### 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)

context = create_context(k)
        result = k.execute(context)
        assert result is not None
        assert k.pod.metadata.labels == {
            "fizz": "buzz",
            "test_label": test_label,
            "airflow_version": mock.ANY,
            "airflow_kpo_in_cluster": "False",
            "dag_id": "dag",
            "run_id": "manual__2016-01-01T0100000100-da4d1ce7b",
            "kubernetes_pod_operator": "True",
            "task_id": mock.ANY,
            "try_number": "1",
        }
        assert k.pod.spec.containers[0].env == [k8s.V1EnvVar(name="env_name", value="value")]
        assert result == {"hello": "world"}
    def test_full_pod_spec(self, test_label, mock_get_connection):
        pod_spec = k8s.V1Pod(
            metadata=k8s.V1ObjectMeta(
                labels={"test_label": test_label, "fizz": "buzz"}, namespace="default", name="test-pod"
            ),
            spec=k8s.V1PodSpec(
                containers=[
                    k8s.V1Container(
                        name="base",
                        image="perl",
                        command=["/bin/bash"],
                        args=["-c", 'echo {\\"hello\\" : \\"world\\"} | cat > /airflow/xcom/return.json'],
                        env=[k8s.V1EnvVar(name="env_name", value="value")],
                    )