### Description

Replace the existing selects with multi-selects that allow you to filter multiple DAG run states and types at the same time, somewhat similar to my prototype:

![image](https://github.com/apache/airflow/assets/1842905/c4ec0793-1ccb-417d-989c-781997416f97)


### Use case/motivation

I'm not sure if it is just me, but sometimes I wish I was able to show multiple DAG run states, especially `running` and `failed`, at the same time. 
This would be especially helpful for busy DAGs on which I want to clear a few failed runs. Without the multi-select, if I switch from `failed` to `running` DAG runs, I need to orient myself again to find the run I just cleared (assuming there are lots of other running DAG runs). _With_ the multi-select, the DAG run I just cleared stays in the same spot and I can check the logs, while clearing some other failed runs.

I'm not sure we need a multi-select for DAG run types as well. I'd tend to say no, but maybe someone else has a use-case for that.

### Related issues

_No response_

### Are you willing to submit a PR?

- [X] 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)

return {
            "extra_links": [],
            "has_outlet_datasets": has_outlet_datasets,
            "id": task_id,
            "instances": [],
            "is_mapped": False,
            "label": task_id,
            "operator": "EmptyOperator",
            "trigger_rule": "all_success",
        }
    assert resp.status_code == 200, resp.json
    assert resp.json == {
        "dag_runs": [],
        "groups": {
            "children": [
                _expected_task_details("task1", False),
                _expected_task_details("task2", False),
                _expected_task_details("task3", True),
                _expected_task_details("task4", True),
            ],
            "id": None,
            "instances": [],
            "label": None,
        },
        "ordering": ["data_interval_end", "execution_date"],
    }
@pytest.mark.need_serialized_dag
def test_next_run_datasets(admin_client, dag_maker, session, app, monkeypatch):