### Apache Airflow version

2.1.3

### Operating System

ContainerOS

### Versions of Apache Airflow Providers

apache-airflow-providers-amazon==2.1.0
apache-airflow-providers-celery==2.0.0
apache-airflow-providers-cncf-kubernetes==2.0.2
apache-airflow-providers-databricks==2.0.1
apache-airflow-providers-docker==2.1.0
apache-airflow-providers-elasticsearch==2.0.2
apache-airflow-providers-ftp==2.0.0
apache-airflow-providers-google==5.0.0
apache-airflow-providers-grpc==2.0.0
apache-airflow-providers-hashicorp==2.0.0
apache-airflow-providers-http==2.0.0
apache-airflow-providers-imap==2.0.0
apache-airflow-providers-microsoft-azure==3.1.0
apache-airflow-providers-mysql==2.1.0
apache-airflow-providers-papermill==2.0.1
apache-airflow-providers-postgres==2.0.0
apache-airflow-providers-redis==2.0.0
apache-airflow-providers-sendgrid==2.0.0
apache-airflow-providers-sftp==2.1.0
apache-airflow-providers-slack==4.0.0
apache-airflow-providers-sqlite==2.0.0
apache-airflow-providers-ssh==2.1.0

### Deployment

Official Apache Airflow Helm Chart

### Deployment details

Official Helm Chart on GKE using CeleryKubernetesExecutor.

### What happened

I'm unable to Run Tasks from the UI when using CeleryKubernetesExecutor. It just shows the error "Only works with the Celery or Kubernetes executors, sorry". 
<img width="1792" alt="Captura de Pantalla 2021-09-22 a la(s) 17 00 30" src="https://user-images.githubusercontent.com/2586758/134413668-5b638941-bb50-44ff-9349-d53326d1f489.png">




### What you expected to happen

It should be able to run Tasks from the UI when using CeleryKubernetesExecutor, as it only is a "selective superset" (based on queue) of both the Celery and Kubernetes executors.

### How to reproduce

1. Run an Airflow instance with the CeleryKubernetes executor.
2. Go to any DAG
3. Select a Task
4. Press the "Run" button.
5. Check the error.

### Anything else

I will append an example PR as a comment.

### Are you willing to submit 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)

airflow/www/views.py
dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        num_runs = request.args.get('num_runs', type=int)
        if num_runs is None:
            num_runs = conf.getint('webserver', 'default_dag_run_display_number')
        try:
            base_date = timezone.parse(request.args["base_date"])
        except (KeyError, ValueError):
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        with create_session() as session:
            dag_runs = (
                session.query(DagRun)
                .filter(DagRun.dag_id == dag.dag_id, DagRun.execution_date <= base_date)
                .order_by(DagRun.execution_date.desc())
                .limit(num_runs)
                .all()
            )
            dag_runs = {dr.execution_date: alchemy_to_dict(dr) for dr in dag_runs}
            tree_data = self._get_tree_data(dag_runs, dag, base_date, session=session)
        
        return htmlsafe_json_dumps(tree_data, separators=(',', ':'))
    @expose('/robots.txt')
    @action_logging
    def robots(self):
        """
        Returns a robots.txt file for blocking certain search engine crawlers. This mitigates some
        of the risk associated with exposing Airflow to the public internet, however it does not
        address the real security risks associated with such a deployment.
        """
        return send_from_directory(current_app.static_folder, 'robots.txt')
class ConfigurationView(AirflowBaseView):