notice
This is documentation for Rasa Open Source Documentation v2.0.x, which is no longer actively maintained.
For up-to-date documentation, see the latest version (2.3.x).
Responses
Responses are messages that your assistant sends to the user. A response is usually only text, but can also include content like images and buttons.
Defining Responses
Responses go under the responses
key in your domain file or in a separate "responses.yml" file. Each response name should start with utter_
.
For example, you could add responses for greeting and saying goodbye under the response names utter_greet
and utter_bye
:
If you are using retrieval intents in your assistant, you also need to add responses for your assistant's replies to these intents:
note
Notice the special format of response names for retrieval intents. Each name starts with utter_
,
followed by the retrieval intent's name (here chitchat
) and finally a suffix specifying
the different response keys (here ask_name
and ask_weather
). See the documentation for NLU
training examples to learn more.
Using Variables in Responses
You can use variables to insert information into responses.
Within a response, a variable is enclosed in curly brackets. For example, see the variable name
below:
When the utter_greet
response is used, Rasa automatically fills in the variable with the
value found in the slot called name
. If such a slot doesn't exist or is empty, the variable gets
filled with None
.
Another way to fill in a variable is within a custom action.
In your custom action code, you can supply values to a response to fill in specific variables.
If you're using the Rasa SDK for your action server,
you can pass a value for the variable as a keyword argument to dispatcher.utter_message
:
If you use a different custom action server, supply the values by adding extra parameters to the responses your server returns:
Response Variations
You can make your assistant's replies more interesting if you provide multiple response variations to choose from for a given response name:
In this example, when utter_greet
gets predicted as the next action, Rasa will randomly pick one
of the two response variations to use.
Channel-Specific Response Variations
To specify different response variations depending on which channel the user is connected to, use channel-specific response variations.
In the following example, the channel
key makes the first response variation channel-specific for
the slack
channel while the second variation is not channel-specific:
note
Make sure the value of the channel
key matches the value returned by the name()
method of your
input channel. If you are using a built-in channel, this value will also match the channel name used
in your credentials.yml
file.
When your assistant looks for suitable response variations under a given response name, it will first try to choose from channel-specific variations for the current channel. If there are no such variations, the assistant will choose from any response variations which are not channel-specific.
In the above example, the second response variation has no channel
specified and can be used by
your assistant for all channels other than slack
.
caution
For each response, try to have at least one response variation without the channel
key.
This allows your assistant to properly respond in all environments, such as in new channels,
in the shell and in interactive learning.
Rich Responses
You can make responses rich by adding visual and interactive elements. There are several types of elements that are supported across many channels:
Buttons
Here is an example of a response that uses buttons:
Each button in the list of buttons
should have two keys:
title
: The text displayed on the buttons that the user sees.payload
: The message sent from the user to the assistant when the button is clicked.
bypass nlu with buttons
It's common to use buttons as a shortcut to bypass the machine-learning-based NLU interpreter.
Messages starting with /
are sent straight to the
RegexInterpreter
, which expects NLU input in a shortened /intent{entities}
format.
In the example above, if the user clicks a button, the user input
will be directly classified as either the mood_great
or mood_sad
intent.
Check your channel
Keep in mind that it is up to the implementation of the output channel how to display the defined buttons. For example, some channels have a limit on the number of buttons you can provide. Check your channel's documentation under Concepts > Channel Connectors for any channel-specific restrictions.
Images
You can add images to a response by providing a URL to the image under the image
key:
Custom Output Payloads
You can send any arbitrary output to the output channel using the
custom
key. The output channel receives the object stored under the custom
key
as a JSON payload.
Here's an example of how to send a date picker to the Slack Output Channel:
Using Responses in Conversations
Calling Responses as Actions
If the name of the response starts with utter_
, the response can
directly be used as an action, without being listed in the actions
section of your domain. You would add the response
to the domain:
You can use that same response as an action in your stories:
When the utter_greet
action runs, it will send the message from
the response back to the user.
Changing responses
If you want to change the text, or any other part of the response, you need to retrain the assistant before these changes will be picked up.
Calling Responses from Custom Actions
You can use the responses to generate response messages from your custom actions. If you're using Rasa SDK as your action server, you can use the dispatcher to generate the response message, for example:
If you use a
different custom action server,
your server should return the following JSON to call the utter_greet
response: