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# vertex
# `prefect_gcp.workers.vertex`
\
Module containing the custom worker used for executing flow runs as Vertex AI Custom Jobs.
Get started by creating a Cloud Run work pool:
```bash theme={null}
prefect work-pool create 'my-vertex-pool' --type vertex-ai
```
Then start a Cloud Run worker with the following command:
```bash theme={null}
prefect worker start --pool 'my-vertex-pool'
```
## Configuration
Read more about configuring work pools
[here](https://docs.prefect.io/3.0/deploy/infrastructure-concepts/work-pools).
## Classes
### `VertexAIWorkerVariables`
Default variables for the Vertex AI worker.
The schema for this class is used to populate the `variables` section of the default
base job template.
### `VertexAIWorkerJobConfiguration`
Configuration class used by the Vertex AI Worker to create a Job.
An instance of this class is passed to the Vertex AI Worker's `run` method
for each flow run. It contains all information necessary to execute
the flow run as a Vertex AI Job.
**Attributes:**
* `region`: The region where the Vertex AI Job resides.
* `credentials`: The GCP Credentials used to connect to Vertex AI.
* `job_spec`: The Vertex AI Job spec used to create the Job.
* `job_watch_poll_interval`: The interval between GCP API calls to check Job state.
**Methods:**
#### `job_name`
```python theme={null}
job_name(self) -> str
```
The name can be up to 128 characters long and can be consist of any UTF-8 characters. Reference:
[https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.CustomJob#google\_cloud\_aiplatform\_CustomJob\_display\_name](https://cloud.google.com/python/docs/reference/aiplatform/latest/google.cloud.aiplatform.CustomJob#google_cloud_aiplatform_CustomJob_display_name)
#### `prepare_for_flow_run`
```python theme={null}
prepare_for_flow_run(self, flow_run: 'FlowRun', deployment: Optional['DeploymentResponse'] = None, flow: Optional['Flow'] = None, work_pool: Optional['WorkPool'] = None, worker_name: Optional[str] = None, worker_id: Optional['UUID'] = None)
```
#### `project`
```python theme={null}
project(self) -> str
```
property for accessing the project from the credentials.
### `VertexAIWorkerResult`
Contains information about the final state of a completed process
### `VertexAIWorker`
Prefect worker that executes flow runs within Vertex AI Jobs.
**Methods:**
#### `kill_infrastructure`
```python theme={null}
kill_infrastructure(self, infrastructure_pid: str, configuration: VertexAIWorkerJobConfiguration, grace_seconds: int = 30) -> None
```
Kill a Vertex AI Custom Job by cancelling it.
**Args:**
* `infrastructure_pid`: The full job name
(e.g., "projects/123/locations/us-central1/customJobs/456").
* `configuration`: The job configuration used to connect to GCP.
* `grace_seconds`: Not used for Vertex AI (GCP handles graceful shutdown).
**Raises:**
* `InfrastructureNotFound`: If the job doesn't exist.
#### `run`
```python theme={null}
run(self, flow_run: 'FlowRun', configuration: VertexAIWorkerJobConfiguration, task_status: Optional[anyio.abc.TaskStatus] = None) -> VertexAIWorkerResult
```
Executes a flow run within a Vertex AI Job and waits for the flow run
to complete.
**Args:**
* `flow_run`: The flow run to execute
* `configuration`: The configuration to use when executing the flow run.
* `task_status`: The task status object for the current flow run. If provided,
the task will be marked as started.
**Returns:**
* A result object containing information about the
final state of the flow run
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