WEBVTT

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Now we can see this pretty simple automation that lets me to actually turn any boring mock ups of the

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t shirt hoodie to something really captivating.

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And there will be using actually OpenAI image model and other different nodes.

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However, let me show you how it works.

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So first things first.

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I can go over to Google and type t shirt designs or even something like that.

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Let me pick some t shirt.

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So for example this one and right click on that and copy the image address I can go over here, open

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the chart and just paste it.

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All right I can paste it here.

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And now the entire process is started.

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So we actually check first we provide the message.

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We check if the message is an URL.

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We use OpenAI to create for us a prompt for an image.

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Then what we do, we actually go over and in general create the entire image with the HTTP request.

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We convert that to the file, and at the end we upload that to Google Drive.

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So it's pretty cool.

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And in a while you will see how it works and how it looks like.

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So with this entire automation that contains only a few different nodes, you can create really captivating

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mock up designs.

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You can use them.

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You can sell like provide items for print on demand.

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And it's really again very nice.

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And afterwards I can see my new mock up is created.

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So let's click on view and nice.

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So like which one is better this one or even this one.

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I really love this one.

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Actually we've got surf California summer time.

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Best urban brand.

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We've got the exact year.

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It's so so cool.

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And the best point is actually you can use this entire automation every time whenever you see something

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or even you can customize that for different things.

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Let's say creating stickers, creating some images with text.

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Because remember you've got actually the model which is perfect in that case.

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So OpenAI image model that it's truly amazing.

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So with all that being said, now let's get into it and build this entire project from start to finish.

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So let's start with the trigger, which is our message inside chat.

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So here we just want to, um, just provide the URL.

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However afterwards let's provide the note which is if.

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So we check if it's an URL.

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So let's execute.

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Um actually let's go over here.

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Um no open chat.

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Um, let's open the chat, provide the URL.

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Okay.

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And now, um, we can go over here and pick the value.

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So we've got chat input and now we can actually go over to string and start with we can provide a value

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which is http.

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Um okay.

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And now we can actually check if it's the true.

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Um, because otherwise if we have not proper links we would like to just stop this entire automation.

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Okay.

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To avoid future errors.

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So now you can see we've got, um.

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Yeah.

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It works.

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So it's the true.

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Okay.

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So everything works as we want.

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Let's go over ahead to the next step, which is actually the note for the open AI.

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And here we just want to analyze the image uh, we just received okay.

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So then uh, we want to pick the resource, uh, which is image operation analyze image model.

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Um, you can use GPT four and then um, what's in this image?

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It's totally nice.

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And the URL we can provide this URL.

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So here from the chat.

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Uh, okay.

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Let's test the step.

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So now let's see how it performs.

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It should give us a response okay.

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The image shows a black t shirt featuring a graphic design.

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The word surf is prominently displayed in large letters with multicolored vertical stripes in the background.

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So it's pretty cool actually.

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We used OpenAI to analyze for us an image and we've got a text.

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So exactly what is on the t shirt, how it's written.

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So in smaller letters underneath there are intricate patterns integrated into the design.

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So exact description of course even you can actually you know, you can change the prompt hover for

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now.

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And it's pretty enough even for me.

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Um, so let's go over to.

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So let's go over back to canvas.

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And now there is a time to create the prompt for our, um, yeah, for our future image.

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For this case, I can pick an A agent and they're just, uh, okay, let's click on define below.

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And here in the prompt I would like to, uh, provide a content.

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So um, usually I go over and in the prompt I provide the variables and their in the system message,

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I go over with the instructions.

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And in the resources of this material you will be able to get the instructions for this chatbot or even

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the template in the JSON, so you can upload like the template, um, just import and here get this

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entire automation already set up.

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Also there you will have the instructions.

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Um, so now I can provide a system message here and let's see what we have inside.

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Um let's see.

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All right.

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Um, you're a creative prompt generation assistant specialized in t shirt artworks requirement.

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Your job is to analyze an existing t shirt design user message above and create a new, upgraded version

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that preserves the original layout, overall structure, and a message placement, but enhances its

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visual style, mood, and artistic quality.

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It's super cool actually.

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Think about it for for a second what you do.

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You go over to Google, you type t shirt design and you see your competitors.

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You actually for an example, you know, you go over here, you see, okay, I can do something better,

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I can do it better.

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And then even I have the automation that helps me to generate better designs.

