Question: Add New Polygon to Dash Leaflet Map via a Callback

Im very new to working with GIS data (using Dash Leaflet and GeoPandas) and am currently stumped.
My goal is to create a simple app which does the following:

App starts with an empty dash_leaflet.Map() figure and a numeric input box titled "Buffer Distance" (with a default of 100)
User draws a polygon on the map which fires a callback
Callback takes in the GeoJSON data from the map and the "buffer distance"
Use Geopandas to import the GeoJSON data and create a new polygon which is smaller than the user drawn polygon by "Buffer Distance"
Pass these 2 polygons (originally drawn & post processed polygon with buffer) back to the map so that both are now displayed on the map

Im having trouble with the last step of pushing the two polygons back the map via some kind of Output
This is the app i am currently working with:
import pandas as pd
from dash import Dash, dcc, html, Input, Output, State
import dash_leaflet as dl
import geopandas as gpd

lat1, lon1 = 36.215487, -81.674006

app = Dash()

input_details = html.Div([
    html.Div([
        html.Div(['Buffer Distance'], style={'width': '37%', 'display': 'inline-block'}),
        dcc.Input(
            value=100,
            id="buffer-distance",
            type='number',
            placeholder='Required',
        ),
    ]),
])

default_map_children = [
    dl.TileLayer(),
    dl.FeatureGroup([
        dl.EditControl(id="edit_control"),
    ]),
    dl.GeoJSON(id='map-geojsons')
]

map_input_results_tab = html.Div(
    [
        html.H2('Add Shapes to Map an Area of Interest'),
        dl.Map(
            id='leaflet-map',
            style={'width': '100%', 'height': '50vh'},
            center=[lat1, lon1],
            zoom=16,
            children=default_map_children
        )
    ])

app.layout = html.Div([input_details, map_input_results_tab])


@app.callback(
    Output('map-geojsons', 'data'),
    Input('edit_control', 'geojson'),
    State('buffer-distance', 'value'),
)
def update_estimates(drawn_geojson, perim_clear):
    if any([x is None for x in [drawn_geojson, perim_clear]]):
        # some value has not been provided, so do not continue with calculations
        return drawn_geojson
    elif not drawn_geojson["features"]:
        # some value has not been provided, so do not continue with calculations
        return drawn_geojson

    gdf = gpd.GeoDataFrame.from_features(drawn_geojson["features"])  # extract user drawn geometry data from UI
    gdf = gdf.set_crs(crs=4326)  # Set the initial CRS to specify that this is lat/lon data
    gdf = gdf.to_crs(
        crs=gdf.estimate_utm_crs())  # Let GeoPandas estimate the best CRS and use that for the area calculation

    # create a new geodataframe using buffer that incorporates the perimeter
    gdf_minus_perim_buffer = gdf['geometry'].buffer(-perim_clear)
    combine_gdf = pd.concat([gdf['geometry'], gdf_minus_perim_buffer])
    # convert back to lat, long
    combine_gdf = combine_gdf.to_crs(crs=4326)
    # convert back to GeoJSON to be rendered in the dash leaflet map
    return_geojson_data = combine_gdf.to_json()

    return return_geojson_data


if __name__ == '__main__':
    app.run_server(debug=True, port=8052)

I think I am close, but am just missing something.. Thanks in advance for any help!


Answer:
It looks like the callback approach above is valid, I was just providing the wrong data type back to the dl.GeoJSON's data attribute .
Changing this line:
# convert back to GeoJSON to be rendered in the dash leaflet map
return_geojson_data = combine_gdf.to_json()

to
# convert back to GeoJSON to be rendered in the dash leaflet map
return_geojson_data = combine_gdf.__geo_interface__

worked perfectly!