All right, so we got the workflow ready.

I'm going to open up this form and I'm

going to drop in an image of myself. And

for the image prompt, I'm saying a

hyperrealistic image of this man shaking

hands with Adam Sandler. It's close up

enough to see extreme detail, but we can

still see both people in frame. So, I'm

going to go ahead and shoot this off,

and I'll check in with you guys when we

get that image.

I don't even know what to say. This is

ridiculously good. I really don't love

the idea of zooming in closeup on my

face in front of the entire internet,

but this is incredible. Look at the

amount of detail that they put into this

image. Anyways, let me show you guys how

we do this with Nitn and Nano Banana

Pro. It's been a crazy week in the AI

space and now we've got Nano Banana Pro

to play with. Nano Banana by itself was

already amazing, but the Pro version

comes with so many upgrades. Here's an

example of an input image being turned

into an infographic. Here's another

infographic, and you can also see that

all of the words and letters are

correct, which sometimes was an issue

with Nano Banana. Here's a cool and

really creative example of the word

Berlin spelled out across multiple

buildings. I also thought this one was

pretty cool where it was able to just

translate the English words into Korean.

And one of my favorite parts about Nano

Banana is the ability to combine tons of

different images together. In this

example, you can see 14 different images

of these little monsters were fed in and

then the image produced all of them

sitting together in one environment. You

can also do this with different people

with different types of clothing with

furniture. So all of these six images

were fed in and this is what we got in

the end. Here's another quick example

with these different elements. And then

one final one. That one's pretty cool,

too. But anyways, what I'm going to be

showing you guys today is how we can use

Nano Banana Pro in NADN so we can power

our automations with better images. I'm

going to be going over three different

examples here. First, we've got text to

image. Then, we're going to be doing

image to image. And then finally, we'll

do multiple images to an image. And the

way that we're going to be accessing

Nano Banana Pro is through key, which is

kind of like an AI image and video

generation model marketplace. As you can

see, we've got Sora 2 VO3.1, and right

here we have Nano Banana Pro. It's also

crazy because Nano Banana Pro through

KAI does two really cool things. It

gives us no watermark, so we don't get

the little Gemini logo in the bottom

right of our images. And we can get our

images in 4K for just 12, which is about

20% cheaper than the official price. But

you should note that pricing may change

in the future. So right now, if you can

get it for 12 cents a key, then get here

and take advantage of it. Anyways, the

reason why we're here in Keyai is so

that we can access Nano Banana Pro

through our API calls in NIN. And so

that's why we can look right here at the

API documentation and create our tasks

and basically make requests for images.

Now, if you just want to get a feel for

it and play around with it a little bit,

you can test out prompts and images in

the playground environment right here.

You can see here's a funny example where

I dropped in an image of me, an image of

Scotty getting his green jacket, and I

said basically to put me in that

environment. And this is what we got.

And I mean, once again, a really good

picture, really good detail. The hands

even look decent. The background looks

good. This is just really impressive.

That's enough wasting time. Let's get

into this first demo with a text to

image flow. So, if you guys want to

download this workflow so that you can

just plug in your API key and just get

going, then I will leave that for free

in my free school community. The link

for that will be down in the

description. So, when you guys get this

workflow, all you'll have to do is

change a few of the prompts in these

nodes, which I will show you guys right

now. So, for our first example, the

image prompt is in here, and I said a

hyperrealistic image of the Chicago

skyline at sunset. So, I'm going to go

ahead and run this first row. And while

this is running, I'll explain real quick

how this all works. So you can see that

we're making two different API calls.

The first one that we're making is to

actually create the image. So if I click

into here, you'll see that we're hitting

the endpoint to create a task. Then

we're putting in our API key. So when

you get this workflow, all you'll have

to do is replace this string with your

own API key. And the way that you can

get your API key is you go to key.ai,

you make an account, put in some billing

information, and then on this lefth hand

side, go to API key, and then all you

have to do is create a new one, and then

copy that value. like I said, right into

here instead of where mine is. And then

you can see we have an actual body

request, which is our image that we

want. And so we want to use the model

Nano Banana Pro. We put in our image

prompts right here, as you can see,

which comes through as a hyperrealistic

image of the Chicago skyline at sunset.

