.com/datarobot-community/pulumi-datarobot/sdk/go/datarobot"
	"github.com/pulumi/pulumi/sdk/v3/go/pulumi"
)

func main() {
	pulumi.Run(func(ctx *pulumi.Context) error {
		_, err := datarobot.NewRemoteRepository(ctx, "exampleRemoteRepository", &datarobot.RemoteRepositoryArgs{
			Description: pulumi.String("GitHub repository with Datarobot user models"),
			Location:    pulumi.String("https://github.com/datarobot/datarobot-user-models"),
			SourceType:  pulumi.String("github"),
		})
		if err != nil {
			return err
		}
		exampleCustomModel, err := datarobot.NewCustomModel(ctx, "exampleCustomModel", &datarobot.CustomModelArgs{
			Description: pulumi.String("An example custom model from GitHub repository"),
			Files: pulumi.Any{
				"file1.py",
				"file2.py",
			},
			TargetType:        pulumi.String("Binary"),
			TargetName:        pulumi.String("my_label"),
			BaseEnvironmentId: pulumi.String("65f9b27eab986d30d4c64268"),
		})
		if err != nil {
			return err
		}
		ctx.Export("exampleId", exampleCustomModel.ID())
		return nil
	})
}

    using System.Collections.Generic;
using System.Linq;
using Pulumi;
using Datarobot = DataRobotPulumi.Datarobot;

return await Deployment.RunAsync(() => 
{
    var exampleRemoteRepository = new Datarobot.RemoteRepository("exampleRemoteRepository", new()
    {
        Description = "GitHub repository with Datarobot user models",
        Location = "https://github.com/datarobot/datarobot-user-models",
        SourceType = "github",
    });

    // set the credential id for private repositories
    // credential_id = datarobot_api_token_credential.example.id
    var exampleCustomModel = new Datarobot.CustomModel("exampleCustomModel", new()
    {
        Description = "An example custom model from GitHub repository",
        Files = new[]
        {
            "file1.py",
            "file2.py",
        },
        TargetType = "Binary",
        TargetName = "my_label",
        BaseEnvironmentId = "65f9b27eab986d30d4c64268",
    });

    // Optional
    // source_remote_repositories = [
    //   {
    //     id  = datarobot_remote_repository.example.id
    //     ref = "master"
    //     source_paths = [
    //       "model_templates/python3_dummy_binary",
    //     ]
    //   }
    // ]
    // guard_configurations = [
    //   {
    //     template_name = "Rouge 1"
    //     name          = "Rouge 1 response"
    //     stages        = ["response"]
    //     intervention = {
    //       action  = "block"
    //       message = "response has been blocked by Rogue 1 guard"
    //       condition = jsonencode({
    //         "comparand": 0.5, 
    //         "comparator": "greaterThan"
    //       })
    //     }
    //   },
    // ]
    // overall_moderation_configuration = {
    //   timeout_sec    = 120
    //   timeout_action = "score"
    // }
    // memory_mb      = 512
    // replicas       = 2
    // network_access = "NONE"
    return new Dictionary<string, object?>
    {
        ["exampleId"] = exampleCustomModel.Id,
    };
});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.RemoteRepository;
import com.pulumi.datarobot.RemoteRepositoryArgs;
import com.pulumi.datarobot.CustomModel;
import com.pulumi.datarobot.CustomModelArgs;
import java.util.List;
import java.util.ArrayList;
import java.util.Map;
import java.io.File;
import java.nio.file.Files;
import java.nio.file.Paths;

public class App {
    public static void main(String[] args) {
        Pulumi.run(App::stack);
    }

    public static void stack(Context ctx) {
        var exampleRemoteRepository = new RemoteRepository("exampleRemoteRepository", RemoteRepositoryArgs.builder()
            .description("GitHub repository with Datarobot user models")
            .location("https://github.com/datarobot/datarobot-user-models")
            .sourceType("github")
            .build());

        // set the credential id for private repositories
        // credential_id = datarobot_api_token_credential.example.id
        var exampleCustomModel = new CustomModel("exampleCustomModel", CustomModelArgs.builder()
            .description("An example custom model from GitHub repository")
            .files(            
                "file1.py",
                "file2.py")
            .targetType("Binary")
            .targetName("my_label")
            .baseEnvironmentId("65f9b27eab986d30d4c64268")
            .build());

        // Optional
        // source_remote_repositories = [
        //   {
        //     id  = datarobot_remote_repository.example.id
        //     ref = "master"
        //     source_paths = [
        //       "model_templates/python3_dummy_binary",
        //     ]
        //   }
        // ]
        // guard_configurations = [
        //   {
        //     template_name = "Rouge 1"
        //     name          = "Rouge 1 response"
        //     stages        = ["response"]
        //     intervention = {
        //       action  = "block"
        //       message = "response has been blocked by Rogue 1 guard"
        //       condition = jsonencode({
        //         "comparand": 0.5, 
        //         "comparator": "greaterThan"
        //       })
        //     }
        //   },
        // ]
        // overall_moderation_configuration = {
        //   timeout_sec    = 120
        //   timeout_action = "score"
        // }
        // memory_mb      = 512
        // replicas       = 2
        // network_access = "NONE"
        ctx.export("exampleId", exampleCustomModel.id());
    }
}

    resources:
  exampleRemoteRepository:
    type: datarobot:RemoteRepository
    properties:
      description: GitHub repository with Datarobot user models
      location: https://github.com/datarobot/datarobot-user-models
      sourceType: github
  exampleCustomModel:
    type: datarobot:CustomModel
    properties:
      description: An example custom model from GitHub repository
      files:
        - file1.py
        - file2.py
      targetType: Binary
      targetName: my_label
      baseEnvironmentId: 65f9b27eab986d30d4c64268
outputs:
  exampleId: ${exampleCustomModel.id}

    Create CustomModel Resource

    Resources are created with functions called constructors. To learn more about declaring and configuring resources, see Resources.

    Constructor syntax

    new CustomModel(name: string, args?: CustomModelArgs, opts?: CustomResourceOptions);
    @overload
def CustomModel(resource_name: str,
                args: Optional[CustomModelArgs] = None,
                opts: Optional[ResourceOptions] = None)

