Actions¶
Contents
Actions are the things your bot runs in response to user input. There are three kinds of actions in Rasa Core:
- default actions (
action_listen
,action_restart
,action_default_fallback
)- utter actions, starting with
utter_
, which just sends a message to the user (see Bot Responses).- custom actions - any other action, these actions can run arbitrary code
Utter Actions¶
To define an UtterAction
, add an utterance template to the domain file,
that starts with utter_
:
templates:
utter_my_message:
- "this is what I want my action to say!"
It is conventional to start the name of an UtterAction
with utter_
.
If this prefix is missing, you can still use the template in your custom
actions, but the template can not be directly predicted as its own action.
See Bot Responses for more details.
If you use an external NLG service, you don’t need to specify the templates in the domain, but you still need to add the utterance names to the actions list of the domain.
Custom Actions¶
An action can run any code you want. Custom actions can turn on the lights, add an event to a calendar, check a user’s bank balance, or anything else you can imagine.
Core will call an endpoint you can specify, when a custom action is predicted. This endpoint should be a webserver that reacts to this call, runs the code and optionally returns information to modify the dialogue state.
To specify, your action server use the endpoints.yml
:
action_endpoint:
url: "http://localhost:5055/webhook"
And pass it to the scripts using --endpoints endpoints.yml
.
You can create an action server in node.js, .NET, java, or any other language and define your actions there - but we provide a small python sdk to make development there even easier.
Custom Actions Written in Python¶
For actions written in python, we have a convenient SDK which starts this action server for you.
The only thing your action server needs to install is rasa_core_sdk
:
pip install rasa_core_sdk
Note
You do not need to install rasa_core
for your action server.
E.g. it is recommended to run Rasa Core in a docker container and
create a separate container for your action server. In this
separate container, you only need to install rasa_core_sdk
.
If your actions are defined in a file
called actions.py
, run this command:
python -m rasa_core_sdk.endpoint --actions actions
In a restaurant bot, if the user says “show me a Mexican restaurant”,
your bot could execute the action ActionCheckRestaurants
,
which might look like this:
from rasa_core_sdk import Action
from rasa_core_sdk.events import SlotSet
class ActionCheckRestaurants(Action):
def name(self):
# type: () -> Text
return "action_check_restaurants"
def run(self, dispatcher, tracker, domain):
# type: (CollectingDispatcher, Tracker, Dict[Text, Any]) -> List[Dict[Text, Any]]
cuisine = tracker.get_slot('cuisine')
q = "select * from restaurants where cuisine='{0}' limit 1".format(cuisine)
result = db.query(q)
return [SlotSet("matches", result if result is not None else [])]
You should add the the action name action_check_restaurants
to
the actions in your domain file. The action’s run
method receives
three arguments. You can access the values of slots and the latest message
sent by the user using the tracker
object, and you can send messages
back to the user with the dispatcher
object, by calling
dispatcher.utter_template
, dispatcher.utter_message
, or any other
rasa_core_sdk.executor.CollectingDispatcher
method.
Details of the run
method:
-
Action.
run
(dispatcher, tracker, domain)[source]¶ Execute the side effects of this action.
Parameters: - dispatcher (CollectingDispatcher) – the dispatcher which is used to
send messages back to the user. Use
dipatcher.utter_message()
or any otherrasa_core_sdk.executor.CollectingDispatcher
method. - tracker (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_core_sdk.Tracker
property. - domain (Dict[Text, Any]) – the bot’s domain
Returns: - A dictionary of
rasa_core_sdk.events.Event
instances that is returned through the endpoint
Return type: List[Dict[Text, Any]]
- dispatcher (CollectingDispatcher) – the dispatcher which is used to
send messages back to the user. Use
There is an example of a SlotSet
event
below, and a full list of possible
events in Events.
Default Actions¶
There are three default actions:
action_listen |
stop predicting more actions and wait for user input |
action_restart |
reset the whole conversation, usually triggered
by using /restart |
action_default_fallback |
undoes the last user message (as if the user did not send it) and utters a message that the bot did not understand. See Fallback Actions. |
All the default actions can be overwritten. To do so, add the action name to the list of actions in your domain:
actions:
- action_listen
Rasa Core will then call your action endpoint and treat it as every other custom action.
Execute Actions in Other Code¶
Rasa Core will send an HTTP POST
request to your server containing
information on which action to run. Furthermore, this request will contain all
information about the conversation.
As a response to the action call from Core, you can modify the tracker, e.g. by setting slots and send responses back to the user. All of the modifications are done using events. There is a list of all possible event types in Events.
Have questions or feedback?¶
We have a very active support community on Rasa Community Forum that is happy to help you with your questions. If you have any feedback for us or a specific suggestion for improving the docs, feel free to share it by creating an issue on Rasa Core GitHub repository.