Welcome back to Jupyter Lab, where I want to show you the assignment, the homework exercise for you
for the end of week one, coming into the week one folder.
And you'll see here week one exercise so you can see there's rather little here.
There's a little framework to tell you what we're doing.
So the idea is for you to build a little tool that will be used by yourself as something that can be
your guide during this course.
It's going to be a tool which will be able to answer questions on code, on llms, on things that you
might run into along the way and be your sidekick, your your customized copilot for this experience.
And this is what it's going to do.
Uh, it's going to you're going to fill in some inputs.
You're going to you can just use these two constants we've got here.
You're going to be using both GPT and open source llama running in llama on your computer, something
which you're familiar with from our week two assignment or day two assignment.
You'll put some code in here to set up your environment.
And then this is where you will type the question that you want to ask your tutor, your personal private
tutor.
And in this case, I am asking it to explain what this code does and why.
And this again, is that line of code that we looked at a couple of times, which is has a few different
things going on there, and this is the better version of the code than the one I originally wrote.
This is the version that I think it was.
Yeah, it was GPT four with canvas that wrote this version of it.
So we will provide this, and then you will fill in this piece of code here, which will get GPT four
mini to answer.
And you should try and answer and have that response stream back and use markdown, uh, so that it
appears in full glory.
Uh, and then do the same thing again for llama 3.2 and see the answer there.
So this will need you to to write the code from scratch and sort of type it out.
And of course you should look back at the fragments of code that we came up with on the prior days and
used that to build this, and hopefully it will be something that will come reasonably naturally and
you'll be used to the familiar .0., blah, blah, blah, blah, blah.
It's all going to be something that will be in your memory and you'll also be very comfortable, I hope,
with creating the messages list of dictionaries, something that you're used to at this point.
Um, and when you do that, you'll see what answer that you get for this.
And it's actually a remarkably good answer.
Again, I think much better than I could do.
Uh, and it would be interesting to see whether you're also happy with the answer that you get from
a minuscule model that is much, much smaller by comparison.
And see how you compare those two.
And then in the future, you'll be able to use this as a bit of a resource.
And so I hope this this is useful for you.
And in fact, after week two, you might want to come back to this and add a user interface to it.
So you could have like a little tool running on the side that would be uh, could be super handy.
Uh, one also thing that you might do is that what I've done here is I've just put down the question
as a global variable.
You might instead want to see if you can think about a way that you could take that in as an input and
be a bit more dynamic about this.
So it could just be a cell that you run, but maybe do that as a as a later improvement.
Now I've done this and the solution is sitting in this solutions folder, but I urge you not to look
at the solution.
Uh, not not unless you you find yourself feeling stuck.
There's nothing worse than feeling stuck.
If you do feel stuck, you could always try first asking ChatGPT or Claude for a nudge, but otherwise,
please, please, please reach out to me.
There is no reason whatsoever to be stuck with this.
It should be something that you that you're able to to get through.
And I would love to help you with that.
Get you to a point when you have your own personal, technical and data science tutor to help you along
the way.
So, um, above all, be sure to have fun with this and I will see you back for the wrap up video for
week one.