@overload
def CustomModel(resource_name: str,
                opts: Optional[ResourceOptions] = None,
                base_environment_id: Optional[str] = None,
                base_environment_version_id: Optional[str] = None,
                class_labels: Optional[Sequence[str]] = None,
                class_labels_file: Optional[str] = None,
                description: Optional[str] = None,
                files: Optional[Any] = None,
                folder_path: Optional[str] = None,
                guard_configurations: Optional[Sequence[CustomModelGuardConfigurationArgs]] = None,
                is_proxy: Optional[bool] = None,
                language: Optional[str] = None,
                memory_mb: Optional[int] = None,
                name: Optional[str] = None,
                negative_class_label: Optional[str] = None,
                network_access: Optional[str] = None,
                overall_moderation_configuration: Optional[CustomModelOverallModerationConfigurationArgs] = None,
                positive_class_label: Optional[str] = None,
                prediction_threshold: Optional[float] = None,
                replicas: Optional[int] = None,
                resource_bundle_id: Optional[str] = None,
                runtime_parameter_values: Optional[Sequence[CustomModelRuntimeParameterValueArgs]] = None,
                source_llm_blueprint_id: Optional[str] = None,
                source_remote_repositories: Optional[Sequence[CustomModelSourceRemoteRepositoryArgs]] = None,
                target_name: Optional[str] = None,
                target_type: Optional[str] = None,
                training_data_partition_column: Optional[str] = None,
                training_dataset_id: Optional[str] = None,
                use_case_ids: Optional[Sequence[str]] = None)
    func NewCustomModel(ctx *Context, name string, args *CustomModelArgs, opts ...ResourceOption) (*CustomModel, error)
    public CustomModel(string name, CustomModelArgs? args = null, CustomResourceOptions? opts = null)
    public CustomModel(String name, CustomModelArgs args)
public CustomModel(String name, CustomModelArgs args, CustomResourceOptions options)

    type: datarobot:CustomModel
properties: # The arguments to resource properties.
options: # Bag of options to control resource's behavior.

    Parameters

    name string
    The unique name of the resource.
    args CustomModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    resource_name str
    The unique name of the resource.
    args CustomModelArgs
    The arguments to resource properties.
    opts ResourceOptions
    Bag of options to control resource's behavior.
    ctx Context
    Context object for the current deployment.
    name string
    The unique name of the resource.
    args CustomModelArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args CustomModelArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args CustomModelArgs
    The arguments to resource properties.
    options CustomResourceOptions
    Bag of options to control resource's behavior.

    Constructor example

    The following reference example uses placeholder values for all input properties.

    var customModelResource = new Datarobot.CustomModel("customModelResource", new()
{
    BaseEnvironmentId = "string",
    BaseEnvironmentVersionId = "string",
    ClassLabels = new[]
    {
        "string",
    },
    ClassLabelsFile = "string",
    Description = "string",
    Files = "any",
    FolderPath = "string",
    GuardConfigurations = new[]
    {
        new Datarobot.Inputs.CustomModelGuardConfigurationArgs
        {
            Intervention = new Datarobot.Inputs.CustomModelGuardConfigurationInterventionArgs
            {
                Action = "string",
                Condition = "string",
                Message = "string",
            },
            Name = "string",
            Stages = new[]
            {
                "string",
            },
            TemplateName = "string",
            DeploymentId = "string",
            InputColumnName = "string",
            LlmType = "string",
            NemoInfo = new Datarobot.Inputs.CustomModelGuardConfigurationNemoInfoArgs
            {
                Actions = "string",
                BlockedTerms = "string",
                LlmPrompts = "string",
                MainConfig = "string",
                RailsConfig = "string",
            },
            OpenaiApiBase = "string",
            OpenaiCredential = "string",
            OpenaiDeploymentId = "string",
            OutputColumnName = "string",
        },
    },
    IsProxy = false,
    Language = "string",
    MemoryMb = 0,
    Name = "string",
    NegativeClassLabel = "string",
    NetworkAccess = "string",
    OverallModerationConfiguration = new Datarobot.Inputs.CustomModelOverallModerationConfigurationArgs
    {
        TimeoutAction = "string",
        TimeoutSec = 0,
    },
    PositiveClassLabel = "string",
    PredictionThreshold = 0,
    Replicas = 0,
    ResourceBundleId = "string",
    RuntimeParameterValues = new[]
    {
        new Datarobot.Inputs.CustomModelRuntimeParameterValueArgs
        {
            Key = "string",
            Type = "string",
            Value = "string",
        },
    },
    SourceLlmBlueprintId = "string",
    SourceRemoteRepositories = new[]
    {
        new Datarobot.Inputs.CustomModelSourceRemoteRepositoryArgs
        {
            Id = "string",
            Ref = "string",
            SourcePaths = new[]
            {
                "string",
            },
        },
    },
    TargetName = "string",
    TargetType = "string",
    TrainingDataPartitionColumn = "string",
    TrainingDatasetId = "string",
    UseCaseIds = new[]
    {
        "string",
    },
});

    example, err := datarobot.NewCustomModel(ctx, "customModelResource", &datarobot.CustomModelArgs{
	BaseEnvironmentId:        pulumi.String("string"),
	BaseEnvironmentVersionId: pulumi.String("string"),
	ClassLabels: pulumi.StringArray{
		pulumi.String("string"),
	},
	ClassLabelsFile: pulumi.String("string"),
	Description:     pulumi.String("string"),
	Files:           pulumi.Any("any"),
	FolderPath:      pulumi.String("string"),
	GuardConfigurations: datarobot.CustomModelGuardConfigurationArray{
		&datarobot.CustomModelGuardConfigurationArgs{
			Intervention: &datarobot.CustomModelGuardConfigurationInterventionArgs{
				Action:    pulumi.String("string"),
				Condition: pulumi.String("string"),
				Message:   pulumi.String("string"),
			},
			Name: pulumi.String("string"),
			Stages: pulumi.StringArray{
				pulumi.String("string"),
			},
			TemplateName:    pulumi.String("string"),
			DeploymentId:    pulumi.String("string"),
			InputColumnName: pulumi.String("string"),
			LlmType:         pulumi.String("string"),
			NemoInfo: &datarobot.CustomModelGuardConfigurationNemoInfoArgs{
				Actions:      pulumi.String("string"),
				BlockedTerms: pulumi.String("string"),
				LlmPrompts:   pulumi.String("string"),
				MainConfig:   pulumi.String("string"),
				RailsConfig:  pulumi.String("string"),
			},
			OpenaiApiBase:      pulumi.String("string"),
			OpenaiCredential:   pulumi.String("string"),
			OpenaiDeploymentId: pulumi.String("string"),
			OutputColumnName:   pulumi.String("string"),
		},
	},
	IsProxy:            pulumi.Bool(false),
	Language:           pulumi.String("string"),
	MemoryMb:           pulumi.Int(0),
	Name:               pulumi.String("string"),
	NegativeClassLabel: pulumi.String("string"),
	NetworkAccess:      pulumi.String("string"),
	OverallModerationConfiguration: &datarobot.CustomModelOverallModerationConfigurationArgs{
		TimeoutAction: pulumi.String("string"),
		TimeoutSec:    pulumi.Int(0),
	},
	PositiveClassLabel:  pulumi.String("string"),
	PredictionThreshold: pulumi.Float64(0),
	Replicas:            pulumi.Int(0),
	ResourceBundleId:    pulumi.String("string"),
	RuntimeParameterValues: datarobot.CustomModelRuntimeParameterValueArray{
		&datarobot.CustomModelRuntimeParameterValueArgs{
			Key:   pulumi.String("string"),
			Type:  pulumi.String("string"),
			Value: pulumi.String("string"),
		},
	},
	SourceLlmBlueprintId: pulumi.String("string"),
	SourceRemoteRepositories: datarobot.CustomModelSourceRemoteRepositoryArray{
		&datarobot.CustomModelSourceRemoteRepositoryArgs{
			Id:  pulumi.String("string"),
			Ref: pulumi.String("string"),
			SourcePaths: pulumi.StringArray{
				pulumi.String("string"),
			},
		},
	},
	TargetName:                  pulumi.String("string"),
	TargetType:                  pulumi.String("string"),
	TrainingDataPartitionColumn: pulumi.String("string"),
	TrainingDatasetId:           pulumi.String("string"),
	UseCaseIds: pulumi.StringArray{
		pulumi.String("string"),
	},
})

