**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
"""
    Parse datetime and return error message for invalid dates
    :param v: the string value to be parsed
    :param allow_empty: Set True to return none if empty str or None
    """
    if allow_empty is True and not v:
        return None
    try:
        return timezone.parse(v)
    except (TypeError, ParserError):
        abort(400, f"Invalid datetime: {v!r}")
def node_dict(node_id, label, node_class):
    return {
        "id": node_id,
        "value": {"label": label, "rx": 5, "ry": 5, "class": node_class},
    }
def dag_to_grid(dag: DagModel, dag_runs: Sequence[DagRun], session: Session):
    """
    Create a nested dict representation of the DAG's TaskGroup and its children
    used to construct the Graph and Grid views.
    """
    query = (
        session.query(
            TaskInstance.task_id,