**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
session.query(TaskFail)
            .join(TaskFail.dag_run)
            .filter(
                TaskFail.dag_id == dag.dag_id,
                DagRun.execution_date >= min_date,
                DagRun.execution_date <= base_date,
            )
        )
        if dag.partial:
            ti_fails = ti_fails.filter(TaskFail.task_id.in_([t.task_id for t in dag.tasks]))
        fails_totals = defaultdict(int)
        for failed_task_instance in ti_fails:
            dict_key = (
                failed_task_instance.dag_id,
                failed_task_instance.task_id,
                failed_task_instance.run_id,
            )
            if failed_task_instance.duration:
                fails_totals[dict_key] += failed_task_instance.duration
        
        mapped_tis = set()
        tis_grouped = itertools.groupby(task_instances, lambda x: (x.dag_id, x.task_id, x.run_id))
        for key, tis in tis_grouped:
            tis = list(tis)
            duration = sum(x.duration for x in tis if x.duration)
            if duration:
                first_ti = tis[0]
                if first_ti.map_index >= 0:
                    mapped_tis.add(first_ti.task_id)
                date_time = wwwutils.epoch(first_ti.execution_date)