    var customModelResource = new CustomModel("customModelResource", CustomModelArgs.builder()
    .baseEnvironmentId("string")
    .baseEnvironmentVersionId("string")
    .classLabels("string")
    .classLabelsFile("string")
    .description("string")
    .files("any")
    .folderPath("string")
    .guardConfigurations(CustomModelGuardConfigurationArgs.builder()
        .intervention(CustomModelGuardConfigurationInterventionArgs.builder()
            .action("string")
            .condition("string")
            .message("string")
            .build())
        .name("string")
        .stages("string")
        .templateName("string")
        .deploymentId("string")
        .inputColumnName("string")
        .llmType("string")
        .nemoInfo(CustomModelGuardConfigurationNemoInfoArgs.builder()
            .actions("string")
            .blockedTerms("string")
            .llmPrompts("string")
            .mainConfig("string")
            .railsConfig("string")
            .build())
        .openaiApiBase("string")
        .openaiCredential("string")
        .openaiDeploymentId("string")
        .outputColumnName("string")
        .build())
    .isProxy(false)
    .language("string")
    .memoryMb(0)
    .name("string")
    .negativeClassLabel("string")
    .networkAccess("string")
    .overallModerationConfiguration(CustomModelOverallModerationConfigurationArgs.builder()
        .timeoutAction("string")
        .timeoutSec(0)
        .build())
    .positiveClassLabel("string")
    .predictionThreshold(0)
    .replicas(0)
    .resourceBundleId("string")
    .runtimeParameterValues(CustomModelRuntimeParameterValueArgs.builder()
        .key("string")
        .type("string")
        .value("string")
        .build())
    .sourceLlmBlueprintId("string")
    .sourceRemoteRepositories(CustomModelSourceRemoteRepositoryArgs.builder()
        .id("string")
        .ref("string")
        .sourcePaths("string")
        .build())
    .targetName("string")
    .targetType("string")
    .trainingDataPartitionColumn("string")
    .trainingDatasetId("string")
    .useCaseIds("string")
    .build());

    custom_model_resource = datarobot.CustomModel("customModelResource",
    base_environment_id="string",
    base_environment_version_id="string",
    class_labels=["string"],
    class_labels_file="string",
    description="string",
    files="any",
    folder_path="string",
    guard_configurations=[{
        "intervention": {
            "action": "string",
            "condition": "string",
            "message": "string",
        },
        "name": "string",
        "stages": ["string"],
        "template_name": "string",
        "deployment_id": "string",
        "input_column_name": "string",
        "llm_type": "string",
        "nemo_info": {
            "actions": "string",
            "blocked_terms": "string",
            "llm_prompts": "string",
            "main_config": "string",
            "rails_config": "string",
        },
        "openai_api_base": "string",
        "openai_credential": "string",
        "openai_deployment_id": "string",
        "output_column_name": "string",
    }],
    is_proxy=False,
    language="string",
    memory_mb=0,
    name="string",
    negative_class_label="string",
    network_access="string",
    overall_moderation_configuration={
        "timeout_action": "string",
        "timeout_sec": 0,
    },
    positive_class_label="string",
    prediction_threshold=0,
    replicas=0,
    resource_bundle_id="string",
    runtime_parameter_values=[{
        "key": "string",
        "type": "string",
        "value": "string",
    }],
    source_llm_blueprint_id="string",
    source_remote_repositories=[{
        "id": "string",
        "ref": "string",
        "source_paths": ["string"],
    }],
    target_name="string",
    target_type="string",
    training_data_partition_column="string",
    training_dataset_id="string",
    use_case_ids=["string"])

    const customModelResource = new datarobot.CustomModel("customModelResource", {
    baseEnvironmentId: "string",
    baseEnvironmentVersionId: "string",
    classLabels: ["string"],
    classLabelsFile: "string",
    description: "string",
    files: "any",
    folderPath: "string",
    guardConfigurations: [{
        intervention: {
            action: "string",
            condition: "string",
            message: "string",
        },
        name: "string",
        stages: ["string"],
        templateName: "string",
        deploymentId: "string",
        inputColumnName: "string",
        llmType: "string",
        nemoInfo: {
            actions: "string",
            blockedTerms: "string",
            llmPrompts: "string",
            mainConfig: "string",
            railsConfig: "string",
        },
        openaiApiBase: "string",
        openaiCredential: "string",
        openaiDeploymentId: "string",
        outputColumnName: "string",
    }],
    isProxy: false,
    language: "string",
    memoryMb: 0,
    name: "string",
    negativeClassLabel: "string",
    networkAccess: "string",
    overallModerationConfiguration: {
        timeoutAction: "string",
        timeoutSec: 0,
    },
    positiveClassLabel: "string",
    predictionThreshold: 0,
    replicas: 0,
    resourceBundleId: "string",
    runtimeParameterValues: [{
        key: "string",
        type: "string",
        value: "string",
    }],
    sourceLlmBlueprintId: "string",
    sourceRemoteRepositories: [{
        id: "string",
        ref: "string",
        sourcePaths: ["string"],
    }],
    targetName: "string",
    targetType: "string",
    trainingDataPartitionColumn: "string",
    trainingDatasetId: "string",
    useCaseIds: ["string"],
});

    type: datarobot:CustomModel
properties:
    baseEnvironmentId: string
    baseEnvironmentVersionId: string
    classLabels:
        - string
    classLabelsFile: string
    description: string
    files: any
    folderPath: string
    guardConfigurations:
        - deploymentId: string
          inputColumnName: string
          intervention:
            action: string
            condition: string
            message: string
          llmType: string
          name: string
          nemoInfo:
            actions: string
            blockedTerms: string
            llmPrompts: string
            mainConfig: string
            railsConfig: string
          openaiApiBase: string
          openaiCredential: string
          openaiDeploymentId: string
          outputColumnName: string
          stages:
            - string
          templateName: string
    isProxy: false
    language: string
    memoryMb: 0
    name: string
    negativeClassLabel: string
    networkAccess: string
    overallModerationConfiguration:
        timeoutAction: string
        timeoutSec: 0
    positiveClassLabel: string
    predictionThreshold: 0
    replicas: 0
    resourceBundleId: string
    runtimeParameterValues:
        - key: string
          type: string
          value: string
    sourceLlmBlueprintId: string
    sourceRemoteRepositories:
        - id: string
          ref: string
          sourcePaths:
            - string
    targetName: string
    targetType: string
    trainingDataPartitionColumn: string
    trainingDatasetId: string
    useCaseIds:
        - string

    CustomModel Resource Properties

    To learn more about resource properties and how to use them, see Inputs and Outputs in the Architecture and Concepts docs.

