Improve rasa command line interface

We found some issues regarding the command line interface rasa:

• rasa interactive rasa interactive currently trains a stacked model and then executes the interactive learning process. Issues:
• You cannot just simple train a core model. You always need to define a valid pipeline in your config file (although you don’t need it), otherwise the training will fail.
• If there are no nlu data, no nlu model can be trained. But, it still tries to use an NLU interpreter later on.

Divide command into rasa interactive- same as before - and rasa interactive core - trains only core model, no need to define pipeline. If it fails to load an nlu model, it should load a regex interpreter (like what rasa interactive core should do).

• using default config Before, if you didn’t define a policy configuration, so when you didn’t pass a configuration with -c, it just got the default_config.yml. Now, if you don’t pass a config file to rasa train core:
• If the config.yml doesn’t exist, you just get an error on the config not existing
• If config.yml exists but doesn’t define policies, you get an error about not having policies defined.

We should add a warning and use the default config again.

[tabergma]

rasa run and rasa shell:

• rasa run should always start a server. It does not matter what kind of model is provided. The server can run with all kind of models.
• rasa shell runs the bot on the command line, if the model includes a Core model. If just an NLU model is given, an NLU interpreter is started.
• Add a subparser for rasa shell nlu that always starts an NLU interpreter as long as an NLU model is included in the provided model.

[tmbo]

I think the improved change detection is an improvement which we should tackle separately