Conversational Context

NOTE: Conversational context is currently only available with the Adapt Intent Parser, and is not yet available for Padatious

Also note that Conversational Context is not likely to work with multiple users. The OVOS and Neon teams are working on a solution to this.

How tall is John Cleese?

"John Cleese is 196 centimeters"

Where's he from?

"He's from England"

Context is added manually by the Skill creator using either the self.set_context() method or the @adds_context() decorator.

Consider the following intent handlers:

    @intent_handler(IntentBuilder().require('PythonPerson').require('Length'))
    def handle_length(self, message):
        python = message.data.get('PythonPerson')
        self.speak('{} is {} cm tall'.format(python, length_dict[python]))

    @intent_handler(IntentBuilder().require('PythonPerson').require('WhereFrom'))
    def handle_from(self, message):
        python = message.data.get('PythonPerson')
        self.speak('{} is from {}'.format(python, from_dict[python]))

To interact with the above handlers the user would need to say

User: How tall is John Cleese?
Neon: John Cleese is 196 centimeters
User: Where is John Cleese from?
Neon: He's from England

To get a more natural response the functions can be changed to let Neon know which PythonPerson we're talking about by using the self.set_context() method to give context:

    @intent_handler(IntentBuilder().require('PythonPerson').require('Length'))
    def handle_length(self, message):
        # PythonPerson can be any of the Monty Python members
        python = message.data.get('PythonPerson')
        self.speak('{} is {} cm tall'.format(python, length_dict[python]))
        self.set_context('PythonPerson', python)

    @intent_handler(IntentBuilder().require('PythonPerson').require('WhereFrom'))
    def handle_from(self, message):
        # PythonPerson can be any of the Monty Python members
        python = message.data.get('PythonPerson')
        self.speak('He is from {}'.format(from_dict[python]))
        self.set_context('PythonPerson', python)

When either of the methods are called the PythonPerson keyword is added to Neon's context, which means that if there is a match with Length but PythonPerson is missing Neon will assume the last mention of that keyword. The interaction can now become the one described at the top of the page.

User: How tall is John Cleese?

Neon detects the Length keyword and the PythonPerson keyword

Neon: 196 centimeters

John Cleese is added to the current context

User: Where's he from?

Neon detects the WhereFrom keyword but not any PythonPerson keyword. The Context Manager is activated and returns the latest entry of PythonPerson which is John Cleese

Neon: He's from England

The context isn't limited by the keywords provided by the current Skill. For example

    @intent_handler(IntentBuilder().require(PythonPerson).require(WhereFrom))
    def handle_from(self, message):
        # PythonPerson can be any of the Monty Python members
        python = message.data.get('PythonPerson')
        self.speak('He is from {}'.format(from_dict[python]))
        self.set_context('PythonPerson', python)
        self.set_context('Location', from_dict[python])

Enables conversations with other Skills as well.

User: Where is John Cleese from?
Neon: He's from England
User: What's the weather like over there?
Neon: Raining and 14 degrees...

Using context to enable Intents

To make sure certain Intents can't be triggered unless some previous stage in a conversation has occured. Context can be used to create "bubbles" of available intent handlers.

User: Hey Neon, bring me some Tea
Neon: Of course, would you like Milk with that?
User: No
Neon: How about some Honey?
User: All right then
Neon: Here you go, here's your Tea with Honey

from mycroft.skills.context import adds_context, removes_context

class TeaSkill(NeonSkill):
    @intent_handler(IntentBuilder('TeaIntent').require("TeaKeyword"))
    @adds_context('MilkContext')
    def handle_tea_intent(self, message):
        self.milk = False
        self.speak('Of course, would you like Milk with that?',
                   expect_response=True)

    @intent_handler(IntentBuilder('NoMilkIntent').require("NoKeyword").
                                  require('MilkContext').build())
    @removes_context('MilkContext')
    @adds_context('HoneyContext')
    def handle_no_milk_intent(self, message):
        self.speak('all right, any Honey?', expect_response=True)

    @intent_handler(IntentBuilder('YesMilkIntent').require("YesKeyword").
                                  require('MilkContext').build())
    @removes_context('MilkContext')
    @adds_context('HoneyContext')
    def handle_yes_milk_intent(self, message):
        self.milk = True
        self.speak('What about Honey?', expect_response=True)

    @intent_handler(IntentBuilder('NoHoneyIntent').require("NoKeyword").
                                  require('HoneyContext').build())
    @removes_context('HoneyContext')
    def handle_no_honey_intent(self, message):
        if self.milk:
            self.speak('Heres your Tea with a dash of Milk')
        else:
            self.speak('Heres your Tea, straight up')

    @intent_handler(IntentBuilder('YesHoneyIntent').require("YesKeyword").
                                require('HoneyContext').build())
    @removes_context('HoneyContext')
    def handle_yes_honey_intent(self, message):
        if self.milk:
            self.speak('Heres your Tea with Milk and Honey')
        else:
            self.speak('Heres your Tea with Honey')

When starting up only the TeaIntent will be available. When that has been triggered and MilkContext is added the MilkYesIntent and MilkNoIntent are available since the MilkContext is set. when a yes or no is received the MilkContext is removed and can't be accessed. In it's place the HoneyContext is added making the YesHoneyIntent and NoHoneyIntent available.

You can find an example Tea Skill using conversational context on Github.

As you can see, Conversational Context lends itself well to implementing a dialog tree or conversation tree.