See the supported connectors for Application Integration.

Vertex AI - Predict task

The Vertex AI - Predict task lets you perform an online prediction. Online predictions are synchronous requests made to a model endpoint. You can use online predictions when making requests in response to application inputs or when you require timely inferences.

Vertex AI is a Google Cloud service that allows you to train and deploy ML models and AI applications, and customize large language models (LLMs) for use in your AI-powered applications.

Before you begin

Ensure that you perform the following tasks in your Google Cloud project before configuring the Vertex AI - Predict task:

Enable the Vertex AI API (aiplatform.googleapis.com).
Enable the Vertex AI API
Deploy the model resource to the endpoint.
Create an authentication profile. Application Integration uses an authentication profile to connect to an authentication endpoint for the Vertex AI - Predict task.
Note: If you're creating an authentication profile of Service account type, then ensure that the service account is assigned with the IAM role that contains the following IAM permission(s):
- aiplatform.endpoints.predict
To know about IAM permissions and the predefined IAM roles that grant them, see IAM permissions reference.

For information about granting additional roles or permissions to a service account, see Granting, changing, and revoking access.
Ensure that VPC Service Controls is NOT setup for Application Integration in your Google Cloud project.
Warning: Vertex AI - Predict task will not function or will stop functioning if VPC Service Controls is setup for Application Integration in your Google Cloud project.

Configure the Vertex AI - Predict task

In the Google Cloud console, go to the Application Integration page.
Go to Application Integration
In the navigation menu, click Integrations.
The Integrations page appears listing all the integrations available in the Google Cloud project.
Select an existing integration or click Create integration to create a new one.
If you are creating a new integration:
1. Enter a name and description in the Create Integration pane.
2. Select a region for the integration.
  Note: The Regions dropdown only lists the regions provisioned in your Google Cloud project. To provision a new region, Click Enable Region. See Enable new region for more information.
3. Select a service account for the integration. You can change or update the service account details of an integration any time from the Integration summary pane in the integration toolbar.
  Note: The option to select a service account is displayed only if you have enabled integration governance for the selected region.
4. Click Create.
This opens the integration in the integration editor.
In the integration editor navigation bar, click Tasks to view the list of available tasks and connectors.
Click and place the Vertex AI - Predict element in the integration editor.
Click the Vertex AI - Predict element on the designer to view the Vertex AI - Predict task configuration pane.
Go to Authentication, and select an existing authentication profile that you want to use.
Optional. If you have not created an authentication profile prior to configuring the task, Click + New authentication profile and follow the steps as mentioned in Create a new authentication profile.
Go to Task Input, and configure the displayed inputs fields using the following Task input parameters table.
Changes to the inputs fields are saved automatically.

Task input parameters

The following table describes the input parameters of the Vertex AI - Predict task:

Property	Data type	Description
Region	String	Model endpoint location. For example: `us` - United States.
ProjectsId	String	Your Google Cloud project ID.
Endpoint	String	The name of the endpoint requested to serve the prediction.
Request	JSON	See request JSON structure.

Task output

The Vertex AI - Predict task returns a response containing the prediction.

Error handling strategy

An error handling strategy for a task specifies the action to take if the task fails due to a temporary error. For information about how to use an error handling strategy, and to know about the different types of error handling strategies, see Error handling strategies.

Quotas and limits

For information about quotas and limits, see Quotas and limits.

What's next

For information about how to use the Vertex AI task with a pre-existing model, see AI powered applications with Application Integration and Vertex AI.
To learn how to use Vertex AI in Application Integration, see Enhancing your business integration flows with Vertex AI.
Test and publish your integration.
Add a Data Mapping task.
Learn about all supported tasks and triggers.