Slot Validation Actions
There is a helper class in Rasa SDK with the role of executing custom slot extraction and validation:
ValidationAction
: the base class for custom actions extracting and validating slots.
In order to implement custom slot extraction and validation logic, you can subclass the
ValidationAction
class.
ValidationAction
class
NLU-based assistants
This section refers to building NLU-based assistants. If you are working with Conversational AI with Language Models (CALM), this content may not apply to you.
You can extend the ValidationAction
class in the Rasa SDK to define custom extraction and / or validation of slots.
How to subclass ValidationAction
Firstly, you must add the name of this action, action_validate_slot_mappings
, to the domain actions
list.
Note that you do not need to implement the name
method in the custom action extending ValidationAction
, since this
is already implemented. If you override the name
method, the custom validation action will not run because the
original name is hardcoded in the call that the default action action_extract_slots
makes to the action server.
You should create only one subclass of ValidationAction
which should contain all extraction and validation
methods for different slots according to your use-case.
With this option, you do not need to specify the action
key in the custom slot mapping,
since the default action action_extract_slots
runs action_validate_slot_mappings
automatically if present in the actions
section of the domain.
Validation of Slots with Predefined Mappings
To validate slots with a predefined mapping, you must write functions named validate_<slot_name>
.
In the following example, the value for slot location
is capitalized only if the extracted value is of type string:
from typing import Text, Any, Dict
from rasa_sdk import Tracker, ValidationAction
from rasa_sdk.executor import CollectingDispatcher
from rasa_sdk.types import DomainDict
class ValidatePredefinedSlots(ValidationAction):
def validate_location(
self,
slot_value: Any,
dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: DomainDict,
) -> Dict[Text, Any]:
"""Validate location value."""
if isinstance(slot_value, str):
# validation succeeded, capitalize the value of the "location" slot
return {"location": slot_value.capitalize()}
else:
# validation failed, set this slot to None
return {"location": None}
Extraction of Custom Slot Mappings
To define custom extraction code, write an extract_<slot_name>
method for every slot with a
custom slot mapping.
The following example shows the implementation of a custom action that extracts the slot count_of_insults
to keep
track of the user's attitude.
from typing import Dict, Text, Any
from rasa_sdk import Tracker
from rasa_sdk.executor import CollectingDispatcher
class ValidateCustomSlotMappings(ValidationAction):
async def extract_count_of_insults(
self, dispatcher: CollectingDispatcher, tracker: Tracker, domain: Dict
) -> Dict[Text, Any]:
intent_of_last_user_message = tracker.get_intent_of_latest_message()
current_count_of_insults = tracker.get_slot("count_of_insults")
if intent_of_last_user_message == "insult":
current_count_of_insults += 1
return {"count_of_insults": current_count_of_insults}
ValidationAction
class implementation
ValidationAction
is a subclass of the Action
Rasa SDK class and the abstract Python ABC
class.
Therefore the class implements the name
and run
methods inherited from Action
.
In addition, ValidationAction
implements more specialized methods that will be called in the run
method:
get_extraction_events
: Extracts custom slots using availableextract_<slot name>
methodsget_validation_events
: Validates slots by calling availablevalidate_<slot name>
methods for each slotrequired_slots
: Returns slots which the validation action should fill
Methods
ValidationAction.name
Defines the action's name: this must be hardcoded as action_validate_slot_mappings
.
-
Returns:
Name of action
-
Return type:
str
ValidationAction.run
async ValidationAction.run(dispatcher, tracker, domain)
The run
method executes the custom extraction code defined in extract_<slot name>
methods by calling the
get_extraction_events
method, then updates the tracker with the returned events.
The run
method will also execute custom validation code defined in validate_<slot name>
methods via the
get_validation_events
method and add the returned events to the tracker.
Parameters
-
dispatcher – the dispatcher which is used to send messages back to the user. Use
dispatcher.utter_message()
or any otherrasa_sdk.executor.CollectingDispatcher
method. See the documentation for the dispatcher -
tracker – the state tracker for the current user. You can access slot values using
tracker.get_slot(slot_name)
, the most recent user message istracker.latest_message.text
and any otherrasa_sdk.Tracker
property. See the documentation for the tracker. -
domain – the bot's domain
Returns
A list of rasa_sdk.events.Event
instances. See the documentation for events.
Return type
List
[Dict
[str
, Any
]]
ValidationAction.required_slots
async ValidationAction.required_slots(domain_slots, dispatcher, tracker, domain)
The required_slots
method will return the domain_slots
which is a list of all slot names mapped in the domain that
do not include any slot mapping with conditions. domain_slots
is returned by the domain_slots
method, which only takes
Domain
as an argument.
Returns
A list of slot names of type Text
.
ValidationAction.get_extraction_events
async ValidationAction.get_extraction_events(dispatcher, tracker, domain)
The get_extraction_events
method will gather the list of slot names via required_slots
method call and then loop
through every slot name to run the extract_<slot name>
method if available.
Returns
A list of rasa_sdk.events.SlotSet
instances. See the documentation for SlotSet events.
ValidationAction.get_validation_events
async ValidationAction.get_validation_events(dispatcher, tracker, domain)
The get_validation_events
method will gather the list of slot names to validate via required_slots
method call.
Then it will get a mapping of slots which were recently set and their values via tracker.slots_to_validate
call.
Looping through this mapping of recently extracted slots, it will check if the slot is in required_slots
then run the
validate_<slot name>
method if available for that slot.
Returns
A list of rasa_sdk.events.SlotSet
instances. See the documentation for SlotSet events.
How to implement custom validation in CALM assistants
In CALM assistants, slot validation actions should be implemented like normal actions by subclassing the base Action
class.
Here is an example of a custom slot validation action in a CALM assistant:
class ValidateLocation(Action):
def name(self) -> Text:
return "validate_location"
def run(
self,
dispatcher: CollectingDispatcher,
tracker: Tracker,
domain: DomainDict,
) -> Dict[Text, Any]:
"""Validate slot value."""
slot_value = tracker.get_slot("location")
if isinstance(slot_value, str):
# validation succeeded, capitalize the value of the "location" slot
return {"location": slot_value.capitalize()}
else:
# validation failed, set this slot to None
return {"location": None}