[DIALING]
[PHONE RINGING]
MARK MIRCHANDANI: (DISTORTED) This
is an intelligent automated system.
How can I help you today?
IVAN RAMIREZ: I'd just like to check the status of my order.
MARK MIRCHANDANI: (DISTORTED) Did
you say you wanted to place an order?
IVAN RAMIREZ: No.
No.
I just want to check the status of my order.
MARK MIRCHANDANI: (DISTORTED) OK.
I'll place your order.
How many units would you like?
IVAN RAMIREZ: No.
Cancel.
I want to check the status of my order.
MARK MIRCHANDANI: (DISTORTED) OK.
1,000 units.
I'll place that order for you.
IVAN RAMIREZ: No.
Stop.
Ah!
All right.
Welcome to "Take5."
Don't you wish that building intelligent useful chatbots
was easier?
MARK MIRCHANDANI: (DISTORTED) Sounds to me like--
it sounds to me like you want to talk more about Dialogflow.
IVAN RAMIREZ: That's right.
MARK MIRCHANDANI: Do you have a demo to show us?
IVAN RAMIREZ: Yeah.
Let's go ahead and jump right in.
[MUSIC PLAYING]
Here we have the Dialogflow console.
So let's go ahead and create a new agent.
We'll go ahead and call it Take5Demo.
We will select the language, English, for now.
But you see we have many options.
And we'll also select the time zone.
Finally, we'll attach this to a GCP project,
and we'll just hit create a new one for now.
Now that our agent has been created, let's go ahead
and define some intents.
But before we do, let's look at some of our pre-made intents
that were created automatically with our agent.
We have, first, our fallback intent, and also
our welcome intent.
Let's dive a little deeper into our fallback content.
This intent will catch anything the bot does not understand
and respond accordingly.
Here there's no need to add any training data.
But we can edit how the bot will respond to our users.
And by default we have some examples here on the screen.
Essentially, can you repeat that again, or, hey,
I didn't catch that.
Let's go ahead and go back to the main screen
and look at our default welcome intent.
Here the bot is looking for users' input,
such as hi, hello, hey there, or any other type of greeting,
and will automatically respond with its own greeting,
as you can see here.
To make things a little interesting, let's go ahead
and edit the text of the response,
and have the chatbot actually ask for the user's name
as part of that greeting.
So here we'll go ahead and add, what's
your name to every single option.
Now, let's add some common ingredients
that the user may enter, such as hi, hello,
and a couple of other examples as well.
This way the chatbot knows exactly what
to expect before it gives us its phrases.
Now, the great thing about Dialogflow
is that you just need to give it a few examples,
and then Dialogflow will go ahead and extrapolate for you.
We recommend at least using 10 examples,
so that Dialogflow can get an idea of the kind of things
that you should expect before it gives its phrases.
And once we've done this, we'll go ahead and click Save.
Now, from an intent, we can also add a follow up intent.
As you can see, we have a bunch of default options
you could pick.
But for this example we'll go ahead
and pick the custom option.
And now that we've selected it, let's
go ahead and dive into it.
The first thing we're going to do is edit the name.
And the name of this intent, we'll just call it, saying hi.
Now, just like we did before, we'll
go ahead and add some training phrases.
Since at this point the bot just asked us our name,
we'll go ahead and give Dialogflow
different examples of different ways
that someone may say their name.
As an example here, I'll put just the first name.
And you'll see that as I add examples,
Dialogflow will automatically identify that I
put a first name, a last name.
And even when I add other words, such as my name is,
or they call me, or I go by, Dialogflow
will still be able to identify which part of the sentence
is the name.
And we do this by using our natural language processing.
If at any point Dialogflow does not catch any particular name,
you can simply select that word, and then
tell Dialogflow that that is a name, that way you're
making sure that Dialogflow is understanding
the context of the input that the user is actually giving.
Now, as we scroll to the bottom, we
can actually add the responses that the bot will give.
And we'll have our bot say hello, and thank you
for chatting with me.
But since we want this to be a little bit more personalized,
we're actually going to include the first name
input of the user that was originally given to us.
And we do this simply by adding a dollar sign, and then saying,
given name.
This will make sure that whatever the given name
input was we're using for our output from the chatbot.
And then we'll go ahead and click Save.
So now that we've built a pretty simple robot,
let's go ahead and look at a quick demo.
We'll go ahead and go to the integration section
where you see we can integrate with a bunch
of different partners.
And we'll go ahead and click on Web Demo.
And here we have our chatbot live.
So we'll go ahead and say hi to it really quickly.
And we're prompted automatically to say our name.
And then we'll give it a brand new name
that it's never seen before.
So here I'll put Enrique Iglesias as an example.
And it automatically captured my name,
and I was able to say hi back to it,
even though it had never seen that name before.
I know this is a really simple demo of Dialogflow,
but just now imagine the possibilities
making a decision tree with different intents,
and different actions, prompting uses for different inputs,
and then tying in a back end that
can have actionable requests.
This is just the surface of what Dialogflow can do.
MARK MIRCHANDANI: So if you want to build
a great chatbot (DISTORTED) instead of one of these,
you should be using Dialogflow.
IVAN RAMIREZ: Yup.
And in less than five minutes, you can be up and running.
MARK MIRCHANDANI: (DISTORTED) Please
like, comment, and subscribe.
IVAN RAMIREZ: And if you're working on any cool projects,
please click on the link below.
[MUSIC PLAYING]