reticulate 1.14 together with Miniconda3 and tensorflow not working

After several hours of trial and error to reticulate Python to Tensorflow there are first silver linings at the horizon: Using the commands

library(reticulate)                         
use_condaenv("r-tensorflow", required = TRUE)
library(tensorflow) 
library(keras)                                
is_keras_available()

gives (for the first application after several mins waiting time, after that about 15secs after every new start of the R program sheet) the long hoped for message

[1] TRUE

and permitting insight into what these commands have done in the meantime:

reticulate::py_config()
python:         C:/.../Local/conda/conda/envs/r-tensorflow/python.exe
libpython:      C:/.../Local/conda/conda/envs/r-tensorflow/python36.dll
pythonhome:     C:/.../Local/conda/conda/envs/r-tensorflow
version:        3.6.6 |Anaconda, Inc.| (default, Jun 28 2018, 11:27:44) [MSC v.1900 64 bit (AMD64)]
Architecture:   64bit
numpy:          C:/.../Local/conda/conda/envs/r-tensorflow/Lib/site-packages/numpy
numpy_version:  1.14.3
tensorflow:     C:\...\Local\conda\conda\envs\R-TENS~1\lib\site-packages\tensorflow\__init__.p
NOTE: Python version was forced by use_python function

Compared with the first part of my posts this shows that there has been some transmogrification from Miniconda3 v4.7.12 (Python 3.7.4), which my WIN10 is still indicating, over (Python) version: 3.6.10 as in my 2nd post, to finally (Python) version: 3.6.6 as regards Python in this final state. Numpy has been downgraded as well, btw. And Tensorflow has suffered, too:

tensorflow::tf_config()
TensorFlow v1.5.0 (C:\...\Local\conda\conda\envs\R-TENS~1\lib\site-packages\tensorflow\__init__.p)
Python v3.6 (C:/.../Local/conda/conda/envs/r-tensorflow/python.exe)

(sessionInfo() still shows tensorflow_2.0.0). Nevertheless, Keras seems to be available.

All this is far away from the promised land of fully automated availability of Python to Tensorflow and hopefully Keras by reticulate v1.14, but nevertheless: a 1st success.

Finally, a bad surprise with this setup: there are serious downward compatibility problems with keras 2.2.5.0, completely inhibiting use of previously working programmes.