**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
is_dag_run_conf_overrides_params=is_dag_run_conf_overrides_params,
                    recent_confs=recent_confs,
                )
        if unpause and dag.is_paused:
            models.DagModel.get_dagmodel(dag_id).set_is_paused(is_paused=False)
        try:
            dag.create_dagrun(
                run_type=DagRunType.MANUAL,
                execution_date=execution_date,
                data_interval=dag.timetable.infer_manual_data_interval(run_after=execution_date),
                state=State.QUEUED,
                conf=run_conf,
                external_trigger=True,
                dag_hash=get_airflow_app().dag_bag.dags_hash.get(dag_id),
                run_id=run_id,
            )
        except (ValueError, ParamValidationError) as ve:
            flash(f"{ve}", "error")
            form = DateTimeForm(data={"execution_date": execution_date})
            return self.render_template(
                "airflow/trigger.html",
                dag_id=dag_id,
                origin=origin,
                conf=request_conf,
                form=form,
                is_dag_run_conf_overrides_params=is_dag_run_conf_overrides_params,
            )
        flash(f"Triggered {dag_id}, it should start any moment now.")
        return redirect(origin)
    def _clear_dag_tis(