-: Okay, so this is just a quick video
showing you the different types of things
that you might want to look at
when you're exploring OpenAI's platform.
If you click on the Dashboard in the top right,
you'll see that you have access to logs.
This can be a way for you to see
how your application is performing in real time.
This is something that when you have a productionized app,
you will look at the logs and see exactly
how the responses are coming out versus users
that are using your chatbot or your LLM-based solution.
There's also traces, which is specifically for agents,
and you also have batches.
I'm gonna skip over assistants
because that will be deprecated.
Batches allow you to do a 50% cost reduction against OpenAI
with a 24-hour turnaround.
This is what it would look like in a real life project
where you have these batch files,
you can go and look at the input and the output,
and you can see whether the batch was canceled
and what the status of that batch was.
The evaluation section allows you to create evaluations
for different types of your models.
So the way that this works is
you store your chat completions,
you create data for the input and the prompts manually,
you upload a file, and then you create a custom evaluation
where you basically will be able to figure out
whether your chatbot is actually doing
what it thinks it should be doing.
Fine-tuning is where you can create custom models
based on your training data.
You can customize these models so that
you can easily have more control.
I would recommend looking at this
when you have around 1,000 to 2,000 examples
and your application has been running for several weeks
and you have lots of data.
You also have access to storage, so files and vector stores.
Vector stores allow you to basically store some text,
which you can then search against in real time,
and you will often use files which are stored
inside of vector stores, but you also use files
for the batch API too.
The other good page to look at is something called usage,
and the usage, if we're gonna go
and have a look at one that has more,
we'll show you the breakdown.
So you can see here we have
a large number of chat completions.
If we look at the spend categories,
you can see which type of models you have
and what costs of those they are.
If we go back to the API capabilities,
you can see we're mainly spending on
the chat completions endpoint.
However, there's a variety of different services
that OpenAI offers, and you can see
how much you would spend on that.
You can also filter this by the 14 days or the 30 days,
and you can see the breakdown of users and services
and API keys as well.
The other things that I'll just point out here is
there's this Cookbook link that is a really good place
for you to figure out how to do different types
of applications using OpenAI.
As well as that, I would also recommend
in the top right clicking on Docs
and having a read through all of the core concepts,
the built-in tools, and also agents.
This is gonna give you a good understanding
as to all the different types of capabilities
that OpenAI's API offers for you.