Docs Home Pulumi IaC Pulumi ESC Pulumi Insights Pulumi Cloud Packages Tutorials
  1. Packages
  2. DataRobot
  3. API Docs
  4. CustomModelLlmValidation
DataRobot v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot

datarobot.CustomModelLlmValidation

Explore with Pulumi AI

DataRobot v0.9.0 published on Tuesday, Apr 8, 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;
Copy
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)
Copy
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
	})
}
Copy
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,
    };
});
Copy
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());
    }
}
Copy
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}
Copy

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 This property is required. string
The unique name of the resource.
args This property is required. CustomModelLlmValidationArgs
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 This property is required. 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 This property is required. string
The unique name of the resource.
args This property is required. CustomModelLlmValidationArgs
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 This property is required. CustomModelLlmValidationArgs
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. 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",
});
Copy
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"),
})
Copy
var customModelLlmValidationResource = new CustomModelLlmValidation("customModelLlmValidationResource", CustomModelLlmValidationArgs.builder()
    .deploymentId("string")
    .chatModelId("string")
    .modelId("string")
    .name("string")
    .predictionTimeout(0)
    .promptColumnName("string")
    .targetColumnName("string")
    .useCaseId("string")
    .build());
Copy
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")
Copy
const customModelLlmValidationResource = new datarobot.CustomModelLlmValidation("customModelLlmValidationResource", {
    deploymentId: "string",
    chatModelId: "string",
    modelId: "string",
    name: "string",
    predictionTimeout: 0,
    promptColumnName: "string",
    targetColumnName: "string",
    useCaseId: "string",
});
Copy
type: datarobot:CustomModelLlmValidation
properties:
    chatModelId: string
    deploymentId: string
    modelId: string
    name: string
    predictionTimeout: 0
    promptColumnName: string
    targetColumnName: string
    useCaseId: string
Copy

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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 This property is required. 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 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:
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 v0.9.0 published on Tuesday, Apr 8, 2025 by DataRobot, Inc.
datarobot-community/pulumi-datarobot