These docs are for version 1.x of Rasa Open Source.

Slots

What are slots?

Slots are your bot’s memory. They act as a key-value store which can be used to store information the user provided (e.g their home city) as well as information gathered about the outside world (e.g. the result of a database query).

Most of the time, you want slots to influence how the dialogue progresses. There are different slot types for different behaviors.

For example, if your user has provided their home city, you might have a text slot called home_city. If the user asks for the weather, and you don't know their home city, you will have to ask them for it. A text slot only tells Rasa Core whether the slot has a value. The specific value of a text slot (e.g. Bangalore or New York or Hong Kong) doesn’t make any difference.

If the value itself is important, use a categorical or a bool slot. There are also float, and list slots. If you just want to store some data, but don’t want it to affect the flow of the conversation, use an unfeaturized slot.

How Rasa Uses Slots

The Policy doesn’t have access to the value of your slots. It receives a featurized representation. As mentioned above, for a text slot the value is irrelevant. The policy just sees a 1 or 0 depending on whether it is set.

You should choose your slot types carefully!

How Slots Get Set

You can provide an initial value for a slot in your domain file:

slots:
  name:
    type: text
    initial_value: "human"

You can get the value of a slot using .get_slot() inside actions.py for example:

data = tracker.get_slot("slot-name")

There are multiple ways that slots are set during a conversation:

Slots Set from NLU

If your NLU model picks up an entity, and your domain contains a slot with the same name, the slot will be set automatically. For example:

# story_01
* greet{"name": "Ali"}
  - slot{"name": "Ali"}
  - utter_greet

Slots Set By Clicking Buttons

You can use buttons as a shortcut. Rasa Core will send messages starting with a / to the RegexInterpreter, which expects NLU input in the same format as in story files, e.g. /intent{entities}. For example, if you let users choose a color by clicking a button, the button payloads might be /choose{"color": "blue"} and /choose{"color": "red"}.

Slots Set by Actions

You can set slots by returning events in custom actions. In this case, your stories need to include the slots.

Slot Types

Text Slot

text
Use For: User preferences where you only care whether or not they’ve been specified.

Example:

slots:
   cuisine:
      type: text

Boolean Slot

bool
Use For: True or False

Example:

slots:
   is_authenticated:
      type: bool

Categorical Slot

categorical
Use For: Slots which can take one of N values

Example:

slots:
   risk_level:
      type: categorical
      values:
      - low
      - medium
      - high

Float Slot

float
Use For: Continuous values

Example:

slots:
   temperature:
      type: float
      min_value: -100.0
      max_value:  100.0

List Slot

list
Use For: Lists of values

Example:

slots:
   shopping_items:
      type: list

Unfeaturized Slot

unfeaturized
Use For: Data you want to store which shouldn’t influence the dialogue flow

Example:

slots:
   internal_user_id:
      type: unfeaturized

Custom Slot Types

In the code below, we define a slot class called NumberOfPeopleSlot.

from rasa.core.slots import Slot

class NumberOfPeopleSlot(Slot):

def feature_dimensionality(self):
        return 2

def as_feature(self):
        r = [0.0] * self.feature_dimensionality()
        if self.value:
            if self.value <= 6:
                r[0] = 1.0
            else:
                r[1] = 1.0
        return r

Now we also need some training stories, so that Rasa Core can learn from these how to handle the different situations:

# story1
...
* inform{"people": "3"}
  - action_book_table
...
# story2
* inform{"people": "9"}
  - action_explain_table_limit

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