### Apache Airflow version

2.7.0rc1

### What happened

As per https://github.com/apache/airflow/pull/31583, now we can only run DAG with config from UI if DAG has params, however, if a DAG is using dag_run.conf there is no way to run with config from UI and as dag_run.conf is not deprecated most of the users will be impacted by this

@hussein-awala  also mentioned it in his [voting](https://lists.apache.org/thread/zd9ppxw1xwxsl66w0tyw1wch9flzb03w)

### What you think should happen instead

I think there should be a way to provide param values from UI when dag_run.conf is used in DAG

### How to reproduce

Use below DAG in 2.7.0rc and you will notice there is no way to provide conf value from airflow UI

DAG CODE

```
from airflow.models import DAG
from airflow.operators.bash import BashOperator
from airflow.operators.python import PythonOperator
from airflow.utils.dates import days_ago

dag = DAG(
dag_id="trigger_target_dag",
default_args={"start_date": days_ago(2), "owner": "Airflow"},
tags=["core"],
schedule_interval=None, # This must be none so it's triggered by the controller
is_paused_upon_creation=False, # This must be set so other workers can pick this dag up. mabye it's a bug idk
)

def run_this_func(**context):
print(
f"Remotely received value of {context['dag_run'].conf['message']} for key=message "
)

run_this = PythonOperator(
task_id="run_this",
python_callable=run_this_func,
dag=dag,
)

bash_task = BashOperator(
task_id="bash_task",
bash_command='echo "Here is the message: $message"',
env={"message": '{{ dag_run.conf["message"] if dag_run else "" }}'},
dag=dag,
)
```

### Operating System

MAS os Monterey

### Versions of Apache Airflow Providers

_No response_

### Deployment

Astronomer

### Deployment details

_No response_

### Anything else

_No response_

### Are you willing to submit PR?

- [ ] Yes I am willing to submit a PR!

### Code of Conduct

- [X] I agree to follow this project's [Code of Conduct](https://github.com/apache/airflow/blob/main/CODE_OF_CONDUCT.md)

.join(TaskInstance.task_instance_note, isouter=True)
        .where(
            TaskInstance.dag_id == dag.dag_id,
            TaskInstance.run_id.in_([dag_run.run_id for dag_run in dag_runs]),
        )
        .group_by(TaskInstance.task_id, TaskInstance.run_id, TaskInstance.state, TaskInstance._try_number)
        .order_by(TaskInstance.task_id, TaskInstance.run_id)
    )
    grouped_tis = {task_id: list(tis) for task_id, tis in itertools.groupby(query, key=lambda ti: ti.task_id)}
    sort_order = conf.get("webserver", "grid_view_sorting_order", fallback="topological")
    if sort_order == "topological":
        sort_children_fn = lambda task_group: task_group.topological_sort()
    elif sort_order == "hierarchical_alphabetical":
        sort_children_fn = lambda task_group: task_group.hierarchical_alphabetical_sort()
    else:
        raise AirflowConfigException(f"Unsupported grid_view_sorting_order: {sort_order}")
    def task_group_to_grid(item, grouped_tis, *, is_parent_mapped: bool):
        if not isinstance(item, TaskGroup):
            def _get_summary(task_instance):
                return {
                    "task_id": task_instance.task_id,
                    "run_id": task_instance.run_id,
                    "state": task_instance.state,
                    "queued_dttm": task_instance.queued_dttm,
                    "start_date": task_instance.start_date,
                    "end_date": task_instance.end_date,
                    "try_number": wwwutils.get_try_count(task_instance._try_number, task_instance.state),
                    "note": task_instance.note,
                }
            def _mapped_summary(ti_summaries):