WEBVTT

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Recently, I came across this YouTube channel that gets millions and millions of views, and one of

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their videos made 407 million views.

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Really, this is the real number.

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And let's watch what we have inside.

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So even we don't have any background music like this is the cat trying to trap a mice.

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So this is pretty cool.

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So I thought I would create an automation that can generate this type of content.

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And I came with something like this.

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So the simple automation that doesn't contain a lot of steps however it generates for me this type of

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videos.

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So this is the video I created with this automation.

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And the cost of generating this video is approximately $0.50.

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And it's really high quality.

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We've got the mice, we've got the cat.

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And again it's highly professional.

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So in this material I will guide you through step by step how to build this entire automation to generate

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these videos so you can publish them on any social media you want, let's say TikTok YouTube shorts

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and get millions, thousands or even hundreds of views.

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So again, this channel gets thousands of views and the most popular videos get millions of views.

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If you watched other automations in this course, such as click 2.1 plus Naarden or even Vo three Content

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Machine, you can notice that the steps inside these automations and this automation I will show you

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how to build in this video are pretty similar.

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From this simple fact, we won't build the entire automation.

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In this video, I will guide you through the entire process of how to build it.

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However, again, if you would like to go and learn how to, for example, connect your Naarden with

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Cloudinary open AI.

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And here we've got full AI to generate the video.

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You can go ahead and watch this material about the click 2.1 plus Naarden or even Vo three content machine

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because again, we've got pretty similar steps.

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For an example, in the Vo three content machine we've got full AI, and here also we've got the HTTP

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request for full AI right there.

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Also we've got let me see.

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Um, even here we've got the method of how you can publish the content.

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So for an example if you wish instead, or even for the further steps, you can provide the data and

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then publish the content on TikTok or YouTube shorts.

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So again, in this video I will guide you through the entire project.

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However, we won't build it because it's kind of wasting our time to repeat setting up the same notes

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over and over again and through different automations.

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That's why, again, I will guide you through each step and it will be very clear.

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So with all that being said, let's dive in.

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The first step we've got in this animation is schedule trigger.

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So actually I like to use it when it comes to the content generating some articles I don't know, maybe

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YouTube videos or even any content.

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So to begin with the first step is our trigger.

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So here I like to use the specific trigger when it comes to publishing, like creating any content,

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you know, maybe some images, videos, posts on LinkedIn and so on.

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So I run it like every day or every second day.

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So you can choose even like let me show you, you can click on Add Note and add another trigger.

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You can just add a other triggers such as trigger manually and let's say on a form.

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So it's your choice.

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My preference is schedule trigger.

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Um, right after our trigger, we've got our a agent that creates for us the prompt.

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So let's preview what we have and the prompt we've got create a prompt to use for image generation.

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And by the way remember in the resources of this material you've got the JSON file to download for this

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entire project with the instructions with the system messages.

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With all of the steps set up, you need to only set up your credentials.

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Okay.

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However, um, let's go back to the point.

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So in the prompt we've got create a prompt for um to use for image generation.

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And in the system message we've got the purpose capabilities interaction style and example output prompt.

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So we exactly specify the theme of the image because later will turn this image into the video.

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So the theme of this image is a cat as you can notice like here, every descriptive scenario featuring

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a tabby cat sitting and setting a clever trap for a mouse with cheese.

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Natural cozy home settings described in the warm, realistic photographic style.

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So the point is we are just describing the system message for this specific case.

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So these specific videos, because they get millions of views.

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However still remember with this automation you can customize the system messages all of the steps for

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a specific purpose.

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It's not that hard at the end if you have your automation created.

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Um, then just setting up your system message like instructions for different purpose is the smallest

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problem ever.

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Okay, um, because you've got the entire system.

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So let's go ahead to ChatGPT and do this stuff.

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And for the capabilities design unique image prompt with precise character actions and setting details

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include props like kitchen tools or common household items for realism, so I don't want to read it

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all.

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However, you know this is the entire concept interaction, style, writing clear, rich, descriptive

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language.

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Avoid headings or instructions in the output, just the image prompt itself and example output.

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So we've got our prompt.

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And this is pretty everything for this agent.

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So again we've got the prompt system message and also the chat model.

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Obviously we need to have the chat model to run a agent.

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And afterwards we've got the we've got the prompt.

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So we've got an output.

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Also you can use output parser.

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So let's say you specify the name of the variable which is the prompt.

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Um and yeah you provide only one um specific variable to return.

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However um it's not needed for that case okay.

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It's pretty simple straightforward.

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So we've got clever.

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Tabby cat crouches quietly on a sunlit kitchen floor as green eyes locked on a small mouse near a piece

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of golden cheese perched on a wire mesh trap.

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Perfect.

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So this is our, um, create prompt, um, part of this automation.

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Next, what we do, we generate image.

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And we've done it many times in the course.

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Really many times in the, in the course um, by using open AI image model.

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And why?

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Because it's the best for now for generating images.

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Okay.

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So what do we do?

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We provide an URL.

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Um, and again we set it up many times and other automations in this course?

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Um, so yeah.

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So we've got our URL where we specify we want to generate image here authentication I use predefined

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credential type OpenAI OpenAI account and send body JSON body.

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So inside what we have we've got the model.

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We've got the prompt quality and size.

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So for this type of the video we want to specify the size which is vertical.

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That's why we've got the size.

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Um okay.

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This is the step.

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We run it.

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We get the b64 file.

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And then in some shape of form we need to convert it to base64, um, to the file.

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I'm sorry.

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So we use convert to file.

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And inside we just provide this specific variable.

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So we just drag and drop it here.

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And afterwards we've got the file which is called data.

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Um and we can view it what we have we've got a mice perfect and a cat.

