**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
x_custom_format=True,
            x_axis_date=True,
            x_axis_format=LINECHART_X_AXIS_TICKFORMAT,
            height=chart_height,
            chart_attr=self.line_chart_attr,
        )
        y_points = {}
        x_points = {}
        for task in dag.tasks:
            task_id = task.task_id
            y_points[task_id] = []
            x_points[task_id] = []
            for ti in tis:
                if ti.task_id != task.task_id:
                    continue
                ts = dag.get_run_data_interval(ti.dag_run).end
                if ti.end_date:
                    dttm = wwwutils.epoch(ti.execution_date)
                    secs = (ti.end_date - ts).total_seconds()
                    x_points[task_id].append(dttm)
                    y_points[task_id].append(secs)
        
        
        y_unit = infer_time_unit([d for t in y_points.values() for d in t])
        
        chart.create_y_axis("yAxis", format=".02f", custom_format=False, label=f"Landing Time ({y_unit})")
        chart.axislist["yAxis"]["axisLabelDistance"] = "-15"
        for task_id in x_points:
            chart.add_serie(
                name=task_id,