    Inputs

    In Python, inputs that are objects can be passed either as argument classes or as dictionary literals.

    The CustomModel resource accepts the following input properties:

    BaseEnvironmentId string
    The ID of the base environment for the Custom Model.
    BaseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    ClassLabels List<string>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    ClassLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    Description string
    The description of the Custom Model.
    Files object
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    FolderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    GuardConfigurations List<DataRobotCustomModelGuardConfiguration>
    The guard configurations for the Custom Model.
    IsProxy bool
    Flag indicating if the Custom Model is a proxy model.
    Language string
    The language used to build the Custom Model.
    MemoryMb int
    The memory in MB for the Custom Model.
    Name string
    The name of the Custom Model.
    NegativeClassLabel string
    The negative class label of the Custom Model.
    NetworkAccess string
    The network access for the Custom Model.
    OverallModerationConfiguration DataRobotCustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    PositiveClassLabel string
    The positive class label of the Custom Model.
    PredictionThreshold double
    The prediction threshold of the Custom Model.
    Replicas int
    The replicas for the Custom Model.
    ResourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    RuntimeParameterValues List<DataRobotCustomModelRuntimeParameterValue>
    The runtime parameter values for the Custom Model.
    SourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    SourceRemoteRepositories List<DataRobotCustomModelSourceRemoteRepository>
    The source remote repositories for the Custom Model.
    TargetName string
    The target name of the Custom Model.
    TargetType string
    The target type of the Custom Model.
    TrainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    TrainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    UseCaseIds List<string>
    The list of Use Case IDs to add the Custom Model version to.
    BaseEnvironmentId string
    The ID of the base environment for the Custom Model.
    BaseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    ClassLabels []string
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    ClassLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    Description string
    The description of the Custom Model.
    Files interface{}
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    FolderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    GuardConfigurations []CustomModelGuardConfigurationArgs
    The guard configurations for the Custom Model.
    IsProxy bool
    Flag indicating if the Custom Model is a proxy model.
    Language string
    The language used to build the Custom Model.
    MemoryMb int
    The memory in MB for the Custom Model.
    Name string
    The name of the Custom Model.
    NegativeClassLabel string
    The negative class label of the Custom Model.
    NetworkAccess string
    The network access for the Custom Model.
    OverallModerationConfiguration CustomModelOverallModerationConfigurationArgs
    The overall moderation configuration for the Custom Model.
    PositiveClassLabel string
    The positive class label of the Custom Model.
    PredictionThreshold float64
    The prediction threshold of the Custom Model.
    Replicas int
    The replicas for the Custom Model.
    ResourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    RuntimeParameterValues []CustomModelRuntimeParameterValueArgs
    The runtime parameter values for the Custom Model.
    SourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    SourceRemoteRepositories []CustomModelSourceRemoteRepositoryArgs
    The source remote repositories for the Custom Model.
    TargetName string
    The target name of the Custom Model.
    TargetType string
    The target type of the Custom Model.
    TrainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    TrainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    UseCaseIds []string
    The list of Use Case IDs to add the Custom Model version to.
    baseEnvironmentId String
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId String
    The ID of the base environment version for the Custom Model.
    classLabels List<String>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile String
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    description String
    The description of the Custom Model.
    files Object
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    folderPath String
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    guardConfigurations List<CustomModelGuardConfiguration>
    The guard configurations for the Custom Model.
    isProxy Boolean
    Flag indicating if the Custom Model is a proxy model.
    language String
    The language used to build the Custom Model.
    memoryMb Integer
    The memory in MB for the Custom Model.
    name String
    The name of the Custom Model.
    negativeClassLabel String
    The negative class label of the Custom Model.
    networkAccess String
    The network access for the Custom Model.
    overallModerationConfiguration CustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    positiveClassLabel String
    The positive class label of the Custom Model.
    predictionThreshold Double
    The prediction threshold of the Custom Model.
    replicas Integer
    The replicas for the Custom Model.
    resourceBundleId String
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues List<CustomModelRuntimeParameterValue>
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId String
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories List<CustomModelSourceRemoteRepository>
    The source remote repositories for the Custom Model.
    targetName String
    The target name of the Custom Model.
    targetType String
    The target type of the Custom Model.
    trainingDataPartitionColumn String
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId String
    The ID of the training dataset assigned to the Custom Model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Custom Model version to.
    baseEnvironmentId string
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    classLabels string[]
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    description string
    The description of the Custom Model.
    files any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    folderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    guardConfigurations CustomModelGuardConfiguration[]
    The guard configurations for the Custom Model.
    isProxy boolean
    Flag indicating if the Custom Model is a proxy model.
    language string
    The language used to build the Custom Model.
    memoryMb number
    The memory in MB for the Custom Model.
    name string
    The name of the Custom Model.
    negativeClassLabel string
    The negative class label of the Custom Model.
    networkAccess string
    The network access for the Custom Model.
    overallModerationConfiguration CustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    positiveClassLabel string
    The positive class label of the Custom Model.
    predictionThreshold number
    The prediction threshold of the Custom Model.
    replicas number
    The replicas for the Custom Model.
    resourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues CustomModelRuntimeParameterValue[]
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories CustomModelSourceRemoteRepository[]
    The source remote repositories for the Custom Model.
    targetName string
    The target name of the Custom Model.
    targetType string
    The target type of the Custom Model.
    trainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    useCaseIds string[]
    The list of Use Case IDs to add the Custom Model version to.
    base_environment_id str
    The ID of the base environment for the Custom Model.
    base_environment_version_id str
    The ID of the base environment version for the Custom Model.
    class_labels Sequence[str]
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    class_labels_file str
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    description str
    The description of the Custom Model.
    files Any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    folder_path str
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    guard_configurations Sequence[CustomModelGuardConfigurationArgs]
    The guard configurations for the Custom Model.
    is_proxy bool
    Flag indicating if the Custom Model is a proxy model.
    language str
    The language used to build the Custom Model.
    memory_mb int
    The memory in MB for the Custom Model.
    name str
    The name of the Custom Model.
    negative_class_label str
    The negative class label of the Custom Model.
    network_access str
    The network access for the Custom Model.
    overall_moderation_configuration CustomModelOverallModerationConfigurationArgs
    The overall moderation configuration for the Custom Model.
    positive_class_label str
    The positive class label of the Custom Model.
    prediction_threshold float
    The prediction threshold of the Custom Model.
    replicas int
    The replicas for the Custom Model.
    resource_bundle_id str
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtime_parameter_values Sequence[CustomModelRuntimeParameterValueArgs]
    The runtime parameter values for the Custom Model.
    source_llm_blueprint_id str
    The ID of the source LLM Blueprint for the Custom Model.
    source_remote_repositories Sequence[CustomModelSourceRemoteRepositoryArgs]
    The source remote repositories for the Custom Model.
    target_name str
    The target name of the Custom Model.
    target_type str
    The target type of the Custom Model.
    training_data_partition_column str
    The name of the partition column in the training dataset assigned to the Custom Model.
    training_dataset_id str
    The ID of the training dataset assigned to the Custom Model.
    use_case_ids Sequence[str]
    The list of Use Case IDs to add the Custom Model version to.
    baseEnvironmentId String
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId String
    The ID of the base environment version for the Custom Model.
    classLabels List<String>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile String
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    description String
    The description of the Custom Model.
    files Any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    folderPath String
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    guardConfigurations List<Property Map>
    The guard configurations for the Custom Model.
    isProxy Boolean
    Flag indicating if the Custom Model is a proxy model.
    language String
    The language used to build the Custom Model.
    memoryMb Number
    The memory in MB for the Custom Model.
    name String
    The name of the Custom Model.
    negativeClassLabel String
    The negative class label of the Custom Model.
    networkAccess String
    The network access for the Custom Model.
    overallModerationConfiguration Property Map
    The overall moderation configuration for the Custom Model.
    positiveClassLabel String
    The positive class label of the Custom Model.
    predictionThreshold Number
    The prediction threshold of the Custom Model.
    replicas Number
    The replicas for the Custom Model.
    resourceBundleId String
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues List<Property Map>
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId String
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories List<Property Map>
    The source remote repositories for the Custom Model.
    targetName String
    The target name of the Custom Model.
    targetType String
    The target type of the Custom Model.
    trainingDataPartitionColumn String
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId String
    The ID of the training dataset assigned to the Custom Model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Custom Model version to.

