PRIYANKA VERGADIA: Are you building
conversational experience but would
like to cut down your design and deployment time?
Stick around as I show you the pre-built agent
templates in Dialogflow CX.
Hi.
I'm Priyanka Vergadia.
In this episode of Deconstructing Chatbots,
I'm going to show you how to decrease your design
time by using Dialogflow CX pre-built agent template.
Although we are not traveling like we used to,
we may be renting cars to get around safely.
Let's see how our friends at AlphaCar, a rental company,
can easily deploy a booking agent.
Imagine you are a manager at AlphaCar
and have noticed an uptick in chatbot and email volume.
But you have a small number of customer service agents
and not a lot of experience deploying a chat agent.
That is a perfect scenario for a pre-built agent template.
Let's see how to set it up in the console.
The first step will be to create a Google Cloud platform
account and a project.
If you already have one, don't worry about this step.
Then go to the Dialogflow CX console.
Click on the project we just created
to import the pre-built agent.
And click Use Pre-Built Agents.
We see a number of templated agents that we can import.
For AlphaCar, let's import the travel car rental agent.
Select a desired location, and create.
We now have the foundational architecture for our agent.
Let's see how the agent currently functions.
Best way to do that is to navigate to the Test Agent
button and start a conversation.
Now that we know how it currently works,
let's modify some of the agent's responses
to make it customized to AlphaCar, starting
with the default welcome intent response on the Start page.
While we are here, let's also modify the sign-off messages
at the end.
Now let's take a look at our custom entities.
Perhaps AlphaCar only offers a select few cars.
So let's swap out the Mitsubishi Mirage and Nissan
Versa with Ford Fusion and Chevy Malibu.
We will add some synonyms and name variations, too.
Now that we've changed these custom entities,
let's change the agent option that are provided
in the middle of the flow.
We are going to click on the Mitsubishi
Mirage and the Nissan Versa pages
and change the necessary information in the entry
dialog.
In production, these page options
may be fed by dynamic integrations
with an inventory CRM, but for the purpose of this demo,
we will hardcode these options.
Now we have a customized flow for AlphaCar.
Let's say AlphaCar knows they get a number of questions
about forms of payment, and they want
to be able to answer those to contain their users.
Let's create a route group with a couple of common questions,
like what forms of payment do you accept,
and when will my account be debited.
To do that, we will go to create a route group.
We will name it Payment Questions and add Route.
Then we will create an intent for each of those questions
with some training phrases.
Once we have added these training phrases and the route,
we save them.
We can enter the fulfillment response now, as well.
For instance, we accept Visa, American Express,
and Mastercard, and your account will
be debited when you return your car rental.
Now let's add that route group to the Car Option page
under Add Route Type inside Route Groups.
Great.
Now let's test the agent using the simulator
to make sure everything's working as expected.
Yay, everything seems to be triggering appropriately.
Now let's add this flow as a test case.
Test cases allow us to uncover bugs and prevent regression.
We can then revisit this flow and others
in the Test Case section, which allows us to rerun all the test
cases, import and export, and view the test coverage
for transitions and intents.
This will help us make sure we're testing
every part of the agent.
It's also a good idea to look at the validation section
to see if there are any recommendations or errors.
It seems like it has spotted similar training phrases
across multiple intents.
This can present NLU confusion down the line,
so best to resolve that by deleting or modifying
selected training phrases.
Let's fast forward to being ready to deploy.
We're going to want to use versions
to move our current development environment into production.
A draft flow is updated every time a developer on our team
makes a change.
As a best practice, we should always test our draft flows
before promoting them to production versions,
although we can always roll back to previous versions
if any problems are discovered.
With that, our AlphaCar agent is now live.
All that's left to do is to regularly
look at the analytics section to improve
the agent by assessing how it's being used in production.
All right, so we just created an entire conversational
experience to book a rental car in literally five minutes.
That's exactly what pre-built agent templates are for.
They increase the speed to market.
Now it's your turn.
Explore a pre-built agent that makes sense for your project
and share your experience with me in the comments below.
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