Congratulations! You are about to discover what Teneo is all about and the core concepts behind it. The 'LUIS^Teneo' section will get you started with the Teneo platform together with LUIS. They provide step-by-step instructions for building intelligent chatbots in Teneo.
Once these are done we will show you more on:
You've just signed up and gotten your hands on your fresh Teneo developers account; if you haven't logged in yet, please log in using your sign-up credentials.
Once logged in, you are greeted by the Team console. The team console is divided into three main areas.
When your environment is ready, the status will change to 'Starting'. A download and a Studio browser link will appear.
We highly recommend the use of Google Chrome for the browser option.
Follow the setup instructions for the Studio client.
Now that you've managed to open Teneo Studio, it's time to get to work. Let us start with entering Studio:
Once logged in you will be greeted by the main solution window. Here, you'll find the solutions you have recently worked on and the solutions you own.
In this view, you can see all the solutions available to you in this environment. A solution can be thought of as a container where all the bots' knowledge is stored.
As you can see, there's already a solution called 'Longberry Barista' available to you. Each team gets this pre-built solution which can act as a reference solution when you're building your own bot. Let us take a look inside:
In this section, you can find meta-information about the solution, such as when it was built, when it was last updated, and when it was last published.
Now it's time to build a bridge between your LUIS solution and Teneo. This will make your solution to bypass Teneo's native classifier together with it's classes inside Class Manager and instead use LUIS native intent classifier.
The first step is to add LuisPredict.groovy to your solutions file resources. This .groovy file contains the needed code to make this possible.
/script_lib
.It's time to visit the LUIS application to collect some details which later will be used to connect this LUIS application to your Teneo solution. But first, we'll need to import intents to our LUIS application. When you created your solution, you based it on the 'Longberry Baristas' template solution which comes with many prebuilt flows and intents. To make sure LUIS is aware of these intents, we'll need to import them into your LUIS application.
Once the application is created and trained it's time to collect some details, so we can add them to your Teneo solution later. You can temporarily store them in a text file.
Now it's time to prepare our Teneo solutions by adding a Global Variable and a Global Script.
First, we'll add a global variable called luisPredict
to the solution. This variable should contain the API keys of your LUIS application. Before we add the variable to the solution, let us prepare its value. Copy the following code and populate it with the values you collected from your LUIS application above:
new LuisPredict('primaryKey','endpointURL','AppId')
The result should look something like this: new LuisPredict('12345678910abcd','https://www.luis.ai/applications/abcd-efghi-jklmn-opqres-tuvw-qq-112112/', 'dcba019876543210')
Now, let's add the global variable:
luisPredict
.Now, let's update the global Pre-Matching script:
luisPredict.predict(_)
.Being able to have a conversation with your chatbot is a crucial part of the development process to ensure that everything is working as intended. Luckily, you don't have to go far to test your chatbot in Teneo, let us use the 'Try Out' to order a coffee!
Hello!
I would like to order a cappuccino
John
Goodbye
There are multiple ways of interacting with a chat bot, such as through an app, on a website, or in your car. Let us publish the Longberry barista solution so that we can have a chat with it through Teneo Web Chat.
Congratulations, you have just made your first solution available online! The next step is to interact with it. There are two ways to interact with a newly published solution, you can either interact with it through a test page or a chat widget. We are going to show you how to try out your bot through the chat widget, Teneo Web Chat.
Teneo Web Chat is also available in the Bots section in your team console. You need to publish the bot from Teneo Studio before using it.
Hi!
I would like to order a flat white
John
Goodbye
The chat widget that you just tested is known as Teneo Web Chat. This widget can be embedded in websites and supports rich media such as buttons, cards, quick replies, and much more!
If you want to try out your published solution via the test page, click ‘Open’ in the publication confirmation pop-up. If you have already closed it, you can click the URL shown in the ‘Publish’ window instead. This will open a test page where you can try out your bot.
Currently, the 'User wants to order a coffee flow' grabs the coffee type when we mention it in the first input. Sadly, this is not the case with names. Our goal with the next few steps is to fix that.
Before:
User: I want to order one flat white, my name is John.
Bot: Ok, what name shall I note for the order?User: I just told you, my name is John!
Bot: Thanks for your order, John. Your flat white will be ready for pickup in 5 minutes.
After:
User: I want to order one flat white, my name is John.
Bot: Thanks for your order, John. Your flat white will be ready for pickup in 5 minutes.
Now let us explore how these conversations are possible!
Let us go back to Teneo studio and edit that flow, and the option to store the name in the first input while ordering coffee.
PERSON
.Now it's time to specify when the output should be skipped:
userNameForOrder
into the 'Skip Conditions' field. This will be evaluated to true if the variable is set and to false if the variable is empty.Now that we have updated the flow we need to republish to make the changes available online.
I want to order one flat white, my name is John.
Congratulations! You have now experienced a small glimpse of what Teneo is capable of.
Now that you have had a brief introduction to the Teneo platform let us continue with more info about working with LUIS^Teneo.
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