![]() In this example, we use our web-based React chat platform as the only input/output of the bot.Ĭonversation flow and bot reactions definitionįinally for each intent we define the bot reply. our bots that let you talk with GitHub from Slack). Xatkit supports a number of platforms (and you can build your own!) so the next step is to declare what combinations of platforms your bot is going to be using (either calling actions on the platform or getting events from it). getting the user name and using it to answer her in a more personal way later on in the bot workflow). ![]() ![]() In a similar fashion, you can also define mapping entities and parameters to collect relevant data from the user utterance during the matching process (to be used later on in the response, e.g. We can easily create the intents the bot should recognize (in this example, the greetings and how the user is feeling right now) and the training sentences to be used to teach the bot how to understand them (these sentences will be used, for instance, when configuring the bot to use DialogFlow as Intent Recognition Provider). You can find the full source bot code here, in the following I’ll just focus on a few core parts. We’ll be adding more documentation on the new Fluent Interface / DSL constructs soon but let me present to you the key ones in this GreetingsBot example, a simple bot that just says replies when it detects you’re greeting it. We have now released a new version of Xatkit and its runtime engine so that you can start using this new syntax in the creation of your bots. So, we are basically combining the benefits of having a specific chatbot DSL with the power of a general-purpose language.
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