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DataRobot v0.8.18 published on Thursday, Mar 27, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.CustomModelLlmValidation

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DataRobot v0.8.18 published on Thursday, Mar 27, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

    Custom Model LLM Validation

    Example Usage

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

const example = new datarobot.CustomModelLlmValidation("example", {
    deploymentId: datarobot_deployment.example.id,
    promptColumnName: "promptText",
    targetColumnName: "resultText",
    chatModelId: "111111111111",
    predictionTimeout: 100,
    useCaseId: datarobot.use_case.example.id,
});
export const exampleId = example.id;

    import pulumi
import pulumi_datarobot as datarobot

example = datarobot.CustomModelLlmValidation("example",
    deployment_id=datarobot_deployment["example"]["id"],
    prompt_column_name="promptText",
    target_column_name="resultText",
    chat_model_id="111111111111",
    prediction_timeout=100,
    use_case_id=datarobot["use_case"]["example"]["id"])
pulumi.export("exampleId", example.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 {
		example, err := datarobot.NewCustomModelLlmValidation(ctx, "example", &datarobot.CustomModelLlmValidationArgs{
			DeploymentId:      pulumi.Any(datarobot_deployment.Example.Id),
			PromptColumnName:  pulumi.String("promptText"),
			TargetColumnName:  pulumi.String("resultText"),
			ChatModelId:       pulumi.String("111111111111"),
			PredictionTimeout: pulumi.Int(100),
			UseCaseId:         pulumi.Any(datarobot.Use_case.Example.Id),
		})
		if err != nil {
			return err
		}
		ctx.Export("exampleId", example.ID())
		return nil
	})
}

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

return await Deployment.RunAsync(() => 
{
    var example = new Datarobot.CustomModelLlmValidation("example", new()
    {
        DeploymentId = datarobot_deployment.Example.Id,
        PromptColumnName = "promptText",
        TargetColumnName = "resultText",
        ChatModelId = "111111111111",
        PredictionTimeout = 100,
        UseCaseId = datarobot.Use_case.Example.Id,
    });

    return new Dictionary<string, object?>
    {
        ["exampleId"] = example.Id,
    };
});

    package generated_program;

import com.pulumi.Context;
import com.pulumi.Pulumi;
import com.pulumi.core.Output;
import com.pulumi.datarobot.CustomModelLlmValidation;
import com.pulumi.datarobot.CustomModelLlmValidationArgs;
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 example = new CustomModelLlmValidation("example", CustomModelLlmValidationArgs.builder()
            .deploymentId(datarobot_deployment.example().id())
            .promptColumnName("promptText")
            .targetColumnName("resultText")
            .chatModelId("111111111111")
            .predictionTimeout(100)
            .useCaseId(datarobot.use_case().example().id())
            .build());

        ctx.export("exampleId", example.id());
    }
}

    resources:
  example:
    type: datarobot:CustomModelLlmValidation
    properties:
      deploymentId: ${datarobot_deployment.example.id}
      # Optional
      promptColumnName: promptText
      targetColumnName: resultText
      chatModelId: '111111111111'
      predictionTimeout: 100
      useCaseId: ${datarobot.use_case.example.id}
outputs:
  exampleId: ${example.id}

    Create CustomModelLlmValidation Resource

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

    Constructor syntax

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

@overload
def CustomModelLlmValidation(resource_name: str,
                             opts: Optional[ResourceOptions] = None,
                             deployment_id: Optional[str] = None,
                             chat_model_id: Optional[str] = None,
                             model_id: Optional[str] = None,
                             name: Optional[str] = None,
                             prediction_timeout: Optional[int] = None,
                             prompt_column_name: Optional[str] = None,
                             target_column_name: Optional[str] = None,
                             use_case_id: Optional[str] = None)
    func NewCustomModelLlmValidation(ctx *Context, name string, args CustomModelLlmValidationArgs, opts ...ResourceOption) (*CustomModelLlmValidation, error)
    public CustomModelLlmValidation(string name, CustomModelLlmValidationArgs args, CustomResourceOptions? opts = null)
    public CustomModelLlmValidation(String name, CustomModelLlmValidationArgs args)
public CustomModelLlmValidation(String name, CustomModelLlmValidationArgs args, CustomResourceOptions options)

    type: datarobot:CustomModelLlmValidation
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 CustomModelLlmValidationArgs
    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 CustomModelLlmValidationArgs
    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 CustomModelLlmValidationArgs
    The arguments to resource properties.
    opts ResourceOption
    Bag of options to control resource's behavior.
    name string
    The unique name of the resource.
    args CustomModelLlmValidationArgs
    The arguments to resource properties.
    opts CustomResourceOptions
    Bag of options to control resource's behavior.
    name String
    The unique name of the resource.
    args CustomModelLlmValidationArgs
    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 customModelLlmValidationResource = new Datarobot.CustomModelLlmValidation("customModelLlmValidationResource", new()
{
    DeploymentId = "string",
    ChatModelId = "string",
    ModelId = "string",
    Name = "string",
    PredictionTimeout = 0,
    PromptColumnName = "string",
    TargetColumnName = "string",
    UseCaseId = "string",
});