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Um, it's super nice.

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You can create nicely professional print on demand items.

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Um, actually, remember, if you like all of these materials, ideas and so on, uh, please leave

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us an honest review or rating of the course.

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We appreciate it.

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Also here you can type actually, you know, ideas for future automations.

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Uh, because we put a lot of effort into preparing them.

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Um, also, you know, um, it helps us a lot and other students to know if this course is worth to

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enroll or not.

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And here are a lot of advantages if you leave an honest review.

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Thank you so, so much.

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If you have already done it, you help us a lot.

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Thank you so, so much.

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Nevertheless, what I meant is that you can, um, yeah, you can take but, um, let's say designs

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or even worse, and you can create something better.

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Also, you can customize this automation for any purpose you want for stickers for let's say I don't

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know for different circumstances, digital items.

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So the choice is yours.

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Okay.

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So we'll provide this system message.

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And here we can choose the model which is OpenAI.

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Um okay so here we've got GPT four or mini.

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It's cool.

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I can say okay let's go over and run it.

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So we should receive the prompt.

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Nice.

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Create a black t shirt design featuring the word um serve.

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Enlarge dynamic brush script typography with a vibrant gradient or multicolored vertical stripes in

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the background and enhancing the lively beach vibes.

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It's super cool.

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The next step will be actually our HTTP request.

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Even before what I can do, let me go over and pick my sticky notes and provide them here so you see

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what is happening.

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Okay.

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And now, um, okay, let me put it here.

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So we can just organize it.

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For me, it's better.

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And for you, it's just better visible.

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Um, okay, let's put it here.

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I'm sorry.

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I'm just the visual person.

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I need to have everything organized.

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Uh, okay.

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It looks pretty cool.

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Let's create new t shirt design.

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Let's go over with our HTTP request.

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HTTP request.

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And there what we have the method which is post.

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All right.

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We've got the method which is post.

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And now uh what we can do we can go over open AI, um API generate images, generate images.

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Also in the resources of this material we will have the file to download.

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Actually here you will have all of the data.

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However, for now, even if you don't have that or you don't want to download it, you can go over to

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the API documentation and just um, yeah, you've got all of the instructions here.

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All right.

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It's simple as that.

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You can go over, um, to the nar den, click on post and paste the URL authentication.

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You've got predefined credential type and you've got the credential type which is OpenAI.

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Here.

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Let's search for the OpenAI and there provide your OpenAI account okay.

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So you can just connect it by this way or just by other different way okay.

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The choice is yours.

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Uh, you can send the body here.

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Um, and there we've got I'm using JSON and we provide the JSON code in general.

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You can go over there and see what you have.

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It's this.

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So you can go over and pick this entire part.

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Okay.

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Even you will have that in the file.

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So feel free to use it now and delete this part.

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And what should be inside.

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In general we have the model here.

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We have the prompt.

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So there I just see that I forgot to provide the another step before the HTTP request, which is our

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code.

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Okay.

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We would like to make sure this content is not affected by any other, um, elements.

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Okay.

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And now what I can do, I can go over um, actually it should be like this.

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I can go over and take my JavaScript code.

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Um, yeah, from my file.

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So now you can't see that because I'm taking that from other screen.

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However, you will have everything in the resources of this material.

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Also, if you download and import the template, you will have everything, everything set up.

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So feel free to do this.

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And here what it says actually we take the content and we remove some additional different um markdowns.

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Okay.

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So here we just replace some things um, with others.

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Um, we are not covering that in depth because this is not the class about, creating the code.

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It's just about creating automations with the smallest amount of code we can achieve inside.

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So that's why you just simply copy and paste in general, even what you can do.

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You can go over to ChatGPT and ask what this code is doing.

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So it will explain you everything step by step.

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Nevertheless, let's click on the step okay.

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And now um, you will see how it works.

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So our agent is creating that and we've got the response which is cleared for us.

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So we've got create a black T-shirt design.

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And we can use this entire data inside our HTTP request.

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And here in the prompt it's pretty important we use the prompt.

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And then what we do we go over here and we take this variable right there.

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Um, okay.

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Uh I'm sorry.

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Let's go over here and pick it provided there.

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Right.

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Yeah.

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Now it works.

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So now let's see actually what we have.

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We've got the model which is GPT image one.

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We've got the prompt.

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We've got the N which is actually the indicator for the number of images.

