When the intent 'who are you' is recognised our train traveling assistant introduces himself and asks if the user would like to order a ticket.

​

At the end of the Book train ticket conversation flow the chatbot asks a booking confirmation.

Both bot questions expect a user intent answer of yes or no. To support 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

• Add output context confirm_booking in the bot dialog Confirm booking with a lifespan of 1. When a user reaches this bot dialog the output context with the initial lifespan value 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. 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. A bot dialog intent can also be linked to multiple input contexts for intent re-use in subflows of flows.

• 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 with a lifespan of 1

• 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

Test the flow in the emulator

• Click on the Emulator tab to test your flow. Let us ask our traveling assistent who he is.

• 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 teaches us how to redirect the user to a specific bot dialog depending on the conditions on the values in session variables.