### Description

Add a process_line callback to KubernetesPodOperator 
Like https://github.com/apache/airflow/blob/main/airflow/providers/apache/beam/operators/beam.py#LL304C36-L304C57 the `BeamRunPythonPipelineOperator`, which allows the user to add stateful plugins based on the logging from docker job 

### Use case/motivation

I can add a plugin based on the logging and also allow cleanup on_kill based on the job creation log. 

### Related issues

_No response_

### Are you willing to submit a 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)

@pytest.fixture(autouse=True)
    def setup_tests(self, test_label):
        self.api_client = ApiClient()
        self.labels = {"test_label": test_label}
        self.expected_pod = {
            "apiVersion": "v1",
            "kind": "Pod",
            "metadata": {
                "namespace": "default",
                "name": ANY,
                "annotations": {},
                "labels": {
                    "test_label": test_label,
                    "kubernetes_pod_operator": "True",
                    "airflow_version": airflow_version.replace("+", "-"),
                    "airflow_kpo_in_cluster": "False",
                    "run_id": "manual__2016-01-01T0100000100-da4d1ce7b",
                    "dag_id": "dag",
                    "task_id": ANY,
                    "try_number": "1",
                },
            },