### What do you see as an issue?

The [/dags/{dag_id}/details](https://airflow.apache.org/docs/apache-airflow/stable/stable-rest-api-ref.html#operation/post_set_task_instances_state) endpoint of the REST API does not return all of the keys that are listed in the documentation. If I run `curl -X GET localhost:8080/api/v1/dags/{my_dag}/details`, then compare the results with the results in the documentation, you can see the following missing keys:

```python
>>> for key in docs.keys():
...     if not key in actual.keys():
...             print(key)
...
root_dag_id
last_parsed_time
last_pickled
last_expired
scheduler_lock
timetable_description
has_task_concurrency_limits
has_import_errors
next_dagrun
next_dagrun_data_interval_start
next_dagrun_data_interval_end
next_dagrun_create_after
template_search_path
```

### Solving the problem

Either remove these keys from the documentation or fix the API endpoint

### Anything else

_No response_

### Are you willing to submit 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)

if dag.partial:
                tis = [ti for ti in tis if not ti.state == State.NONE]
            ti = tis[-1]  
            ti.task = dag.get_task(ti.task_id)
            context = ti.get_template_context(session=session)
            context["reason"] = reason
            return callbacks, context
        return None
    @provide_session
    def handle_callback(self, dagrun: DagRun, success=True, reason=None, session=NEW_SESSION):
        """
        Triggers on_failure_callback or on_success_callback as appropriate.
        This method gets the context of a single TaskInstance part of this DagRun
        and passes that to the callable along with a 'reason', primarily to
        differentiate DagRun failures.
        .. note: The logs end up in
            ``$AIRFLOW_HOME/logs/scheduler/latest/PROJECT/DAG_FILE.py.log``
        :param dagrun: DagRun object
        :param success: Flag to specify if failure or success callback should be called
        :param reason: Completion reason
        :param session: Database session
        """
        callbacks, context = DAG.fetch_callback(
            dag=self, dag_run_id=dagrun.run_id, success=success, reason=reason, session=session
        ) or (None, None)
        DAG.execute_callback(callbacks, context, self.dag_id)
    @classmethod
    def execute_callback(cls, callbacks: list[Callable] | None, context: Context | None, dag_id: str):