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# Subworkflow Deployment Node

> Execute deployed workflows as subworkflows within parent workflows.

`vellum.workflows.nodes.SubworkflowDeploymentNode`

Used to execute a deployed Workflow as a subworkflow within another workflow. This allows you to compose workflows from other deployed workflows.

### Attributes

**`deployment`** `Union[UUID, str]` — required

Either the Workflow Deployment's UUID or its name

---

**`subworkflow_inputs`** `Dict[str, Any]` — required

The inputs for the Subworkflow. Supports:

* Strings
* Numbers (float)
* Chat History (List\[ChatMessage])
* JSON objects (Dict\[str, Any])

---

**`release_tag`** `str` — default: LATEST

The release tag to use for the Workflow Execution

---

**`external_id`** `Optional[str]`

The external ID to use for the Workflow Execution

---

**`expand_meta`** `Optional[WorkflowExpandMetaRequest]`

An optionally specified configuration used to opt in to including additional metadata about this workflow execution in the API response. Corresponding values will be returned under the execution\_meta key within NODE events in the response stream. See [Execute Workflow: Expand Meta](/developers/client-sdk/workflows/execute-workflow#request.body.expand_meta).

---

**`metadata`** `Optional[Dict[str, Optional[Any]]]`

The metadata to use for the Workflow Execution

---

**`request_options`** `Optional[RequestOptions]`

The request options to use for the Workflow Execution

---

### Outputs

The outputs of this node are determined by the outputs defined in the deployed workflow. Each output from the workflow will be streamed through this node.

**`Example Usage`**

```python title="Example Usage"
from vellum import ChatMessage, WorkflowExpandMetaRequest
from vellum.workflows.nodes import SubworkflowDeploymentNode

class MySubworkflowNode(SubworkflowDeploymentNode):
    deployment = "customer_support_workflow"  # or UUID("...")
    subworkflow_inputs = {
        "user_query": "How do I reset my password?",
        "chat_history": [
            ChatMessage(role="USER", text="Hi there"),
            ChatMessage(role="ASSISTANT", text="Hello! How can I help?")
        ],
        "user_metadata": {
            "user_id": "123",
            "account_type": "premium"
        },
        "priority_score": 0.8
    }
    release_tag = "production"
    external_id = "support-ticket-456"
    expand_meta = WorkflowExpandMetaRequest(
        include_inputs=True,
        include_outputs=True
    )
    metadata = {
        "source": "mobile_app",
        "region": "us-west"
    }
```

**`Streaming Example`**

```python title="Streaming Example"
# Outputs are streamed as they're generated by the workflow
for output in node.run():
    if output.is_streaming:
        print(f"Received partial output for {output.name}: {output.delta}")
    elif output.is_fulfilled:
        print(f"Received final output for {output.name}: {output.value}")
```

**`Error Handling Example`**

```python title="Error Handling Example"
try:
    for output in node.run():
        process_output(output)
except NodeException as e:
    if e.code == VellumErrorCode.INVALID_INPUTS:
        print("Invalid input provided to workflow")
    elif e.code == VellumErrorCode.INTERNAL_ERROR:
        print("Internal workflow error occurred")
    else:
        raise
```

> Execute deployed workflows as subworkflows within parent workflows.