Problems transforming GEE Python API objects to Python variables within Flask application

Question

I am trying to expose an API endpoint through Flask, and I generated the JSON data to return through this endpoint by processing data hosted in the Google Earth Engine Python API using server-side objects. It takes geographic coordinates and returns information about the agricultural parcel of the same pixel value as the pixel value of the coordinates.

I tested the code in Google Colab python environment without deploying and it returned the desired response, but when I accessed a publicly accessible URL of the API endpoint deployed through ngrok, it no longer worked. Also running the Flask app locally returns the same error, which seems to be related to the use of the GetInfo() method, which is the only method recommended for transforming server-side objects to local variables with the GEE Python API. It is a synchronous method, hence the attempt to make the Flask application async with asyncio.

async def get_mapBiomas_feature(latitude, longitude):
      point = ee.Geometry.Point(longitude, latitude)
      image_final = ee.Image('projects/mapbiomas-workspace/public/collection8/mapbiomas_collection80_integration_v1'). select("classification_2022")
      point_class_value_2022 = image_final.sample(point, 1).first().get("classification_2022")
      if point_class_value_2022 in culturas:
        cultura_2022 = class_names.get(str(point_class_value_2022))
      else:
        cultura_2022 = "Coberta do solo nao contem cultura agricola"
      masked_image_2022 = image_final.updateMask(image_final.eq(ee.Image.constant(point_class_value_2022)))
      connected_image_labels_2022 = masked_image_2022.connectedComponents(ee.Kernel.square(1), 1024).select("labels")
      await asyncio.sleep(5)
      buffered_point = point.buffer(50000)
      clipped_image_2022 = connected_image_labels_2022.clip(buffered_point)
      vectors_2022 = await reduceVectors(clipped_image_2022)
      selected_feature_2022 = vectors_2022.filterBounds(point).first()
      geometry_2022 = selected_feature_2022.geometry().simplify(1000)
      coordinates_2022 = geometry_2022.coordinates()
      area_hectares_2022 = geometry_2022.area(maxError=100).divide(10000)
      properties_2022 = {'area_hectares': area_hectares_2022, 'origem': cultura_2022, "poligono": coordinates_2022}
      print("Properties 2022", properties_2022)
      results = ee.Dictionary(properties_2022).getInfo()      
      await asyncio.sleep(5)
      print(results)
      return results

Code error:

dict = ee.Dictionary(properties).getInfo()
  File "/usr/local/lib/python3.10/dist-packages/ee/computedobject.py", line 105, in getInfo
    return data.computeValue(self)
  File "/usr/local/lib/python3.10/dist-packages/ee/data.py", line 1040, in computeValue
    return _execute_cloud_call(
  File "/usr/local/lib/python3.10/dist-packages/ee/data.py", line 356, in _execute_cloud_call
    raise _translate_cloud_exception(e)  # pylint: disable=raise-missing-from
ee.ee_exception.EEException: Element.get: Parameter 'object' is required.
INFO:werkzeug:127.0.0.1 - - [25/Oct/2023 15:36:23] "GET /MapBiomas_cultura?lat=-55.09&lon=-7.73 HTTP/1.1" 500 -

Full code snippet: https://goonlinetools.com/snapshot/code/#ynfju6xqnhd4v6h3wmq5cv

The use of GetInfo() is discouraged in the API documentation because it's a syncronous method, so I tried using many different implementations of Asyncio for Flask to see if this was a problem with the GetInfo() method and the delayed response of the server-side processing. I also created a python virtual env and ran Flask locally to see if the problem was with the Colab processing environment and the Ngrok deployment.