    Outputs

    All input properties are implicitly available as output properties. Additionally, the CustomModel resource produces the following output properties:

    DeploymentsCount int
    The number of deployments for the Custom Model.
    FilesHashes List<string>
    The hash of file contents for each file in files.
    FolderPathHash string
    The hash of the folder path contents.
    Id string
    The provider-assigned unique ID for this managed resource.
    TrainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    TrainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    VersionId string
    The ID of the latest Custom Model version.
    DeploymentsCount int
    The number of deployments for the Custom Model.
    FilesHashes []string
    The hash of file contents for each file in files.
    FolderPathHash string
    The hash of the folder path contents.
    Id string
    The provider-assigned unique ID for this managed resource.
    TrainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    TrainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    VersionId string
    The ID of the latest Custom Model version.
    deploymentsCount Integer
    The number of deployments for the Custom Model.
    filesHashes List<String>
    The hash of file contents for each file in files.
    folderPathHash String
    The hash of the folder path contents.
    id String
    The provider-assigned unique ID for this managed resource.
    trainingDatasetName String
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId String
    The version ID of the training dataset assigned to the Custom Model.
    versionId String
    The ID of the latest Custom Model version.
    deploymentsCount number
    The number of deployments for the Custom Model.
    filesHashes string[]
    The hash of file contents for each file in files.
    folderPathHash string
    The hash of the folder path contents.
    id string
    The provider-assigned unique ID for this managed resource.
    trainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    versionId string
    The ID of the latest Custom Model version.
    deployments_count int
    The number of deployments for the Custom Model.
    files_hashes Sequence[str]
    The hash of file contents for each file in files.
    folder_path_hash str
    The hash of the folder path contents.
    id str
    The provider-assigned unique ID for this managed resource.
    training_dataset_name str
    The name of the training dataset assigned to the Custom Model.
    training_dataset_version_id str
    The version ID of the training dataset assigned to the Custom Model.
    version_id str
    The ID of the latest Custom Model version.
    deploymentsCount Number
    The number of deployments for the Custom Model.
    filesHashes List<String>
    The hash of file contents for each file in files.
    folderPathHash String
    The hash of the folder path contents.
    id String
    The provider-assigned unique ID for this managed resource.
    trainingDatasetName String
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId String
    The version ID of the training dataset assigned to the Custom Model.
    versionId String
    The ID of the latest Custom Model version.

    Look up Existing CustomModel Resource

    Get an existing CustomModel resource’s state with the given name, ID, and optional extra properties used to qualify the lookup.