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That's cool.

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So we'll be animating that turning that from image to video with really nice model which is minimax.

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But uh, for now, um, in some way.

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We need to take this file and upload it to the hosting platform.

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Okay.

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Because afterwards we want to just put it into into our model of the full AI, which is minimax.

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So we use Cloudinary.

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Um, also we've covered that in the course I think um, a few times.

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So this is the platform that allows us to do this stuff.

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So here inside you need to provide there in this link you need to provide your cloud name.

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Um, so pay in mind if you copy my, um, JSON template just inside here, provide your cloud name.

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Um, I showed it many times in this course how to do this.

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So you can refer to, for example, these videos if you wish.

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Um, so you provide your cloud name and in the send body you provide form data parameter type which

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is an a then binary file name which is file and and field name which is data.

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Because obviously here we've got a data for the parameter type.

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We've got the form data upload preset.

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And here it's important you need to provide your preset name.

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That's perfect.

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And just go over to Cloudinary.

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And here you will have your preset name.

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Uh, maybe let me very shortly show you how it works.

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Cloudinary.

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So it will take only a few seconds.

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Um, let me sign in.

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So when it comes to the cloud name, you can copy that from home.

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Um, right here at the top.

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And you need to provide it in the URL.

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And for the preset, you need to click on the settings and then on upload and here at your preset.

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So in general you need to copy the name of it and provide it.

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Uh right here.

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Perfect.

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The next step what we have.

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So we've got two parts create prompt generate image.

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The next step what we do, we actually turn the image into the video.

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And here we've got a specific link which is specified for this model.

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So minimax Halo zero two Pro image to video.

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And here there is something important because let me show you.

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We go over to fly and we've got our model which is this one.

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So the cost of generating it.

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It's approximately $0.50, as you can notice for the six seconds.

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Video.

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However, if you want to use something cheaper, you've got the model which is image to video standard.

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Um, so here it's cheaper.

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Also, if you go ahead to API, you pick the table of the content, which is http URL.

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Then you go ahead here and you've got the URL you can use for this specific model.

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So only probably you need to change from pro to standard.

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Let me see.

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Um let's see.

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Yeah.

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You need to change here to standard.

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And then you're using standard version.

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And the advantage of it.

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Um, we go over here.

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The advantage of it is that we are we are paying only, um, twice as less, I can say.

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So.

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$0.27 for six seconds.

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Video.

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Um, of course, the quality will be just worse.

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However, it's not bad, as you can see right there.

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Okay.

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So we can just use it.

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This is the disclaimer if you want to just save money on this automation okay.

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So in the URL we've got it.

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We've got our model which is generic type header authentication full.

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I um so I connected it by providing authorization here, probably the key and the API key as I remember.

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Well um, you've got also that in other videos you can go over here and see how you can connect, um,

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your full I with an ID, um, and the JSON.

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Then what we do, we send the body, we've got the JSON using JSON.

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And here we've got our JSON code.

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So we provide a URL, JSON URL and aspect ratio which is nine by 16 and a prompt.

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So in the prompt we've got a static camera.

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We don't have the prompt for for this specific circumstance.

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Um, because we've, we had the prompt for only the image.

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So we just specify okay, make the camera static.

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Because in these videos, uh, you know, like everything is static, cat is not doing like it's not

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performing a lot of activities, um, and so on.

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And the camera is static.

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It's not.

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It's not moving.

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Perfect.

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So it's pretty simple.

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Then what we do.

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We wait ten minutes.

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Because mostly these videos take ten minutes to create.

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If I go here to Pro model to requests here, the video took, um, 500 seconds.

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Almost.

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Um, and there 503 seconds.

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Okay.

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So we just wait ten minutes.

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Um, then what we do, we get the video and we provide the specific URL.

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So what we specify, we want to connect with minimax requests.

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So this specific tab um this one.

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And here we just provide, uh, the request ID the request ID um let me show you this is this ID.

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So we just specify we want to take this ID and this is the variable.

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So every time it changes and we check the status.

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Okay.

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So it's pretty simple.

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And for that case we only provide our credentials methodget.

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So it's very important.

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And get video.

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You've got the method get and post actually an image to video you've got post.

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Similarly with creating image, you've got the post here.

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Um, yeah, we don't have the get.

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Um, but again we've got method get URL credential and that's pretty everything.

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And at the end we've got our Google Sheets where we save the data.

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So I provided image prompt here, image URL and video URL.

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Also you can find it in the resources of this material.

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So the specific Google Sheets I need to say it's pretty straightforward.

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So we've got only three columns.

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The first one is image prompt image url video URL.

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So we just just save our data for further tracking.

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Um, to just have the access to all of the videos, images and the prompts.

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And for this case, this is everything.

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I think these videos are highly professional.

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We can generate really nice videos with this specific automation.

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It's not that hard, as you may notice.

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Actually, we've created many much complicated automations in this course.

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I mean, much more so in general yeah this is pretty straightforward automation.

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And we've got a lot of HTTP requests.

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However from this course for sure you know how to use them properly.

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Without a doubt.

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We've got one agent scheduled trigger weight node convert to file save information to Google Sheets.

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So yeah by this way we generated the system that produces for you this type of the videos.

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And also remember if you wish you can go over for example to this video and check how you can, um,

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actually publish this specific video that we generate with this automation to our social media.

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So for an example, TikTok YouTube shorts here, Facebook, LinkedIn.

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For that we are using potato.

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So yeah you can you can just use this application.

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It's the most it's the best application so far for publishing the content from Nadine for me on social

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media.

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So yeah, I explained the entire process here in this video probably or even in other video.

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And for now I can say thank you for watching.

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I hope you enjoyed it and I will see you in the next material.
