And for the final piece of background information, I wanted to take another moment to talk about API
costs.
It's something that I mentioned before.
I've also got a section on this, of course, in the readme too.
So as I said before, there is this.
It is confusing that there is typically this pro plan associated with the chat web interfaces like ChatGPT,
which is typically $20 a month, uh, in the US, and similar amounts in other territories, uh, and
with a monthly subscription, uh, it's somewhat rate limited, but but basically there's no charge
per call.
And it's, it feels like you have an almost unlimited ability to be calling the model through the chat
interface.
The APIs are different.
The APIs do not have a monthly subscription, but you pay per call, and the costs that you pay depends
on the model that you're using, and also on the number of input tokens and the number of output tokens.
And it charges you.
The total cost is a combination of those two.
It's a smaller charge based on the number of input tokens, and a slightly higher charge based on the
number of output tokens.
But I should stress that the total costs are overall very low when it comes to the individual calls.
If you're looking to build a system that will be making large numbers of calls, then the numbers add
up and you have to be very sensitive and aware of it as you scale.
But in the kinds of projects we'll be working on, the costs will be quite small, and I would like
to show you exactly what that is in just a second.
I do want to say that generally, as far as you're concerned, for this course, probably when it comes
to API costs, what will matter the most is that these days these platforms seem to require a minimum.
In the case of OpenAI and Claude, at the moment in the US, they require you to put on at least a $5
worth of credit that you then draw down on.
And in this course, we won't scratch the surface of that $5, but you do have to put in that initial
amount, but there will be plenty of opportunities for you to be using that in your own projects in
different ways.
And I think it's a great investment in terms of your education and ability to use these models to build
new projects for yourself, as well as build your education and your experience.
Having said that, if that is something that you're not comfortable with, as I say, now that we see
how to use a llama and you've built that as part of the last exercise, you would be able to use a llama
instead of using either OpenAI or Claude or Gemini at any point.
You've got some practice doing that now with the last exercise, and you can put that into action should
you wish.
If you're not comfortable with with the API costs.
But with that background, let me now take you to a site where I can show you a bit more insight into
the API costs and also the context.
Windows.