### 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)

"""Runs Task Instance."""
        dag_id = request.form.get("dag_id")
        task_id = request.form.get("task_id")
        dag_run_id = request.form.get("dag_run_id")
        map_index = request.args.get("map_index", -1, type=int)
        origin = get_safe_url(request.form.get("origin"))
        dag: DAG = get_airflow_app().dag_bag.get_dag(dag_id)
        task = dag.get_task(task_id)
        ignore_all_deps = request.form.get("ignore_all_deps") == "true"
        ignore_task_deps = request.form.get("ignore_task_deps") == "true"
        ignore_ti_state = request.form.get("ignore_ti_state") == "true"
        executor = ExecutorLoader.get_default_executor()
        if not getattr(executor, "supports_ad_hoc_ti_run", False):
            msg = "Only works with the Celery, CeleryKubernetes or Kubernetes executors"
            return redirect_or_json(origin, msg, "error", 400)
        dag_run = dag.get_dagrun(run_id=dag_run_id)
        ti = dag_run.get_task_instance(task_id=task.task_id, map_index=map_index)
        if not ti:
            msg = "Could not queue task instance for execution, task instance is missing"
            return redirect_or_json(origin, msg, "error", 400)
        ti.refresh_from_task(task)
        
        dep_context = DepContext(
            deps=RUNNING_DEPS,
            ignore_all_deps=ignore_all_deps,
            ignore_task_deps=ignore_task_deps,