Context is used to reuse intents across several bot dialogs. Learn more about the concept of context here.
When the intent 'who are you' is recognised, the bot will introduce himself and ask if the user would like to order a ticket.
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In a totally different part of the conversation, at the end of the Book train ticket
conversation flow, the chatbot asks for a booking confirmation.
Both bot questions expect a user intent answer of yes or no. To support correct reuse of intents, we can define a bot dialog intent linked to a certain context. The user will only be redirected to the linked bot dialog if the intent is recognized and the user is in a specific context.
Add the yes
and no
intents and train them with expressions
In the bot dialog Confirm booking
go to the NLP tab
Add an output context confirm_booking
. Press enter to create the output context
When a user reaches this bot dialog the output context is added to the user session context
For each user message, the lifespan of a context is decreased by one. A user can have multiple contexts with different lifespan values.
Add the Confirmed Booking
bot dialog with required context confirm_booking
and intent yes
in the NLP tab. When the yes
intent is returned by the NLP model and the user has the context confirm_booking
, he will be redirected to this bot dialog.
When multiple intent and input context combinations are found, the user's context with the highest lifespan value is taken.
Add the Cancel booking
bot dialog with the required context confirm_booking
and intent no
Add output context who_are_you
in the bot dialog Who are you
Add the Yes book ticket
bot dialog with required context who_are_you
and intent yes
Add the No book ticket
bot dialog with required context who_are_you
and intent no
Click on the Emulator tab to test your dialog flow. Ask your bot who they are:
Go to the debug mode and select the first message in the messages list who are you
to view the received information after sending this user message.
The context who_are_you
has been added to the user session with an initial lifespan value of 1
as you can see in the context section
The user is redirected to the bot dialog
The NLP result section shows that the 'who are you' intent has been recognised as top scoring intent
In the Message Data section, we see the message being sent by the bot as answer
In the User Session section, we see the context list of the user with name and lifespan
The next tutorial will show you how to redirect the user to a specific bot dialog, depending on the conditions of the values in session variables.