Bug: Optional `command` Component Input Not Working—Fails When Argument Not Passed or Empty (AzureML SDK v2)

- **Package Name**: `azure-ai-ml`
- **Package Version**: 1.27.1
- **Operating System**: Ubuntu 22.04.5 LTS
- **Python Version**: Python 3.12.11

**Describe the bug**
When defining a `command` component in AzureML SDK v2, a string input marked as `optional=True` with a default value *(or not)* does not behave as expected.
If I either omit the input or pass an empty string (""), I receive a `Request is invalid and/or missing fields. The Value field is required.` error, even though the documentation [states this is supported](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-inputs-outputs-pipeline?view=azureml-api-2&tabs=cli#:~:text=Learning%20examples%20repository.-,Define%20optional%20inputs,-By%20default%2C%20all).

**To Reproduce**
Steps to reproduce the behavior:
1. Define a component input as optional:

```python
from azure.ai.ml.entities import Input

inputs = {
"run_date" : Input(type=STRING),
"tags" : Input(type=STRING, optional=True, default="yolo")
}
```
2. Use the following command in the component:

```python
arguments = [
"--run_date ${{inputs.run_date}}",
"$[[--tags ${{inputs.tags}}]]"
]
```

3. Submit a job without specifying `"tags"` in `inputs_run`, or set `"tags": ""`.
```python
python_step_component.compute = COMPUTE_TARGET_RUN
inputs_run = {
"run_date": "2023-01-31",
}
# Submit the job
job = ml_client.jobs.create_or_update(
python_step_component(
**inputs_run
),
experiment_name="test-optional-args",

)
```

4. Error occurs:
```swift
HttpResponseError: (UserError) Request is invalid and/or missing fields.
(RequestInvalid) The Value field is required.
```

Click for full error

```swift

HttpResponseError Traceback (most recent call last)
Cell In[6], line 13
5 inputs_run = {
6 "run_date": "***redacted****",
7 "use_case": "***redacted****",
8 "kedro_pipeline_to_run": "***redacted****",
9 # "tags": "aa" # Optional, default is ''
10 }
12 # 4. Submit the component as a standalone job
---> 13 job = ml_client.jobs.create_or_update(
14 python_step_component(**inputs_run),
15 experiment_name="nptb_bpyn_mt"
16 )
18 print(f"Submitted job name: {job.name}")

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/core/tracing/decorator.py:138, in distributed_trace..decorator..wrapper_use_tracer(*args, **kwargs)
136 for key, value in span_attributes.items():
137 span.add_attribute(key, value) # type: ignore
--> 138 return func(*args, **kwargs)
139 else:
140 # Native path
141 config = {}

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/ai/ml/_telemetry/activity.py:371, in monitor_with_telemetry_mixin..monitor..wrapper(*args, **kwargs)
369 dimensions = {**parameter_dimensions, **(custom_dimensions or {})}
370 with log_activity(logger, activity_name or f.__name__, activity_type, dimensions) as activityLogger:
--> 371 return_value = f(*args, **kwargs)
372 if not parameter_dimensions:
373 # collect from return if no dimensions from parameter
374 activityLogger.activity_info.update(_collect_from_return_value(return_value))

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/ai/ml/operations/_job_operations.py:713, in JobOperations.create_or_update(self, job, description, compute, tags, experiment_name, skip_validation, **kwargs)
707 if (rest_job_resource.properties.job_type == RestJobType.PIPELINE) or (
708 hasattr(rest_job_resource.properties, "identity")
709 and (isinstance(rest_job_resource.properties.identity, UserIdentity))
710 ):
711 self._set_headers_with_user_aml_token(kwargs)
--> 713 result = self._create_or_update_with_different_version_api(rest_job_resource=rest_job_resource, **kwargs)
715 if is_local_run(result):
716 ws_base_url = self._all_operations.all_operations[
717 AzureMLResourceType.WORKSPACE
718 ]._operation._client._base_url

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/ai/ml/operations/_job_operations.py:761, in JobOperations._create_or_update_with_different_version_api(self, rest_job_resource, **kwargs)
758 if rest_job_resource.properties.job_type == RestJobType.COMMAND:
759 service_client_operation = self.service_client_01_2025_preview.jobs
--> 761 result = service_client_operation.create_or_update(
762 id=rest_job_resource.name,
763 resource_group_name=self._operation_scope.resource_group_name,
764 workspace_name=self._workspace_name,
765 body=rest_job_resource,
766 **kwargs,
767 )
769 return result

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/core/tracing/decorator.py:138, in distributed_trace..decorator..wrapper_use_tracer(*args, **kwargs)
136 for key, value in span_attributes.items():
137 span.add_attribute(key, value) # type: ignore
--> 138 return func(*args, **kwargs)
139 else:
140 # Native path
141 config = {}

File /anaconda/envs/nptb_bpyn/lib/python3.12/site-packages/azure/ai/ml/_restclient/v2025_01_01_preview/operations/_jobs_operations.py:632, in JobsOperations.create_or_update(self, resource_group_name, workspace_name, id, body, **kwargs)
630 map_error(status_code=response.status_code, response=response, error_map=error_map)
631 error = self._deserialize.failsafe_deserialize(_models.ErrorResponse, pipeline_response)
--> 632 raise HttpResponseError(response=response, model=error, error_format=ARMErrorFormat)
634 if response.status_code == 200:
635 deserialized = self._deserialize('JobBase', pipeline_response)

HttpResponseError: (UserError) Request is invalid and/or missing fields.
Code: UserError
Message: Request is invalid and/or missing fields.
Exception Details: (RequestInvalid) The Value field is required.
Code: RequestInvalid
Message: The Value field is required.
Additional Information:Type: ComponentName
Info: {
"value": "managementfrontend"
}Type: Correlation
Info: {
"value": {
"operation": "dfc7960391fcc82d77649e2257ea3d0c",
"request": "a7bae414cded0d35"
}
}Type: Environment
Info: {
"value": "eastus2"
}Type: Location
Info: {
"value": "eastus2"
}Type: Time
Info: {
"value": "2025-06-30T19:57:29.6789526+00:00"
}Type: InnerError
Info: {
"value": {
"code": "RequestInvalid",
"innerError": null
}
}Type: MessageFormat
Info: {
"value": "Request is invalid and/or missing fields."
}
```

5. If `"tags": "a"` (non-empty), the job works.

**Expected behavior**
I expect that omitting the `"tags"` input, or passing an empty string, would work without error, as `"tags"` is defined as optional with a default.

This matches the official [documentation](https://learn.microsoft.com/en-us/azure/machine-learning/how-to-manage-inputs-outputs-pipeline?view=azureml-api-2&tabs=cli#define-optional-inputs).

**Screenshots**
*N/A (errors shown in stack trace).*

**Additional context**
This issue blocks workflows that expect empty or missing values to use the default.