    public static get(name: string, id: Input<ID>, state?: CustomModelState, opts?: CustomResourceOptions): CustomModel
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        base_environment_id: Optional[str] = None,
        base_environment_version_id: Optional[str] = None,
        class_labels: Optional[Sequence[str]] = None,
        class_labels_file: Optional[str] = None,
        deployments_count: Optional[int] = None,
        description: Optional[str] = None,
        files: Optional[Any] = None,
        files_hashes: Optional[Sequence[str]] = None,
        folder_path: Optional[str] = None,
        folder_path_hash: Optional[str] = None,
        guard_configurations: Optional[Sequence[CustomModelGuardConfigurationArgs]] = None,
        is_proxy: Optional[bool] = None,
        language: Optional[str] = None,
        memory_mb: Optional[int] = None,
        name: Optional[str] = None,
        negative_class_label: Optional[str] = None,
        network_access: Optional[str] = None,
        overall_moderation_configuration: Optional[CustomModelOverallModerationConfigurationArgs] = None,
        positive_class_label: Optional[str] = None,
        prediction_threshold: Optional[float] = None,
        replicas: Optional[int] = None,
        resource_bundle_id: Optional[str] = None,
        runtime_parameter_values: Optional[Sequence[CustomModelRuntimeParameterValueArgs]] = None,
        source_llm_blueprint_id: Optional[str] = None,
        source_remote_repositories: Optional[Sequence[CustomModelSourceRemoteRepositoryArgs]] = None,
        target_name: Optional[str] = None,
        target_type: Optional[str] = None,
        training_data_partition_column: Optional[str] = None,
        training_dataset_id: Optional[str] = None,
        training_dataset_name: Optional[str] = None,
        training_dataset_version_id: Optional[str] = None,
        use_case_ids: Optional[Sequence[str]] = None,
        version_id: Optional[str] = None) -> CustomModel
    func GetCustomModel(ctx *Context, name string, id IDInput, state *CustomModelState, opts ...ResourceOption) (*CustomModel, error)
    public static CustomModel Get(string name, Input<string> id, CustomModelState? state, CustomResourceOptions? opts = null)
    public static CustomModel get(String name, Output<String> id, CustomModelState state, CustomResourceOptions options)
    Resource lookup is not supported in YAML
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    resource_name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    name
    The unique name of the resulting resource.
    id
    The unique provider ID of the resource to lookup.
    state
    Any extra arguments used during the lookup.
    opts
    A bag of options that control this resource's behavior.
    The following state arguments are supported:
    BaseEnvironmentId string
    The ID of the base environment for the Custom Model.
    BaseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    ClassLabels List<string>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    ClassLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    DeploymentsCount int
    The number of deployments for the Custom Model.
    Description string
    The description of the Custom Model.
    Files object
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    FilesHashes List<string>
    The hash of file contents for each file in files.
    FolderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    FolderPathHash string
    The hash of the folder path contents.
    GuardConfigurations List<DataRobotCustomModelGuardConfiguration>
    The guard configurations for the Custom Model.
    IsProxy bool
    Flag indicating if the Custom Model is a proxy model.
    Language string
    The language used to build the Custom Model.
    MemoryMb int
    The memory in MB for the Custom Model.
    Name string
    The name of the Custom Model.
    NegativeClassLabel string
    The negative class label of the Custom Model.
    NetworkAccess string
    The network access for the Custom Model.
    OverallModerationConfiguration DataRobotCustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    PositiveClassLabel string
    The positive class label of the Custom Model.
    PredictionThreshold double
    The prediction threshold of the Custom Model.
    Replicas int
    The replicas for the Custom Model.
    ResourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    RuntimeParameterValues List<DataRobotCustomModelRuntimeParameterValue>
    The runtime parameter values for the Custom Model.
    SourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    SourceRemoteRepositories List<DataRobotCustomModelSourceRemoteRepository>
    The source remote repositories for the Custom Model.
    TargetName string
    The target name of the Custom Model.
    TargetType string
    The target type of the Custom Model.
    TrainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    TrainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    TrainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    TrainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    UseCaseIds List<string>
    The list of Use Case IDs to add the Custom Model version to.
    VersionId string
    The ID of the latest Custom Model version.
    BaseEnvironmentId string
    The ID of the base environment for the Custom Model.
    BaseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    ClassLabels []string
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    ClassLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    DeploymentsCount int
    The number of deployments for the Custom Model.
    Description string
    The description of the Custom Model.
    Files interface{}
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    FilesHashes []string
    The hash of file contents for each file in files.
    FolderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    FolderPathHash string
    The hash of the folder path contents.
    GuardConfigurations []CustomModelGuardConfigurationArgs
    The guard configurations for the Custom Model.
    IsProxy bool
    Flag indicating if the Custom Model is a proxy model.
    Language string
    The language used to build the Custom Model.
    MemoryMb int
    The memory in MB for the Custom Model.
    Name string
    The name of the Custom Model.
    NegativeClassLabel string
    The negative class label of the Custom Model.
    NetworkAccess string
    The network access for the Custom Model.
    OverallModerationConfiguration CustomModelOverallModerationConfigurationArgs
    The overall moderation configuration for the Custom Model.
    PositiveClassLabel string
    The positive class label of the Custom Model.
    PredictionThreshold float64
    The prediction threshold of the Custom Model.
    Replicas int
    The replicas for the Custom Model.
    ResourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    RuntimeParameterValues []CustomModelRuntimeParameterValueArgs
    The runtime parameter values for the Custom Model.
    SourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    SourceRemoteRepositories []CustomModelSourceRemoteRepositoryArgs
    The source remote repositories for the Custom Model.
    TargetName string
    The target name of the Custom Model.
    TargetType string
    The target type of the Custom Model.
    TrainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    TrainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    TrainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    TrainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    UseCaseIds []string
    The list of Use Case IDs to add the Custom Model version to.
    VersionId string
    The ID of the latest Custom Model version.
    baseEnvironmentId String
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId String
    The ID of the base environment version for the Custom Model.
    classLabels List<String>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile String
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    deploymentsCount Integer
    The number of deployments for the Custom Model.
    description String
    The description of the Custom Model.
    files Object
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    filesHashes List<String>
    The hash of file contents for each file in files.
    folderPath String
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    folderPathHash String
    The hash of the folder path contents.
    guardConfigurations List<CustomModelGuardConfiguration>
    The guard configurations for the Custom Model.
    isProxy Boolean
    Flag indicating if the Custom Model is a proxy model.
    language String
    The language used to build the Custom Model.
    memoryMb Integer
    The memory in MB for the Custom Model.
    name String
    The name of the Custom Model.
    negativeClassLabel String
    The negative class label of the Custom Model.
    networkAccess String
    The network access for the Custom Model.
    overallModerationConfiguration CustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    positiveClassLabel String
    The positive class label of the Custom Model.
    predictionThreshold Double
    The prediction threshold of the Custom Model.
    replicas Integer
    The replicas for the Custom Model.
    resourceBundleId String
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues List<CustomModelRuntimeParameterValue>
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId String
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories List<CustomModelSourceRemoteRepository>
    The source remote repositories for the Custom Model.
    targetName String
    The target name of the Custom Model.
    targetType String
    The target type of the Custom Model.
    trainingDataPartitionColumn String
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId String
    The ID of the training dataset assigned to the Custom Model.
    trainingDatasetName String
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId String
    The version ID of the training dataset assigned to the Custom Model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Custom Model version to.
    versionId String
    The ID of the latest Custom Model version.
    baseEnvironmentId string
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId string
    The ID of the base environment version for the Custom Model.
    classLabels string[]
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile string
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    deploymentsCount number
    The number of deployments for the Custom Model.
    description string
    The description of the Custom Model.
    files any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    filesHashes string[]
    The hash of file contents for each file in files.
    folderPath string
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    folderPathHash string
    The hash of the folder path contents.
    guardConfigurations CustomModelGuardConfiguration[]
    The guard configurations for the Custom Model.
    isProxy boolean
    Flag indicating if the Custom Model is a proxy model.
    language string
    The language used to build the Custom Model.
    memoryMb number
    The memory in MB for the Custom Model.
    name string
    The name of the Custom Model.
    negativeClassLabel string
    The negative class label of the Custom Model.
    networkAccess string
    The network access for the Custom Model.
    overallModerationConfiguration CustomModelOverallModerationConfiguration
    The overall moderation configuration for the Custom Model.
    positiveClassLabel string
    The positive class label of the Custom Model.
    predictionThreshold number
    The prediction threshold of the Custom Model.
    replicas number
    The replicas for the Custom Model.
    resourceBundleId string
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues CustomModelRuntimeParameterValue[]
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId string
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories CustomModelSourceRemoteRepository[]
    The source remote repositories for the Custom Model.
    targetName string
    The target name of the Custom Model.
    targetType string
    The target type of the Custom Model.
    trainingDataPartitionColumn string
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId string
    The ID of the training dataset assigned to the Custom Model.
    trainingDatasetName string
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId string
    The version ID of the training dataset assigned to the Custom Model.
    useCaseIds string[]
    The list of Use Case IDs to add the Custom Model version to.
    versionId string
    The ID of the latest Custom Model version.
    base_environment_id str
    The ID of the base environment for the Custom Model.
    base_environment_version_id str
    The ID of the base environment version for the Custom Model.
    class_labels Sequence[str]
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    class_labels_file str
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    deployments_count int
    The number of deployments for the Custom Model.
    description str
    The description of the Custom Model.
    files Any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    files_hashes Sequence[str]
    The hash of file contents for each file in files.
    folder_path str
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    folder_path_hash str
    The hash of the folder path contents.
    guard_configurations Sequence[CustomModelGuardConfigurationArgs]
    The guard configurations for the Custom Model.
    is_proxy bool
    Flag indicating if the Custom Model is a proxy model.
    language str
    The language used to build the Custom Model.
    memory_mb int
    The memory in MB for the Custom Model.
    name str
    The name of the Custom Model.
    negative_class_label str
    The negative class label of the Custom Model.
    network_access str
    The network access for the Custom Model.
    overall_moderation_configuration CustomModelOverallModerationConfigurationArgs
    The overall moderation configuration for the Custom Model.
    positive_class_label str
    The positive class label of the Custom Model.
    prediction_threshold float
    The prediction threshold of the Custom Model.
    replicas int
    The replicas for the Custom Model.
    resource_bundle_id str
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtime_parameter_values Sequence[CustomModelRuntimeParameterValueArgs]
    The runtime parameter values for the Custom Model.
    source_llm_blueprint_id str
    The ID of the source LLM Blueprint for the Custom Model.
    source_remote_repositories Sequence[CustomModelSourceRemoteRepositoryArgs]
    The source remote repositories for the Custom Model.
    target_name str
    The target name of the Custom Model.
    target_type str
    The target type of the Custom Model.
    training_data_partition_column str
    The name of the partition column in the training dataset assigned to the Custom Model.
    training_dataset_id str
    The ID of the training dataset assigned to the Custom Model.
    training_dataset_name str
    The name of the training dataset assigned to the Custom Model.
    training_dataset_version_id str
    The version ID of the training dataset assigned to the Custom Model.
    use_case_ids Sequence[str]
    The list of Use Case IDs to add the Custom Model version to.
    version_id str
    The ID of the latest Custom Model version.
    baseEnvironmentId String
    The ID of the base environment for the Custom Model.
    baseEnvironmentVersionId String
    The ID of the base environment version for the Custom Model.
    classLabels List<String>
    Class labels for multiclass classification. Cannot be used with classlabelsfile.
    classLabelsFile String
    Path to file containing newline separated class labels for multiclass classification. Cannot be used with class_labels.
    deploymentsCount Number
    The number of deployments for the Custom Model.
    description String
    The description of the Custom Model.
    files Any
    The list of tuples, where values in each tuple are the local filesystem path and the path the file should be placed in the Custom Model. If list is of strings, then basenames will be used for tuples.
    filesHashes List<String>
    The hash of file contents for each file in files.
    folderPath String
    The path to a folder containing files to build the Custom Model. Each file in the folder is uploaded under path relative to a folder path.
    folderPathHash String
    The hash of the folder path contents.
    guardConfigurations List<Property Map>
    The guard configurations for the Custom Model.
    isProxy Boolean
    Flag indicating if the Custom Model is a proxy model.
    language String
    The language used to build the Custom Model.
    memoryMb Number
    The memory in MB for the Custom Model.
    name String
    The name of the Custom Model.
    negativeClassLabel String
    The negative class label of the Custom Model.
    networkAccess String
    The network access for the Custom Model.
    overallModerationConfiguration Property Map
    The overall moderation configuration for the Custom Model.
    positiveClassLabel String
    The positive class label of the Custom Model.
    predictionThreshold Number
    The prediction threshold of the Custom Model.
    replicas Number
    The replicas for the Custom Model.
    resourceBundleId String
    A single identifier that represents a bundle of resources: Memory, CPU, GPU, etc.
    runtimeParameterValues List<Property Map>
    The runtime parameter values for the Custom Model.
    sourceLlmBlueprintId String
    The ID of the source LLM Blueprint for the Custom Model.
    sourceRemoteRepositories List<Property Map>
    The source remote repositories for the Custom Model.
    targetName String
    The target name of the Custom Model.
    targetType String
    The target type of the Custom Model.
    trainingDataPartitionColumn String
    The name of the partition column in the training dataset assigned to the Custom Model.
    trainingDatasetId String
    The ID of the training dataset assigned to the Custom Model.
    trainingDatasetName String
    The name of the training dataset assigned to the Custom Model.
    trainingDatasetVersionId String
    The version ID of the training dataset assigned to the Custom Model.
    useCaseIds List<String>
    The list of Use Case IDs to add the Custom Model version to.
    versionId String
    The ID of the latest Custom Model version.

