### 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)

map_indexes = args.getlist("map_index", type=int)
        upstream = to_boolean(args.get("upstream"))
        downstream = to_boolean(args.get("downstream"))
        future = to_boolean(args.get("future"))
        past = to_boolean(args.get("past"))
        origin = origin or url_for("Airflow.index")
        dag = get_airflow_app().dag_bag.get_dag(dag_id)
        if not dag:
            msg = f"DAG {dag_id} not found"
            return redirect_or_json(origin, msg, status="error", status_code=404)
        try:
            task = dag.get_task(task_id)
        except airflow.exceptions.TaskNotFound:
            msg = f"Task {task_id} not found"
            return redirect_or_json(origin, msg, status="error", status_code=404)
        task.dag = dag
        if state not in (
            "success",
            "failed",
        ):
            msg = f"Invalid state {state}, must be either 'success' or 'failed'"
            return redirect_or_json(origin, msg, status="error", status_code=400)
        latest_execution_date = dag.get_latest_execution_date()
        if not latest_execution_date:
            msg = f"Cannot mark tasks as {state}, seem that dag {dag_id} has never run"
            return redirect_or_json(origin, msg, status="error", status_code=400)
        if map_indexes is None:
            tasks: list[Operator] | list[tuple[Operator, int]] = [task]
        else:
            tasks = [(task, map_index) for map_index in map_indexes]