**Description**

Replace the Configuration JSON text-area with a form that has individual input fields for each key & value. This will remove the need for the user to provide a json object. See hashicorp vault's key-value secrets UI for an example of what this might look like:

![Screenshot 2020-09-21 at 12 06 03](https://user-images.githubusercontent.com/17148324/93759844-df04f680-fc02-11ea-8613-f3bcc0b22d09.png)
 
- If present these keys and values should be serialised as json client-side and posted to the trigger-dag API endpoint as the `conf` request-parameter.
- By default no conf request-parameter is sent. Perhaps a checkbox should be used to determine whether conf is sent at all?
- The user may want to add new keys, or remove keys & values that they have previously added.
- [PR-10839](https://github.com/apache/airflow/pull/10839) is pre-populating the form with the DAG's default params. The new form should be pre-populated with the keys & values from `DAG.params`


**Use case / motivation**

Currently when triggering a manual DAG run with user-provided runtime parameters, the user has to provide a correctly formatted JSON object. Filling in a form with keys & values will be a significantly better user experience, and will be less error prone & laborious than handling json in a free-text field.

This builds on the great work already done on enhancing the Trigger-DAG functionality

**Related Issues**

Originating PR: https://github.com/apache/airflow/pull/10839
"""Returns grid data"""
        dag_id = request.args.get("dag_id")
        dag = get_airflow_app().dag_bag.get_dag(dag_id)
        if not dag:
            return {"error": f"can't find dag {dag_id}"}, 404
        root = request.args.get("root")
        if root:
            dag = dag.partial_subset(task_ids_or_regex=root, include_downstream=False, include_upstream=True)
        num_runs = request.args.get("num_runs", type=int)
        if num_runs is None:
            num_runs = conf.getint("webserver", "default_dag_run_display_number")
        try:
            base_date = timezone.parse(request.args["base_date"])
        except (KeyError, ValueError):
            base_date = dag.get_latest_execution_date() or timezone.utcnow()
        with create_session() as session:
            query = session.query(DagRun).filter(
                DagRun.dag_id == dag.dag_id, DagRun.execution_date <= base_date
            )
            run_type = request.args.get("run_type")
            if run_type:
                query = query.filter(DagRun.run_type == run_type)
            run_state = request.args.get("run_state")
            if run_state:
                query = query.filter(DagRun.state == run_state)