![]() Now we have to create a Lambda function that handles the requests from the bot. Since the slot is required, the prompt field will be useless in this case, but as Amazon Lex requires us to fill in something, let’s type “whose birthday?”. And for the type of the slot, we will choose AMAZON.Person, and we will define the slot as “required”. We also have to define a name slot so that Amazon Lex can recognize it as such. Having this in mind, we proceed to create the utterances. On the other hand, utterances can also contain slots, which are variable values given by the user when asking the chatbot (for example: if you expect the user to type questions similar to “when is Mike’s birthday?”, “Mike” will be a variable value, so you can configure it as a slot in the utterance, by indicating it with brackets: “when is birthday? An intent can have multiple utterances, some of them can be used to increase the possibility for the intent to be triggered, by setting several similar expressions. As Amazon Lex uses a deep learning engine to recognize these expressions, the utterances don’t have to be the exact text you expect the user types/says. Utterances: Here, you can set the text expressions that are going to trigger the intents. Each intent is independent of the others. They manage the different tasks that can be done with it (e.g., book a flight) and can be configured separately. Intents: These are the main components of a bot. Here’s a brief explanation of a chatbot’s components: There is a free tier that allows a maximum of 10,000 text requests and 5,000 voice requests during the first year.Ĭhatbots in Lex follow a structure that allows us to create them in very few easy steps. The costs associated with this service vary depending on the number of requests made to the bot. Amazon Lex also offers an SDK to deploy the bot in a mobile app (iOS or Android). This reduces a lot of development time and costs. This means that you won’t have to deal with text or speech recognition, but Amazon Lex will do it for you. ![]() Amazon Lex uses the same engine as Alexa, and it provides a very straightforward way to develop a chatbot in a few easy steps, having only to develop the logic that interacts with our back-end or third-party APIs. One of the platforms that allow us to develop chatbots is Amazon Lex. This allows us to create beautiful virtual assistants. They can also be developed to accept voice questions. ![]() Text and voice: Interaction with the chatbot is not limited only to text.This gives them much power to do great things. Direct interaction with APIs: The bot’s logic can be programmed to interact directly with our back-end API or a third-party API or service.Queries and transactions: Chatbots offer not only the possibility of asking questions but also making transactions (e.g., placing an order, booking a flight, setting up a calendar event, etc.).Reduction of call center costs: Some questions and their responses can be fully automated, so there is no need for a person answering those questions.Automated responses: They can be programmed to give an automated response to the user based on the user input (voice or text) and the data stored in the system.The capabilities they offer are endless, but to name some popular uses, you can: get support, order a pizza, book a flight, query about your schedule, and many more.Īmong the advantages the chatbots offer, here are the main ones: The popularity of chatbots these days is so important and the advantages their offer are so vast, that lots of companies have started using them in the last few years, leaving behind the need of a full-service call center (in some cases leaving behind the whole call center).
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