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So we have the one and you can change that.

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We've got the size.

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And now actually let's go over to the documentation I would like to pick the vertical size.

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So here let's choose the portrait.

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Actually this is the vertical.

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Um let's paste it here.

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And also we've got the quality.

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So let's search for the quality.

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And there you can choose between high medium low.

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Um for that okay I would like to specify um here the high.

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So what I can do I can go over right there, provide the next line and there like, like type the quotation

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mark quality.

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Um, there what I can do colon provide a colon.

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And here just type high.

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All right.

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It's as simple as that.

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Um, so it's simple.

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data.

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Now, what I can do, I can go over here and test the step.

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So see if everything is set up properly.

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I've got some problems.

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So let's go over here.

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Okay.

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We've got the model GPT image one prompt and we've got the quality.

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Let's see if we have any misspellings.

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Um however we don't have the comma.

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All right.

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We don't have the comma here.

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So every time whenever you have any items, you need to provide the comma.

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Otherwise it's it's treated as the one item.

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And that's why we had an error.

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Probably.

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Let's test a step again.

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We've got some problem.

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Uh, let's see what is wrong right there.

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Uh, we've got send body JSON.

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However, let's maybe expand that and see all of the elements.

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Model GPT image one prompt.

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Okay, okay.

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We don't have the, uh, there the quotation mark, of course.

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Obviously.

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Yeah.

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We don't have the quotation mark.

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And now for sure, it should work.

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Um, yeah.

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So first try.

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Yeah, it works because actually we don't have an error, which is instant.

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Uh.

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Pretty cool.

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Yeah, yeah.

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It's cool.

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Let's wait for some time.

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Um, it takes a several seconds, even sometimes up to 1 or 2 minutes.

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That depends from number of images.

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The size, quality.

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Um, a lot of different, um, yeah, indicators.

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However, the process is not that I can say not that long.

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We can even rename it.

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So generate images.

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Rename.

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So we are waiting to for that to be executed again.

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Let's run it.

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Um, so let's see what's happening.

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Um, let's refresh the page.

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Okay.

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Accidentally.

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I forgot to save the entire workflow.

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So this is the warning for you.

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I had to set again these four notes.

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However, for now it's it's running.

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So let's wait a while and see if this step works.

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And after 30s or so we've got it.

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And there is a time to convert this data to file because we've got our base64 string.

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Okay.

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So now what you do, you take this um variable from HTTP request and you put it here and it should give

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you the file.

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So actually you turn it into the file and there is the moment of truth.

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Let's view it now.

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Wow.

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So so nice.

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Surf California summertime.

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Perfect.

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All right.

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Uh, what do you think about it?

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What do you think about it?

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For me, it's super cool.

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Yeah.

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Um, and the last step will be to save our work, which is the drive.

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Let's pick the drive up, upload, upload file.

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We can upload the file there.

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We've got input data field name, which is the data.

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Um, the file name.

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You can even go over to schema and pick some file name, you know.

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So, um, what we have here, what can we pick?

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Um, even actually, you know, you can leave it.

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So let's name it as the, let's say, test or even you can provide some variables.

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So maybe, I don't know, um, provide this data or even the prompt.

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So maybe let's go over with that.

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Create a black, um t shirt design featuring the large um, yeah.

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Large text.

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Nice.

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We can pick the drive.

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So pick our drive.

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And here pick the folder.

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So t shirt designs.

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Okay.

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T shirt designs.

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Nice.

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It should work.

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Um, I've got this folder right here.

16:29.300 --> 16:31.060
Let's now test the step.

16:31.060 --> 16:31.130
Up.

16:31.850 --> 16:32.210
Up.

16:32.570 --> 16:34.370
So let's test this note.

16:34.850 --> 16:39.730
Actually run it and see if that performs okay.

16:41.170 --> 16:43.690
We should have the t shirt design here.

16:43.970 --> 16:44.850
Nice.

16:44.890 --> 16:45.290
Yeah.

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For sure.

16:46.650 --> 16:49.410
And with all that being said, don't repeat my errors.

16:49.410 --> 16:50.970
So save the workflow.

16:51.890 --> 16:53.250
And now we'll test it out.

16:53.770 --> 16:55.890
So let's open the chat.

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Let's search for some t shirt.

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This one is not I don't like it.

17:00.410 --> 17:01.290
I don't like it.

