### Apache Airflow version

Other Airflow 2 version (please specify below)

### What happened

Greetings!
Recently I’ve faced a problem. It seems that assigning object, which can’t be serialized to JSON, to the dag_run.conf dict cause critical errors with UI.
After executing code example in "How to reproduce": 
Grid representation of the DAG breaks with following result:
<img width="800" alt="Pasted Graphic" src="https://github.com/apache/airflow/assets/79107237/872ccde5-500f-4484-a36c-dce6b7112286">
Browse -> DAG Runs also becomes unavailable.
<img width="800" alt="Pasted Graphic 1" src="https://github.com/apache/airflow/assets/79107237/b4e3df0c-5324-41dd-96f3-032e706ab7a9">
Dag itself continues to work correctly, this affects only UI graph and dagrun/list/
I suggest to use custom dictionary with restriction on setting non json values.

### What you think should happen instead

Raise an error

### How to reproduce

Execute following task. 
Composer 2 version 2.4.2
Airflow version 2.5.3
```
@task 
def test_task(**context):
    context['dag_run'].conf["test"] = np.int64(1234)
```

### Operating System

Ubuntu 20.04.6 LTS

### Versions of Apache Airflow Providers

_No response_

### Deployment

Google Cloud Composer

### Deployment details

_No response_

### 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)

"DagRun Finished: dag_id=%s, execution_date=%s, run_id=%s, "
                "run_start_date=%s, run_end_date=%s, run_duration=%s, "
                "state=%s, external_trigger=%s, run_type=%s, "
                "data_interval_start=%s, data_interval_end=%s, dag_hash=%s"
            )
            self.log.info(
                msg,
                self.dag_id,
                self.execution_date,
                self.run_id,
                self.start_date,
                self.end_date,
                (self.end_date - self.start_date).total_seconds()
                if self.start_date and self.end_date
                else None,
                self._state,
                self.external_trigger,
                self.run_type,
                self.data_interval_start,
                self.data_interval_end,
                self.dag_hash,
            )
            session.flush()
        self._emit_true_scheduling_delay_stats_for_finished_state(finished_tis)
        self._emit_duration_stats_for_finished_state()
        session.merge(self)
        
        return schedulable_tis, callback
    @provide_session
    def task_instance_scheduling_decisions(self, session: Session = NEW_SESSION) -> TISchedulingDecision: