### Description

Allow users to re-use recent DagRun configurations upon running a DAG.
This can be achieved by adding a dropdown that contains some information about recent configurations. When user selects an item, the relevant JSON configuration can be pasted to the "Configuration JSON" textbox.
<img width="692" alt="Screen Shot 2022-11-16 at 16 22 30" src="https://user-images.githubusercontent.com/39705397/202209536-c709ec75-c768-48ab-97d4-82b02af60569.png">
<img width="627" alt="Screen Shot 2022-11-16 at 16 22 38" src="https://user-images.githubusercontent.com/39705397/202209553-08828521-dba2-4e83-8e2a-6dec850086de.png">
<img width="612" alt="Screen Shot 2022-11-16 at 16 38 40" src="https://user-images.githubusercontent.com/39705397/202209755-0946521a-e1a5-44cb-ae74-d43ca3735f31.png">


### Use case/motivation

Commonly, DAGs are triggered using repetitive configurations. Sometimes the same configuration is used for triggering a DAG, and sometimes, the configuration differs by just a few parameters. 

This interaction forces a user to store the templates he uses somewhere on his machine or to start searching for the configuration he needs in `dagrun/list/`, which does take extra time.

It will be handy to offer a user an option to select one of the recent configurations upon running a DAG.

### 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)

"""Mark task as failed."""
        args = request.form
        dag_id = args.get("dag_id")
        task_id = args.get("task_id")
        run_id = args.get("dag_run_id")
        if "map_index" not in args:
            map_indexes: list[int] | None = None
        else:
            map_indexes = args.getlist("map_index", type=int)
        origin = get_safe_url(args.get("origin"))
        upstream = to_boolean(args.get("upstream"))
        downstream = to_boolean(args.get("downstream"))
        future = to_boolean(args.get("future"))
        past = to_boolean(args.get("past"))
        return self._mark_task_instance_state(
            dag_id=dag_id,
            run_id=run_id,
            task_id=task_id,
            map_indexes=map_indexes,
            origin=origin,
            upstream=upstream,
            downstream=downstream,
            future=future,
            past=past,
            state=TaskInstanceState.FAILED,
        )