### Overview
Some Executors have their own first class CLI commands (now that’s hardcoding/coupling!) which setup or modify various components related to that Executor.
### Examples
- **5a**) Celery Executor commands: https://github.com/apache/airflow/blob/27e2101f6ee5567b2843cbccf1dca0b0e7c96186/airflow/cli/cli_parser.py#L1689-L1734
- **5b**) Kubernetes Executor commands: https://github.com/apache/airflow/blob/27e2101f6ee5567b2843cbccf1dca0b0e7c96186/airflow/cli/cli_parser.py#L1754-L1771
- **5c**) Default CLI parser has hardcoded logic for Celery and Kubernetes Executors specifically: https://github.com/apache/airflow/blob/27e2101f6ee5567b2843cbccf1dca0b0e7c96186/airflow/cli/cli_parser.py#L63-L99
### Proposal
Update the BaseExecutor interface with a pluggable mechanism to vend CLI `GroupCommands` and parsers. Executor subclasses would then implement these methods, if applicable, which would then be called to fetch commands and parsers from within Airflow Core cli parser code. We would then migrate the existing Executor CLI code from cli_parser to the respective Executor class.

Pseudo-code example for vending `GroupCommand`s:
```python
# Existing code in cli_parser.py
...
airflow_commands: List[CLICommand] = [
GroupCommand(
        name='dags',
        help='Manage DAGs',
        subcommands=DAGS_COMMANDS,
    ),
    ...
]
# New code to add groups vended by executor classes
executor_cls, _ = ExecutorLoader.import_executor_cls(conf.get('core', 'EXECUTOR'))
airflow_commands.append(executor_cls.get_cli_group_commands())
...
```
self,
        key: TaskInstanceKey,
        command: CommandType,
        queue: str | None = None,
        executor_config: Any | None = None,
    ) -> None:  
        """
        This method will execute the command asynchronously.
        :param key: Unique key for the task instance
        :param command: Command to run
        :param queue: name of the queue
        :param executor_config: Configuration passed to the executor.
        """
        raise NotImplementedError()
    def get_task_log(self, ti: TaskInstance, try_number: int) -> tuple[list[str], list[str]]:
        """
        This method can be implemented by any child class to return the task logs.
        :param ti: A TaskInstance object
        :param try_number: current try_number to read log from
        :return: tuple of logs and messages
        """
        return [], []
    def end(self) -> None: