The recipe key allows for different types of config and model architecture. Currently, "default.v1" and the experimental "graph.v1" recipes are supported.
New in 3.5
The config file now includes a new mandatory key
assistant_id which represents the unique assistant identifier.
assistant_id key must specify a unique value to distinguish multiple assistants in deployment.
The assistant identifier will be propagated to each event's metadata, alongside the model id.
Note that if the config file does not include this required key or the placeholder default value is not replaced, a random
assistant name will be generated and added to the configuration everytime when running
If you don't know which components or policies to choose, you can use the Suggested Config feature, which will recommend sensible defaults.
You can leave the pipeline and/or policies key out of your configuration file.
When you run
rasa train, the Suggested Config feature will select a default configuration
for the missing key(s) to train the model.
Make sure to specify the language key in your
config.yml file with the
2-letter ISO language code.
The selected configuration will also be written as comments into the
so you can see which configuration was used. For the example above, the resulting file
might look e.g. like this:
If you like, you can then un-comment the suggested configuration for one or both of the keys and make modifications. Note that this will disable automatic suggestions for this key when training again. As long as you leave the configuration commented out and don't specify any configuration for a key yourself, a default configuration will be suggested whenever you train a new model.
nlu- or dialogue- only models
Only the default configuration for
pipeline will be automatically selected
if you run
rasa train nlu, and only the default configuration for
will be selected if you run
rasa train core.