    Supporting Types

    CustomModelGuardConfiguration, CustomModelGuardConfigurationArgs

    Intervention DataRobotCustomModelGuardConfigurationIntervention
    The intervention for the guard configuration.
    Name string
    The name of the guard configuration.
    Stages List<string>
    The list of stages for the guard configuration.
    TemplateName string
    The template name of the guard configuration.
    DeploymentId string
    The deployment ID of this guard.
    InputColumnName string
    The input column name of this guard.
    LlmType string
    The LLM type for this guard.
    NemoInfo DataRobotCustomModelGuardConfigurationNemoInfo
    Configuration info for NeMo guards.
    OpenaiApiBase string
    The OpenAI API base URL for this guard.
    OpenaiCredential string
    The ID of an OpenAI credential for this guard.
    OpenaiDeploymentId string
    The ID of an OpenAI deployment for this guard.
    OutputColumnName string
    The output column name of this guard.
    Intervention CustomModelGuardConfigurationIntervention
    The intervention for the guard configuration.
    Name string
    The name of the guard configuration.
    Stages []string
    The list of stages for the guard configuration.
    TemplateName string
    The template name of the guard configuration.
    DeploymentId string
    The deployment ID of this guard.
    InputColumnName string
    The input column name of this guard.
    LlmType string
    The LLM type for this guard.
    NemoInfo CustomModelGuardConfigurationNemoInfo
    Configuration info for NeMo guards.
    OpenaiApiBase string
    The OpenAI API base URL for this guard.
    OpenaiCredential string
    The ID of an OpenAI credential for this guard.
    OpenaiDeploymentId string
    The ID of an OpenAI deployment for this guard.
    OutputColumnName string
    The output column name of this guard.
    intervention CustomModelGuardConfigurationIntervention
    The intervention for the guard configuration.
    name String
    The name of the guard configuration.
    stages List<String>
    The list of stages for the guard configuration.
    templateName String
    The template name of the guard configuration.
    deploymentId String
    The deployment ID of this guard.
    inputColumnName String
    The input column name of this guard.
    llmType String
    The LLM type for this guard.
    nemoInfo CustomModelGuardConfigurationNemoInfo
    Configuration info for NeMo guards.
    openaiApiBase String
    The OpenAI API base URL for this guard.
    openaiCredential String
    The ID of an OpenAI credential for this guard.
    openaiDeploymentId String
    The ID of an OpenAI deployment for this guard.
    outputColumnName String
    The output column name of this guard.
    intervention CustomModelGuardConfigurationIntervention
    The intervention for the guard configuration.
    name string
    The name of the guard configuration.
    stages string[]
    The list of stages for the guard configuration.
    templateName string
    The template name of the guard configuration.
    deploymentId string
    The deployment ID of this guard.
    inputColumnName string
    The input column name of this guard.
    llmType string
    The LLM type for this guard.
    nemoInfo CustomModelGuardConfigurationNemoInfo
    Configuration info for NeMo guards.
    openaiApiBase string
    The OpenAI API base URL for this guard.
    openaiCredential string
    The ID of an OpenAI credential for this guard.
    openaiDeploymentId string
    The ID of an OpenAI deployment for this guard.
    outputColumnName string
    The output column name of this guard.
    intervention CustomModelGuardConfigurationIntervention
    The intervention for the guard configuration.
    name str
    The name of the guard configuration.
    stages Sequence[str]
    The list of stages for the guard configuration.
    template_name str
    The template name of the guard configuration.
    deployment_id str
    The deployment ID of this guard.
    input_column_name str
    The input column name of this guard.
    llm_type str
    The LLM type for this guard.
    nemo_info CustomModelGuardConfigurationNemoInfo
    Configuration info for NeMo guards.
    openai_api_base str
    The OpenAI API base URL for this guard.
    openai_credential str
    The ID of an OpenAI credential for this guard.
    openai_deployment_id str
    The ID of an OpenAI deployment for this guard.
    output_column_name str
    The output column name of this guard.
    intervention Property Map
    The intervention for the guard configuration.
    name String
    The name of the guard configuration.
    stages List<String>
    The list of stages for the guard configuration.
    templateName String
    The template name of the guard configuration.
    deploymentId String
    The deployment ID of this guard.
    inputColumnName String
    The input column name of this guard.
    llmType String
    The LLM type for this guard.
    nemoInfo Property Map
    Configuration info for NeMo guards.
    openaiApiBase String
    The OpenAI API base URL for this guard.
    openaiCredential String
    The ID of an OpenAI credential for this guard.
    openaiDeploymentId String
    The ID of an OpenAI deployment for this guard.
    outputColumnName String
    The output column name of this guard.