We have our aspect ratio, we have our

resolution, and we have our output

format. And so in case you're wondering

where I got all of this information

from, I got it from the API

documentation of Nano Banana Pro right

here, where you can see it gives us the

endpoint. It gives us what we need to

include. So, we need to include the

model, which is Nano Banana Pro. We need

to include the input prompt, which is

how we turn that text into an image. And

then we have some other optional things

like the image input, which I'll show

you guys later when we do an image to

image example. We have the aspect ratio.

So, right now in this example, we're

doing 1:1, but you could also do 2 3,

32, 16:9, 916. And then we have our

input resolution, which we can do 1K,

2K, or 4K. And then, of course, finally,

we have the output format. So, that's

the first API call that we make. And

what happens after we do that first one

is it comes back to us and it says,

"Okay, cool. We got your request and

here is your task ID." So the way that I

like to think about this is when you go

and you order food at some sort of

restaurant and they give you a number.

This is basically the number that they

give you and they're telling you, "Okay,

we're going to work on your food." And

so while they're working on our food or

our image, what we have to do is wait.

So I've got a wait note here which is

going to wait for about 5 seconds. And

then after it finishes waiting, we're

going to make another API call. And this

one is to get the image. It's going to

check the status of our request or our

food order. And so the way that I filled

out all this information was I came into

the API documentation for Nano Banana

Pro. And then I went to query task

instead of create task. And so I'm not

diving super deep into the API stuff

right now. If you want to see a full

breakdown, I've got a really good video

on that. I'll tag that right up here if

you want to check it out. And the query

task one is much simpler because all we

have to do is we have the endpoints and

then we have to give it that task ID or

the order number and then we give it our

API key once again. So in any what that

looks like is the task ID I was able to

drag in from this lefth hand node and

this is what the create image API call

gave us and then of course I'm giving it

my API key down here. And so when we do

this you can see we have kind of this

loop. This is called polling which means

every 5 seconds we're basically going to

keep checking in to see if it's done.

And you can see here it took 13 tries.

And so what happens is we do this switch

node because when we check in on our

order they can basically tell us it

worked. it's still generating or it

failed. And so we have three different

paths for those three different

scenarios. And what you can see is if

it's still generating, it loops back. It

waits five more seconds. It checks

again. If it fails, the process just

ends. And if it's successful, it moves

on to the next step. So that guarantees

that we just only move on if we were

successful and if the image is done. And

then when it's done, we move over here

to the result and we get this final URL,

which I will go ahead and download real

quick. And we have our beautiful image

of the Chicago skyline at sunset. And

this is actually crazy. I mean, look at

the water, look at the cars, look at the

lights, the sky. Like, this is actually

really, really good. All right, so the

good news is now that we understand this

flow, the two flows beneath are pretty

much the exact same thing. The only

difference is instead of just sending

over text in the body to make the

request for the image, we're also

sending over either one image or

multiple images. So that's really the

only difference here. Okay, so let's

move on to the second example where

we're getting an image and we're turning

it into a different image. So I'm going

to open up the form and what I'm going

to do is type in an image prompt and

drop in an image file. Okay, so I

dropped in an image of me holding my

laptop and I said make this man sitting

on a beach using the laptop. The image

should be hyperrealistic. We should see

all detail. And keep in mind these

prompts are not optimized or very good

at all. But with this little of a

prompt, you'll see how good the results

are. So I'm going to shoot this off. We

turn that image into a public URL

because Nano Banana needs a URL to be

public in order to use it and view it

and change it. And then we're going to

do the exact same thing where we're

waiting. And actually, what you can see

happened here is this failed. And so

that's why we have this as a switch with

different paths. And actually, I'm kind

of glad that that happened so I can show

you guys how we can check our logs. So

if you go back into key and then you go

over here to the logs, you can see your

different runs and if they were

successful or if they failed. And what

I've noticed is that right now because

Nano Banana is super new and probably

tons of people are using it. Sometimes I

get failures when I just kind of like

shouldn't. And you can see the message

here is just a 422 and it says

unexpected error handling prediction. So

I'm just going to run that exact same

example with the same picture, the same

prompt and run it again and I'll show

you guys that it goes through. All

right, so that just finished up and you

can see it's literally the exact same

image. It's the one of me on the laptop

and what I dropped in as the prompt was

the exact same prompt. So sometimes it's

just going to fail and it's not even

your fault. So just wanted to let you

guys know that. But let's go ahead and

take a look at this results and

hopefully it's pretty good. All right,

there we go. I would say that this is

pretty solid. It even got my haircut in

there. It's got the shirt and we can see

that I've even got some sand on my hand.

