### Apache Airflow Provider(s)

databricks

### Versions of Apache Airflow Providers

apache-airflow-providers-databricks==1!2.0.2


### Apache Airflow version

2.1.4 (latest released)

### Operating System

Debian GNU/Linux 11 (bullseye)

### Deployment

Docker-Compose

### Deployment details

Running local deployment using Astronomer CLI

### What happened

When calling the `get_run_state` method from the `DatabricksHook`, I get the following error:

`TypeError: Object of type RunState is not JSON serializable`

I think this is due to [the method returning a RunState custom class](https://github.com/apache/airflow/blob/main/airflow/providers/databricks/hooks/databricks.py#L275) as opposed to a `str` like the rest of the methods in the databricks hook (i.e. `get_job_id`, `get_run_page_url`, etc.)

### What you expected to happen

When calling the `get_run_state` method, simply return the `result_state` or `state_message` [variables](https://github.com/apache/airflow/blob/main/airflow/providers/databricks/hooks/databricks.py#L287-L288) instead of the `RunState` class.

### How to reproduce

Create a dag that references a databricks deployment and use this task to see the error:

```
    from airflow.providers.databricks.hooks.databricks import DatabricksHook
    run_id = <insert run id from databricks ui here>

    def get_run_state(self, run_id: str):
           return self.hook.get_run_state(run_id=run_id)

    python_get_run_state = PythonOperator(
        task_id="python_get_run_state",
        python_callable=get_run_state,
        op_kwargs={
            "run_id": str(run_id)
        }
    )
```

### Anything else

_No response_

### 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/providers/databricks/hooks/databricks.py
self.log.info('Using AAD Token for SPN. ')
            auth = _TokenAuth(self._fill_aad_tokens(headers))
        elif self.databricks_conn.extra_dejson.get('use_azure_managed_identity', False):
            self.log.info('Using AAD Token for managed identity.')
            
            
            try:
                jsn = requests.get(
                    AZURE_METADATA_SERVICE_TOKEN_URL,
                    params={"api-version": "2021-02-01"},
                    headers={"Metadata": "true"},
                    timeout=2,
                ).json()
                if 'compute' not in jsn or 'azEnvironment' not in jsn['compute']:
                    raise AirflowException(
                        f"Was able to fetch some metadata, but it doesn't look like Azure Metadata: {jsn}"
                    )
            except (requests_exceptions.RequestException, ValueError) as e:
                raise AirflowException(f"Can't reach Azure Metadata Service: {e}")
            auth = _TokenAuth(self._fill_aad_tokens(headers))
        else:
            self.log.info('Using basic auth.')
            auth = (self.databricks_conn.login, self.databricks_conn.password)
        url = f'https://{self._parse_host(host)}/{endpoint}'
        if method == 'GET':
            request_func = requests.get
        elif method == 'POST':
            request_func = requests.post
        elif method == 'PATCH':
            request_func = requests.patch