    example, err := datarobot.NewCustomModelLlmValidation(ctx, "customModelLlmValidationResource", &datarobot.CustomModelLlmValidationArgs{
	DeploymentId:      pulumi.String("string"),
	ChatModelId:       pulumi.String("string"),
	ModelId:           pulumi.String("string"),
	Name:              pulumi.String("string"),
	PredictionTimeout: pulumi.Int(0),
	PromptColumnName:  pulumi.String("string"),
	TargetColumnName:  pulumi.String("string"),
	UseCaseId:         pulumi.String("string"),
})

    var customModelLlmValidationResource = new CustomModelLlmValidation("customModelLlmValidationResource", CustomModelLlmValidationArgs.builder()
    .deploymentId("string")
    .chatModelId("string")
    .modelId("string")
    .name("string")
    .predictionTimeout(0)
    .promptColumnName("string")
    .targetColumnName("string")
    .useCaseId("string")
    .build());

    custom_model_llm_validation_resource = datarobot.CustomModelLlmValidation("customModelLlmValidationResource",
    deployment_id="string",
    chat_model_id="string",
    model_id="string",
    name="string",
    prediction_timeout=0,
    prompt_column_name="string",
    target_column_name="string",
    use_case_id="string")

    const customModelLlmValidationResource = new datarobot.CustomModelLlmValidation("customModelLlmValidationResource", {
    deploymentId: "string",
    chatModelId: "string",
    modelId: "string",
    name: "string",
    predictionTimeout: 0,
    promptColumnName: "string",
    targetColumnName: "string",
    useCaseId: "string",
});

    type: datarobot:CustomModelLlmValidation
properties:
    chatModelId: string
    deploymentId: string
    modelId: string
    name: string
    predictionTimeout: 0
    promptColumnName: string
    targetColumnName: string
    useCaseId: string

    CustomModelLlmValidation 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 CustomModelLlmValidation resource accepts the following input properties:

    DeploymentId string
    The ID of the custom model deployment.
    ChatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    ModelId string
    The ID of the model used in the deployment.
    Name string
    The name to use for the validated custom model.
    PredictionTimeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    PromptColumnName string
    The name of the column the custom model uses for prompt text input.
    TargetColumnName string
    The name of the column the custom model uses for prediction output.
    UseCaseId string
    The ID of the use case to associate with the validated custom model.
    DeploymentId string
    The ID of the custom model deployment.
    ChatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    ModelId string
    The ID of the model used in the deployment.
    Name string
    The name to use for the validated custom model.
    PredictionTimeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    PromptColumnName string
    The name of the column the custom model uses for prompt text input.
    TargetColumnName string
    The name of the column the custom model uses for prediction output.
    UseCaseId string
    The ID of the use case to associate with the validated custom model.
    deploymentId String
    The ID of the custom model deployment.
    chatModelId String
    The ID of the chat model to use for the custom model LLM validation.
    modelId String
    The ID of the model used in the deployment.
    name String
    The name to use for the validated custom model.
    predictionTimeout Integer
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName String
    The name of the column the custom model uses for prompt text input.
    targetColumnName String
    The name of the column the custom model uses for prediction output.
    useCaseId String
    The ID of the use case to associate with the validated custom model.
    deploymentId string
    The ID of the custom model deployment.
    chatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    modelId string
    The ID of the model used in the deployment.
    name string
    The name to use for the validated custom model.
    predictionTimeout number
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName string
    The name of the column the custom model uses for prompt text input.
    targetColumnName string
    The name of the column the custom model uses for prediction output.
    useCaseId string
    The ID of the use case to associate with the validated custom model.
    deployment_id str
    The ID of the custom model deployment.
    chat_model_id str
    The ID of the chat model to use for the custom model LLM validation.
    model_id str
    The ID of the model used in the deployment.
    name str
    The name to use for the validated custom model.
    prediction_timeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    prompt_column_name str
    The name of the column the custom model uses for prompt text input.
    target_column_name str
    The name of the column the custom model uses for prediction output.
    use_case_id str
    The ID of the use case to associate with the validated custom model.
    deploymentId String
    The ID of the custom model deployment.
    chatModelId String
    The ID of the chat model to use for the custom model LLM validation.
    modelId String
    The ID of the model used in the deployment.
    name String
    The name to use for the validated custom model.
    predictionTimeout Number
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName String
    The name of the column the custom model uses for prompt text input.
    targetColumnName String
    The name of the column the custom model uses for prediction output.
    useCaseId String
    The ID of the use case to associate with the validated custom model.

    Outputs

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

    Id string
    The provider-assigned unique ID for this managed resource.
    Id string
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.
    id string
    The provider-assigned unique ID for this managed resource.
    id str
    The provider-assigned unique ID for this managed resource.
    id String
    The provider-assigned unique ID for this managed resource.

    Look up Existing CustomModelLlmValidation Resource

    Get an existing CustomModelLlmValidation 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?: CustomModelLlmValidationState, opts?: CustomResourceOptions): CustomModelLlmValidation
    @staticmethod
def get(resource_name: str,
        id: str,
        opts: Optional[ResourceOptions] = None,
        chat_model_id: Optional[str] = None,
        deployment_id: Optional[str] = None,
        model_id: Optional[str] = None,
        name: Optional[str] = None,
        prediction_timeout: Optional[int] = None,
        prompt_column_name: Optional[str] = None,
        target_column_name: Optional[str] = None,
        use_case_id: Optional[str] = None) -> CustomModelLlmValidation
    func GetCustomModelLlmValidation(ctx *Context, name string, id IDInput, state *CustomModelLlmValidationState, opts ...ResourceOption) (*CustomModelLlmValidation, error)
    public static CustomModelLlmValidation Get(string name, Input<string> id, CustomModelLlmValidationState? state, CustomResourceOptions? opts = null)
    public static CustomModelLlmValidation get(String name, Output<String> id, CustomModelLlmValidationState state, CustomResourceOptions options)
    resources:  _:    type: datarobot:CustomModelLlmValidation    get:      id: ${id}
    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:
    ChatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    DeploymentId string
    The ID of the custom model deployment.
    ModelId string
    The ID of the model used in the deployment.
    Name string
    The name to use for the validated custom model.
    PredictionTimeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    PromptColumnName string
    The name of the column the custom model uses for prompt text input.
    TargetColumnName string
    The name of the column the custom model uses for prediction output.
    UseCaseId string
    The ID of the use case to associate with the validated custom model.
    ChatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    DeploymentId string
    The ID of the custom model deployment.
    ModelId string
    The ID of the model used in the deployment.
    Name string
    The name to use for the validated custom model.
    PredictionTimeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    PromptColumnName string
    The name of the column the custom model uses for prompt text input.
    TargetColumnName string
    The name of the column the custom model uses for prediction output.
    UseCaseId string
    The ID of the use case to associate with the validated custom model.
    chatModelId String
    The ID of the chat model to use for the custom model LLM validation.
    deploymentId String
    The ID of the custom model deployment.
    modelId String
    The ID of the model used in the deployment.
    name String
    The name to use for the validated custom model.
    predictionTimeout Integer
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName String
    The name of the column the custom model uses for prompt text input.
    targetColumnName String
    The name of the column the custom model uses for prediction output.
    useCaseId String
    The ID of the use case to associate with the validated custom model.
    chatModelId string
    The ID of the chat model to use for the custom model LLM validation.
    deploymentId string
    The ID of the custom model deployment.
    modelId string
    The ID of the model used in the deployment.
    name string
    The name to use for the validated custom model.
    predictionTimeout number
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName string
    The name of the column the custom model uses for prompt text input.
    targetColumnName string
    The name of the column the custom model uses for prediction output.
    useCaseId string
    The ID of the use case to associate with the validated custom model.
    chat_model_id str
    The ID of the chat model to use for the custom model LLM validation.
    deployment_id str
    The ID of the custom model deployment.
    model_id str
    The ID of the model used in the deployment.
    name str
    The name to use for the validated custom model.
    prediction_timeout int
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    prompt_column_name str
    The name of the column the custom model uses for prompt text input.
    target_column_name str
    The name of the column the custom model uses for prediction output.
    use_case_id str
    The ID of the use case to associate with the validated custom model.
    chatModelId String
    The ID of the chat model to use for the custom model LLM validation.
    deploymentId String
    The ID of the custom model deployment.
    modelId String
    The ID of the model used in the deployment.
    name String
    The name to use for the validated custom model.
    predictionTimeout Number
    The timeout in seconds for the prediction when validating a custom model. Defaults to 300.
    promptColumnName String
    The name of the column the custom model uses for prompt text input.
    targetColumnName String
    The name of the column the custom model uses for prediction output.
    useCaseId String
    The ID of the use case to associate with the validated custom model.

    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 v0.8.18 published on Thursday, Mar 27, 2025 by DataRobot, Inc.
    datarobot-community/pulumi-datarobot