## Documentation Index

Fetch the complete documentation index at: [/docs/llms.txt](/content/docs/llms.txt)

Use this file to discover all available pages before exploring further.

Add your Google Cloud Platform ProjectID and location to begin using the VertexAI API.

By adding this integration, your data may be sent to Google for certain actions within Arize AX (e.g., prompt playground) and your account may be billed for usage.

Certain models (such as **Claude Fable 5**) require **data retention mode** to be explicitly enabled in your Vertex AI account before they can be used.

## Add the Integration Using the Arize Skills

Add a VertexAI integration from your coding agent using the [Arize Skills](/content/docs/ax/agents/arize-skills/index.html):

Create a vertex integration called 'my-vertex' with the project id my-project, location us-central1 and arize integration key 12345

## Add the Integration from Arize AX

### Select VertexAI from the Providers List

### Create an Arize Integration Key

To verify ownership of your project form within Arize AX, we need to create a project access label on your GCP project. Arize AX will use this to ensure that the **Arize organization** you are running Vertex commands from has access to your **GCP project**. To create this go into your GCP and search for labels. Add a label with the key `arize-integration-key` and whatever value you want.

### Fill Out Your Integration Details

Add the GCP ProjectID, location, and project access label of the project you have the VertexAI API enabled in.

### Create a Custom IAM Role Using the Code Provided

1. Copy the following IAM role `gcloud` command to run in your GCP console:

Sample commands:

You must add your project ID to the commands below where it says `<my-project>`. The commands pulled from Arize AX have your project ID prefilled.

Create command (most cases):

```
gcloud iam roles create arizeApp --project=<my-project> \
       --title="Arize App" \
       --description="Custom IAM role for Arize App" \
       --permissions=aiplatform.endpoints.predict,resourcemanager.projects.get \
       --stage=ALPHA
```

Update migration (uncommon): If you have a pre-existing integration and need to update it to add an `arize-integration-key` label, change the `create` portion of the command to `update`.

```
gcloud iam roles update arizeApp --project=<my-project> \
       --title="Arize App" \
       --description="Custom IAM role for Arize App" \
       --permissions=aiplatform.endpoints.predict,resourcemanager.projects.get \
       --stage=ALPHA
```

2. Run the command in the GCP console:

### Assign the Custom Role to the Arize Service Account

In order for Arize to send requests to the VertexAI API in your project, you must assign the Arize App Service Account that role.

You will be using the Arize Service Account, you DO NOT NEED to create your own service account

1. Copy the following IAM permissions gcloud command to run in your GCP console:

2. Run the command in the GCP console:

### Advanced Settings

The Advanced Settings configuration pane

Expand the **Advanced Settings** section to configure the following:

- **Supports Function Calling** - Turn this on to allow the integration to use function calling features. This is on by default.
- **Authorized Orgs** - Configure which organizations have access to this integration.
- **Authorized Spaces** - Configure which spaces have access to this integration.

## Add the Integration

Finally check the box to agree to the terms and conditions, then select the **Add Integration** button to create the integration.