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In Rasa, policies are the components responsible for dialogue management. In a CALM-based assistant, the FlowPolicy is responsible for executing your business logic. If you're building an NLU-based assistant, you can read about the relevant policies here.

Policies in CALM

Dialogue Understanding in CALM accounts for the context of a conversation, so the role of the dialogue manager is simpler than it is in an NLU-based assistant.

You can customize the policies your assistant uses by specifying the policies key in your project's config.yml. In most cases, the default configuration should meet your needs, customization is there for advanced use-cases.

There are different policies to choose from, and you can include multiple policies in a single configuration. Here's an example of what a list of policies might look like:

• Rasa Pro <=3.7.x
• Rasa Pro >=3.8.x

config.yml

# ...

policies:
  - name: FlowPolicy
  - name: rasa_plus.ml.EnterpriseSearchPolicy

config.yml

# ...

policies:
  - name: FlowPolicy
  - name: EnterpriseSearchPolicy

Action Selection

At every turn, each policy defined in your configuration gets a chance to predict a next action with a certain confidence level. A policy can also decide not to predict any action. The policy that predicts with the highest confidence decides the assistant's next action.

Maximum number of predictions

By default, when using CALM assistant (or routing to it, in case of coexistence of NLU-based and CALM systems) the maximum number of next action predictions after each user message is 1000. To update this value, you can set the environment variable MAX_NUMBER_OF_PREDICTIONS_CALM to the desired number of maximum predictions. For an NLU-based assistant the maximum is set in the environment variable MAX_NUMBER_OF_PREDICTIONS with a default of 10.