Once you start using Dialogflow, you will begin to really acknowledge the power of Google’s AI and How you can get users to the streams and sequences of random messages you receive from your users.
Dialogflow provides predefined system entities that can match many common data types. For example, there are system entities that match dates, times, colours, email addresses, and so on. You can also create your own custom data matching entities. For example, you could define a fruit entity that could match the types of fruit available for purchase with a grocery store agent.
The following tutorial will show how to reply back to the user by their name.
With the help of the Kommunicate user interface, I will demonstrate how the conversation flow works. Please check the link to find out how to integrate Kommunicate with Dialogflow.
Words within phrases could have different possible values, and instead of creating different phrases for each name, possible values for a name would be grouped into an entity.
- Create a new Intent to get a user name where the user asks what the bot can do. The bot first asks for the name of the user.
- Provide training phrases for this intent, DialogFlow will recognize parts of the phases that contain the entities you have just created. It will give different colors to different entities. In this case, the entity will be @sys.given-name, and we’ll refer to it as $given-name.
- Check conditions with Custom User Fields using Parameter Values captured or not captured when users trigger a Dialog Flow Intent.
- Set the default response with the parameter value for the intent you have created and save the changes. Now the chatbot can recognize and remember the names of users and greet them with their names.
The saved changes can be tested on Kommunicate chat widget
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