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DataRobot v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.CustomModel

Explore with Pulumi AI

DataRobot v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

Custom Model

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;
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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)
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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
	})
}
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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,
    };
});
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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());
    }
}
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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}
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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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. String
The unique name of the resource.
args This property is required. 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",
    },
});
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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"),
	},
})
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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());
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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"])
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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"],
});
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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
Copy

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)
resources:  _:    type: datarobot:CustomModel    get:      id: ${id}
name This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
The unique provider ID of the resource to lookup.
name This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required.
The unique name of the resulting resource.
id This property is required.
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 This property is required. DataRobotCustomModelGuardConfigurationIntervention
The intervention for the guard configuration.
Name This property is required. string
The name of the guard configuration.
Stages This property is required. List<string>
The list of stages for the guard configuration.
TemplateName This property is required. 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 This property is required. CustomModelGuardConfigurationIntervention
The intervention for the guard configuration.
Name This property is required. string
The name of the guard configuration.
Stages This property is required. []string
The list of stages for the guard configuration.
TemplateName This property is required. 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 This property is required. CustomModelGuardConfigurationIntervention
The intervention for the guard configuration.
name This property is required. String
The name of the guard configuration.
stages This property is required. List<String>
The list of stages for the guard configuration.
templateName This property is required. 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 This property is required. CustomModelGuardConfigurationIntervention
The intervention for the guard configuration.
name This property is required. string
The name of the guard configuration.
stages This property is required. string[]
The list of stages for the guard configuration.
templateName This property is required. 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 This property is required. CustomModelGuardConfigurationIntervention
The intervention for the guard configuration.
name This property is required. str
The name of the guard configuration.
stages This property is required. Sequence[str]
The list of stages for the guard configuration.
template_name This property is required. 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 This property is required. Property Map
The intervention for the guard configuration.
name This property is required. String
The name of the guard configuration.
stages This property is required. List<String>
The list of stages for the guard configuration.
templateName This property is required. 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 This property is required. string
The action of the guard intervention.
Condition This property is required. 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 This property is required. string
The action of the guard intervention.
Condition This property is required. 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 This property is required. String
The action of the guard intervention.
condition This property is required. 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 This property is required. string
The action of the guard intervention.
condition This property is required. 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 This property is required. str
The action of the guard intervention.
condition This property is required. 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 This property is required. String
The action of the guard intervention.
condition This property is required. 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 This property is required. string
The name of the runtime parameter.
Type This property is required. string
The type of the runtime parameter.
Value This property is required. string
The value of the runtime parameter (type conversion is handled internally).
Key This property is required. string
The name of the runtime parameter.
Type This property is required. string
The type of the runtime parameter.
Value This property is required. string
The value of the runtime parameter (type conversion is handled internally).
key This property is required. String
The name of the runtime parameter.
type This property is required. String
The type of the runtime parameter.
value This property is required. String
The value of the runtime parameter (type conversion is handled internally).
key This property is required. string
The name of the runtime parameter.
type This property is required. string
The type of the runtime parameter.
value This property is required. string
The value of the runtime parameter (type conversion is handled internally).
key This property is required. str
The name of the runtime parameter.
type This property is required. str
The type of the runtime parameter.
value This property is required. str
The value of the runtime parameter (type conversion is handled internally).
key This property is required. String
The name of the runtime parameter.
type This property is required. String
The type of the runtime parameter.
value This property is required. String
The value of the runtime parameter (type conversion is handled internally).

CustomModelSourceRemoteRepository
, CustomModelSourceRemoteRepositoryArgs

Id This property is required. string
The ID of the source remote repository.
Ref This property is required. string
The reference of the source remote repository.
SourcePaths This property is required. List<string>
The list of source paths in the source remote repository.
Id This property is required. string
The ID of the source remote repository.
Ref This property is required. string
The reference of the source remote repository.
SourcePaths This property is required. []string
The list of source paths in the source remote repository.
id This property is required. String
The ID of the source remote repository.
ref This property is required. String
The reference of the source remote repository.
sourcePaths This property is required. List<String>
The list of source paths in the source remote repository.
id This property is required. string
The ID of the source remote repository.
ref This property is required. string
The reference of the source remote repository.
sourcePaths This property is required. string[]
The list of source paths in the source remote repository.
id This property is required. str
The ID of the source remote repository.
ref This property is required. str
The reference of the source remote repository.
source_paths This property is required. Sequence[str]
The list of source paths in the source remote repository.
id This property is required. String
The ID of the source remote repository.
ref This property is required. String
The reference of the source remote repository.
sourcePaths This property is required. 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 v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot