Version: 2.0.0

Actions

When a Rasa Open Source assistant calls a custom action, it sends a request to the action server. Rasa Open Source only knows about whatever events and responses come back in the request response; it's up to the action server to call the correct code based on the action name that Rasa Open Source provides.

To better understand what happens when Rasa calls a custom action, consider the following example:

You have deployed a weather bot to both Facebook and Slack. The user can ask for the weather with the intent ask_weather. There is a slot location which will be filled if the user has specified a location. The action action_tell_weather will use an API to get the weather forecast , using a default location if the user doesn't specify one. The action will set the temperature to the maximum temperature of the weather forecast. The message returned will differ according to the channel they are using.

Custom Action Input

Your action server receives the following payload from the Rasa server:

{
"next_action": "action_tell_weather",
"sender_id": "2687378567977106",
"tracker": {
"sender_id": "2687378567977106",
"slots": {
"location": null,
"temperature": null
},
"latest_message": {
"text": "/ask_weather",
"intent": {
"name": "ask_weather",
"confidence": 1
},
"intent_ranking": [
{
"name": "ask_weather",
"confidence": 1
}
],
"entities": []
},
"latest_event_time": 1599850576.655345,
"followup_action": null,
"paused": false,
"events": [
{
"event": "action",
"timestamp": 1599850576.654908,
"name": "action_session_start",
"policy": null,
"confidence": null
},
{
"event": "session_started",
"timestamp": 1599850576.654916
},
{
"event": "action",
"timestamp": 1599850576.654928,
"name": "action_listen",
"policy": null,
"confidence": null
},
{
"event": "user",
"timestamp": 1599850576.655345,
"text": "/ask_weather",
"parse_data": {
"text": "/ask_weather",
"intent": {
"name": "ask_weather",
"confidence": 1
},
"intent_ranking": [
{
"name": "ask_weather",
"confidence": 1
}
],
"entities": []
},
"input_channel": "facebook",
"message_id": "3f2f2317dada4908b7a841fd3eab6bf9",
"metadata": {}
}
],
"latest_input_channel": "facebook",
"active_form": {},
"latest_action_name": "action_listen"
},
"domain": {
"config": {
"store_entities_as_slots": true
},
"session_config": {
"session_expiration_time": 60,
"carry_over_slots_to_new_session": true
},
"intents": [
{
"greet": {
"use_entities": true
}
},
{
"ask_weather": {
"use_entities": true
}
}
],
"entities": [],
"slots": {
"location": {
"type": "rasa.core.slots.UnfeaturizedSlot",
"initial_value": null,
"auto_fill": true
},
"temperature": {
"type": "rasa.core.slots.UnfeaturizedSlot",
"initial_value": null,
"auto_fill": true
}
},
"responses": {
"utter_greet": [
{
"text": "Hey! How are you?"
}
]
},
"actions": [
"action_tell_weather",
"utter_greet"
],
"forms": []
},
"version": "2.0.0"
}

next_action

The next_action field tells your action server what action to run. Your actions don't have to be implemented as classes, but they do have to be callable by name.

In the example case, your action server should run the action action_tell_weather.

sender_id

The sender_id tells you the unique ID of the user having the conversation. Its format varies according to the input channel. What it tells you about the user also depends on the input channel and how the user is identified by the channel.

In the example case, the sender_id is not used for anything.

tracker

The tracker contains information about the conversation, including a history of events and a record of all slots:

  • sender_id: The same sender_id as is available in the top level of the payload
  • slots: Each slot in your bot's domain and its value at the current time
  • latest_message: The attributes of the latest message
  • latest_event_time: The timestamp at which the last event was added to the tracker
  • followup_action: The action called was a forced follow up action
  • paused: Whether the conversation is currently paused
  • events: A list of all previous events
  • latest_input_channel: The input channel from which the last user message was received
  • active_form: The name of the currently active form, if any
  • latest_action_name: The name of the last action the bot executed

In the example case, your custom action uses the value of the location slot (if it is set) to get the weather forecast. It also checks the latest_input_channel property and formats the message payload so that it will display correctly in Facebook Messenger.

domain

The domain is a json representation of your domain.yaml file. It is unlikely that a custom action will refer to its contents, as they are static and do not indicate the state of the conversation.

version

This is the version of the Rasa Open Source server. A custom action is also unlikely to refer to this, although you might use it in a verification step if your action server is only compatible with certain Rasa versions.

Custom Action Output

The Rasa server expects a dictionary of events and responses as a response to a custom action call.

events

Events are how your action server can influence the conversation. In the example case, your custom action should store the maximum temperature in the temperature slot, so it needs to return a slot event. To set the slot and do nothing else, your response payload would look like this:

{
"events": [
{
"event": "slot",
"timestamp": null,
"name": "temperature",
"value": "30"
}
],
"responses": []
}

Note that events will be applied to the tracker in the order you list them; with slot events, the order won't matter, but with other event types it can.

responses

A response can be of any of the response types described in the Rasa Open Source documentation on rich responses. See the response sample of the API spec for the expected formats.

In the example case, you want to send the user a message with the weather forecast. To send a regular text message, the response payload would look like this:

{
"events": [
{
"event": "slot",
"timestamp": null,
"name": "temperature",
"value": "30"
}
],
"responses": [
{
"text": "This is your weather forecast!"
}
]
}

However, you want to make use of your channels' specific capabilities. Since the latest_input_channel was Facebook, you add a response with a custom payload that will be rendered as a media message according to Facebook's API spec. Your response payload then looks like this:

{
"events": [
{
"event": "slot",
"timestamp": null,
"name": "temperature",
"value": "30"
}
],
"responses": [
{
"text": "This is your weather forecast!"
},
{
"attachment": {
"type": "template",
"payload": {
"template_type": "media",
"elements": [
{
"media_type": "weather_forcast.gif",
"attachment_id": "<id from facebook upload endpoint>"
}
]
}
}
}
]
}

When this response is sent back to the Rasa server, Rasa will apply the slot event and two responses to the tracker, and return both messages to the user.