    CustomModelGuardConfigurationIntervention, CustomModelGuardConfigurationInterventionArgs

    Action string
    The action of the guard intervention.
    Condition string
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    Message string
    The message of the guard intervention.
    Action string
    The action of the guard intervention.
    Condition string
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    Message string
    The message of the guard intervention.
    action String
    The action of the guard intervention.
    condition String
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    message String
    The message of the guard intervention.
    action string
    The action of the guard intervention.
    condition string
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    message string
    The message of the guard intervention.
    action str
    The action of the guard intervention.
    condition str
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    message str
    The message of the guard intervention.
    action String
    The action of the guard intervention.
    condition String
    The JSON-encoded condition of the guard intervention. e.g. {"comparand": 0.5, "comparator": "lessThan"}
    message String
    The message of the guard intervention.

    CustomModelGuardConfigurationNemoInfo, CustomModelGuardConfigurationNemoInfoArgs

    Actions string
    The actions for the NeMo information.
    BlockedTerms string
    NeMo guardrails blocked terms list.
    LlmPrompts string
    NeMo guardrails prompts.
    MainConfig string
    Overall NeMo configuration YAML.
    RailsConfig string
    NeMo guardrails configuration Colang.
    Actions string
    The actions for the NeMo information.
    BlockedTerms string
    NeMo guardrails blocked terms list.
    LlmPrompts string
    NeMo guardrails prompts.
    MainConfig string
    Overall NeMo configuration YAML.
    RailsConfig string
    NeMo guardrails configuration Colang.
    actions String
    The actions for the NeMo information.
    blockedTerms String
    NeMo guardrails blocked terms list.
    llmPrompts String
    NeMo guardrails prompts.
    mainConfig String
    Overall NeMo configuration YAML.
    railsConfig String
    NeMo guardrails configuration Colang.
    actions string
    The actions for the NeMo information.
    blockedTerms string
    NeMo guardrails blocked terms list.
    llmPrompts string
    NeMo guardrails prompts.
    mainConfig string
    Overall NeMo configuration YAML.
    railsConfig string
    NeMo guardrails configuration Colang.
    actions str
    The actions for the NeMo information.
    blocked_terms str
    NeMo guardrails blocked terms list.
    llm_prompts str
    NeMo guardrails prompts.
    main_config str
    Overall NeMo configuration YAML.
    rails_config str
    NeMo guardrails configuration Colang.
    actions String
    The actions for the NeMo information.
    blockedTerms String
    NeMo guardrails blocked terms list.
    llmPrompts String
    NeMo guardrails prompts.
    mainConfig String
    Overall NeMo configuration YAML.
    railsConfig String
    NeMo guardrails configuration Colang.

    CustomModelOverallModerationConfiguration, CustomModelOverallModerationConfigurationArgs

    TimeoutAction string
    The timeout action of the overall moderation configuration.
    TimeoutSec int
    The timeout in seconds of the overall moderation configuration.
    TimeoutAction string
    The timeout action of the overall moderation configuration.
    TimeoutSec int
    The timeout in seconds of the overall moderation configuration.
    timeoutAction String
    The timeout action of the overall moderation configuration.
    timeoutSec Integer
    The timeout in seconds of the overall moderation configuration.
    timeoutAction string
    The timeout action of the overall moderation configuration.
    timeoutSec number
    The timeout in seconds of the overall moderation configuration.
    timeout_action str
    The timeout action of the overall moderation configuration.
    timeout_sec int
    The timeout in seconds of the overall moderation configuration.
    timeoutAction String
    The timeout action of the overall moderation configuration.
    timeoutSec Number
    The timeout in seconds of the overall moderation configuration.

    CustomModelRuntimeParameterValue, CustomModelRuntimeParameterValueArgs

    Key string
    The name of the runtime parameter.
    Type string
    The type of the runtime parameter.
    Value string
    The value of the runtime parameter (type conversion is handled internally).
    Key string
    The name of the runtime parameter.
    Type string
    The type of the runtime parameter.
    Value string
    The value of the runtime parameter (type conversion is handled internally).
    key String
    The name of the runtime parameter.
    type String
    The type of the runtime parameter.
    value String
    The value of the runtime parameter (type conversion is handled internally).
    key string
    The name of the runtime parameter.
    type string
    The type of the runtime parameter.
    value string
    The value of the runtime parameter (type conversion is handled internally).
    key str
    The name of the runtime parameter.
    type str
    The type of the runtime parameter.
    value str
    The value of the runtime parameter (type conversion is handled internally).
    key String
    The name of the runtime parameter.
    type String
    The type of the runtime parameter.
    value String
    The value of the runtime parameter (type conversion is handled internally).

    CustomModelSourceRemoteRepository, CustomModelSourceRemoteRepositoryArgs

    Id string
    The ID of the source remote repository.
    Ref string
    The reference of the source remote repository.
    SourcePaths List<string>
    The list of source paths in the source remote repository.
    Id string
    The ID of the source remote repository.
    Ref string
    The reference of the source remote repository.
    SourcePaths []string
    The list of source paths in the source remote repository.
    id String
    The ID of the source remote repository.
    ref String
    The reference of the source remote repository.
    sourcePaths List<String>
    The list of source paths in the source remote repository.
    id string
    The ID of the source remote repository.
    ref string
    The reference of the source remote repository.
    sourcePaths string[]
    The list of source paths in the source remote repository.
    id str
    The ID of the source remote repository.
    ref str
    The reference of the source remote repository.
    source_paths Sequence[str]
    The list of source paths in the source remote repository.
    id String
    The ID of the source remote repository.
    ref String
    The reference of the source remote repository.
    sourcePaths List<String>
    The list of source paths in the source remote repository.

    Package Details

    Repository
    datarobot datarobot-community/pulumi-datarobot
    License
    Apache-2.0
    Notes
    This Pulumi package is based on the datarobot Terraform Provider.
    datarobot logo
    DataRobot v0.4.5 published on Monday, Nov 18, 2024 by DataRobot, Inc.
    datarobot-community/pulumi-datarobot