17:01.290 --> 17:07.170
Let's, um, copy image address and run that inside our workflow.

17:07.210 --> 17:08.450
The moment of truth.

17:09.650 --> 17:13.210
Um, so let's wait, let's wait, let's.

17:13.490 --> 17:16.130
We can see our agent code is works.

17:16.130 --> 17:18.090
Okay, now there is a time.

17:18.250 --> 17:19.410
Um, there is a time.

17:19.450 --> 17:21.770
Um, so 30s or so it will take.

17:22.010 --> 17:23.570
I don't want to make cuts.

17:23.770 --> 17:26.930
Let's search for other t shirts in the meantime.

17:27.490 --> 17:29.090
So, actually, it's pretty nice.

17:29.090 --> 17:34.640
You can take all of the designs and turn them into pretty new mockups and even let me show you.

17:34.720 --> 17:38.120
Maybe like previous mockups I created like this one.

17:38.160 --> 17:40.360
You know, like this one.

17:40.800 --> 17:44.600
Like you have you have, like, endless possibilities even.

17:44.640 --> 17:44.800
Oh.

17:44.840 --> 17:45.120
All right.

17:45.120 --> 17:46.600
This is this is nice case.

17:46.600 --> 17:52.280
Even you can specify if you would like to receive, like the mock up on the t shirt.

17:52.280 --> 17:57.040
So us here on the mock up on the t shirt or just only the image.

17:57.160 --> 17:57.560
Okay.

17:57.600 --> 18:04.400
The image of the graphic, then you can just take it and put on, um, you know, put on the t shirt.

18:04.520 --> 18:05.120
Uh, yeah.

18:05.160 --> 18:08.480
Template mock up and just sell it on print on demand.

18:08.520 --> 18:09.920
You can actually do this.

18:10.040 --> 18:11.480
Um, it's still being generated.

18:11.480 --> 18:14.160
You can do this inside a agent.

18:14.160 --> 18:15.720
So just change the instructions.

18:15.720 --> 18:16.800
It's simple as that.

18:16.840 --> 18:19.960
You can just provide, you know, only provide the image without.

18:20.120 --> 18:20.720
Uh, yeah.

18:21.000 --> 18:22.280
Without the t shirt.

18:22.320 --> 18:22.800
Okay.

18:22.840 --> 18:23.960
Now it's the moment of truth.

18:23.960 --> 18:25.000
Let's see what we have.

18:26.440 --> 18:29.640
Let's wait, let's wait, let's wait, let's wait.

18:29.880 --> 18:31.120
Because it should, it should.

18:31.160 --> 18:34.160
It should appear right here in a moment.

18:34.200 --> 18:35.960
Even we can refresh the page.

18:36.720 --> 18:37.440
Nice.

18:37.480 --> 18:38.400
I can see.

18:39.160 --> 18:39.880
All right.

18:39.920 --> 18:41.800
Design your, um.

18:41.800 --> 18:42.200
Here.

18:42.240 --> 18:43.640
Design as you want.

18:43.680 --> 18:45.760
Pretty cool, isn't it?

18:45.760 --> 18:46.240
For me?

18:46.280 --> 18:47.440
It's super nice.

18:47.480 --> 18:51.000
And again, you can repeat the process for everything you want.

18:51.200 --> 18:53.720
So let's say actually anything you want.

18:53.760 --> 18:59.400
So let's say you've got a stickers I don't know, maybe you have some ideas so feel free to share with

18:59.400 --> 18:59.840
me.

18:59.880 --> 19:04.200
However for t shirts, for maybe cups, um, you've got the max cups.

19:04.240 --> 19:09.240
You know, like for pillows, I don't know, just feel free to experiment with that.

19:09.240 --> 19:09.680
For now.

19:09.680 --> 19:11.080
I can say thank you for watching.

19:11.120 --> 19:14.040
Remember, you've got the instructions in the resources of this material.

19:14.080 --> 19:16.080
You've got the template to download.

19:16.360 --> 19:17.440
Um, yeah.

19:17.480 --> 19:17.920
Leave.

19:18.200 --> 19:20.080
Leave us an honest review rating.

19:20.080 --> 19:21.280
We really appreciate it.

19:21.400 --> 19:22.720
Thank you again for watching.

19:22.920 --> 19:23.840
Um, yeah.

19:24.040 --> 19:27.080
Take care and I will see you in the next material.
