- [Instructor] Before we dive into the code,
I want to show you what we'll be building.
Meet our hiking_agent.
Now let's say I want to go for a hike.
I'm going to run the agent,
and what it will do is it will check the weather near me
and it'll see if it's suitable for hiking today.
So we can see it's partially cloudy
with an average temperature of about 13 degrees centigrade.
And the model says, you know,
it's going to judge that that's a good day for a hike.
And if it is, and it is right now,
then it's going to find some national parks that are near me
to give me some suggestions.
So right now I'm filming in California,
so it's going to start looking
for some national parks in California,
look through those and give me some suggestions.
And here they are.
So it's found the Golden Gate National Recreation Area,
it found the Sequoia & Kings Canyon National Parks,
or it's also found the Redwood National and State Parks.
And it gave me some details on this,
including a little opinion.
It's perfect for a relaxed stroll,
or it's a great challenge, or my personal favorite,
and here is number three,
it's best for a cool, shaded walk inside a dramatic canyon.
Now think about the complexity
of what just happened here for a moment.
The agent first figured out my location,
and then it checked the weather at this location
to see if it's suitable for a hike.
And then it searched for national parks near me
in the state that I'm in, that I could hike in.
Now that would be a really large cognitive load
if I were to do it myself.
And in the past, you'd go to Google Maps
or something like that.
You would search, you would take look, you would make notes,
you'd go to a different service, you'd look at the weather,
you might read reviews of some of the trails
to see like are they the kind
of thing that you would want to do?
And that's a large cognitive load.
And that's what agents are really, really good at.
And in this case, this agent is entirely local
and it's powered by Open Source GPT.
So we're going to see how to build this agent
over the next few videos,
and we'll start by getting our environment set up.