-: We are going to see how to try assistants
in OpenAI's Playground.
Let's jump in.
First, we are going to enter openai.com and login.
We are going to hit on API,
and on this left panel, we are going to go to Assistants.
And we are going to hit on Create an assistant.
Then we'll begin creating an assistant.
Let's go with career advisor,
AI career advisor.
And here I got something ready.
"You are a career assistant.
"People will come to you looking for advice
"on how to build career on AI.
"Your task is to use all the knowledge
"in the ebook you have uploaded
"to assist the user to create list of useful advice
"and a roadmap on how to prepare themselves."
Okay, so, we are going to use GPT for Turbo model,
and we are going to use retrieval to be able
to get information from this ebook
on how to build a career in AI.
So, now we have prompted everything we need.
We are going to hit on Test.
There we go.
We have our playground with our AI career advisor.
So now, we are going to begin doing some testing.
So here we can continue editing our assistant,
and we can add more files here if needed.
Let's begin doing a first prompt.
I want to build a career in AI.
Can you help me?
So here it's a little bit different from using ChatGPT.
We had to send the message first and then click on Run.
And there we get the answer.
So says, "I'll be happy to help
"to provide the most accurate and personalized advice.
"I have a few questions."
Great, because we prompted it to ask questions.
"What is your current education
"and professional background and experience.
"Looking for advice?
"What areas are you particularly interested in?
"Do you have any specific goals?"
Okay, let's write some answers.
I am an engineer.
I have a little experience with Python.
Yes, I'm looking for a advice
on educational paths.
"What areas of AI are you interested?"
I'm interested in, let's say, generative AI.
"Goals or companies in mind where you like to work?"
Not really.
Maybe just remote work.
And again, we hit on the plus,
and then we hit on Run.
So if it takes a little bit,
it's because it's doing the retrieval on our ebook,
but let's see the results.
"Great, thank you for writing information.
"Given your engineering background and some experience,
"you are already on a promising path."
Great.
So understanding the basics, strengthen Python skills,
that's a great advice.
Math foundations, great.
Educational paths.
Online courses, great,
special certificates or nano degrees.
Participate in open source projects, that's a great advice.
Building a portfolio.
Logging and sharing knowledge.
This is supposed to be information from our ebook.
Networking and job search.
So, what we are going to do here,
it's to verify that it's taking information from the ebook.
Please take
a quote from the ebook
on every advice you are giving.
Let's go send the message and click on Run.
Again, it's taking a while.
You may notice that this takes far longer than ChatGPT
or the API with it before.
This is because it's doing lots of operations
in the background.
So we already have the result.
Let's see.
"Here's a revised plan with direct quotes from the ebook."
So, for example, deepen your technical skills.
"For example, it's important to understand models
"such as linear regression."
So here I have the ebook, "How to Build Your Career in AI"
from Andrew Ng.
Let's look for linear regression
and see if the quote is correct.
"For example, it's important to understand models
"such as linear regression, logistic,
"neural networks, decision trees."
So, yes, it looks like it's retrieving the ebook correctly,
and we have all the quotes we asked for here.
Also here we can see the token count for this conversation.
Always be aware of the cost of each model and each function.
That's it for trying assistants into OpenAI's Playground.
Now we are going to see a similar example
inside our code editor.