We've got a nice little reflection in

the Apple logo, too, which is a nice

touch. But I mean, this stuff is pretty

solid. And so really the only difference

here, of course, is that we're sending

over an image with the text prompt. So

we get our image in the form as binary.

We use this HTTP request to turn that

binary into a publicly facing URL. As

you can see right here, if I open this

up, we get the laptop image. And then we

pass this URL into key for Nanoban to

use. And we do that in the body request

of this down here. And as you can see,

we just have one extra little object in

this JSON body. And that is called

image_input. And then this is where we

put the variable for our picture URL.

And that obviously comes across over

here. So now Nana Banana has a picture

and it has our prompt and then it goes

ahead and combines those to make the new

image. All right. So you guys remember

how right here I told you we had to

upload that binary picture to imageB in

order to turn it into a publicly facing

URL. Well, I'm going to show you guys a

different way that you could do it down

here where you don't have to do that,

but you do have to make sure the image

URLs are public. So you can come into

this node and you can set a image prompt

and then three different images. And all

of these are public facing URL images of

an Amazon product. So the first one we

have is a Santa shirt. The second one we

have is this Whoop. And then the third

one we have is this Oala water bottle.

And what we have as a prompt is a

hyperrealistic image of a man wearing

the shirt provided in the image. He's

hiking on a mountain and is holding the

water bottle provided in the image. He's

also wearing the watch provided in the

image. So we're going to go ahead and

run this one. And once again, it's the

exact same flow where we send off the

request, we wait, we pull, and then we

constantly pull until we have our

success message. And by the way, while

this is running, if you guys noticed how

dark this is, and it's recent update has

like a new dark mode, and it's darker

than the original dark mode. And I made

a post in my community about it, and I

started to get a little bit roasted for

not liking the new dark mode. So, just

kind of thought that was funny. All

right, so this one just finished up. And

what you'll notice is because we did

three images, it did take longer. So,

this one pulled 35 times rather than

some of these were more like 13 or 15.

But let's take a look at this final

image. That's awesome. You can see we've

got the Oala text is almost perfect.

We've got the Santa shirt. We've got

some sweat on the arm and the whoop down

there. And this is pretty much exactly

what we were hoping to get. The whole

background looks super awesome as well.

But in this one, as far as the

differences in this node to this node,

there's only one. And that is in the

body request in our array of images that

we're sending over. We're just sending

over three rather than one. So anyways,

I know that some of these were fun

examples, but I hope you guys can see

how fast this stuff is improving. And

I'll be honest, it is a little bit

scary. There are certain concerns when

you don't have watermarks and when

things look so real, you can't tell if

they're fake or not. And I get that. But

it's very exciting to also think about

what opportunities this stuff actually

brings. How much more can small

businesses now do with content and ads

if they don't have budgets to go rent

out a whole studio and pay actors and

things like that? And you can now

literally place your products almost

anywhere and you can go get a

professional headshot without going to a

professional headshot studio. So, I'm

not trying to be oblivious to some of

the risks and some of the fears, but I'm

just trying to spread some excitement.

So, once again, download these workflows

for free. Just play around with the

stuff and see how you can work it into

your LinkedIn posts, your copy, your

content, whatever it is. use this stuff

to save you time. If you want to dive

deeper into some of these use cases,

then definitely check out my plus

community. We've got a great community

of over 200 members who are building

with nodn every day and building

businesses with Naden every day. We've

also got full courses in here. We've got

agent zero for the beginners,

foundations of AI automation. We've got

10 hours to 10 seconds where you learn

how to identify, design, and build

time-saving automations. For our premium

members, we've got one person AI agency

and subs to sales. And then for everyone

in the community, we've got tons of

projects in here which are kind of like

live step-by-step projects and builds

that you can follow along to. We also

run one live call per week in the

community. So, I'd love to have you guys

in those calls in the communities. But

that's going to do it for today. So, if

you enjoyed the video or you learned

something new, please give it a like. It

definitely helps me out a ton. And as

always, I appreciate you guys making it

to the end of the video. I'll see you on

the next one.