Recently, I came across this YouTube channel that gets millions and millions of views, and one of
their videos made 407 million views.
Really, this is the real number.
And let's watch what we have inside.
So even we don't have any background music like this is the cat trying to trap a mice.
So this is pretty cool.
So I thought I would create an automation that can generate this type of content.
And I came with something like this.
So the simple automation that doesn't contain a lot of steps however it generates for me this type of
videos.
So this is the video I created with this automation.
And the cost of generating this video is approximately $0.50.
And it's really high quality.
We've got the mice, we've got the cat.
And again it's highly professional.
So in this material I will guide you through step by step how to build this entire automation to generate
these videos so you can publish them on any social media you want, let's say TikTok YouTube shorts
and get millions, thousands or even hundreds of views.
So again, this channel gets thousands of views and the most popular videos get millions of views.
If you watched other automations in this course, such as click 2.1 plus Naarden or even Vo three Content
Machine, you can notice that the steps inside these automations and this automation I will show you
how to build in this video are pretty similar.
From this simple fact, we won't build the entire automation.
In this video, I will guide you through the entire process of how to build it.
However, again, if you would like to go and learn how to, for example, connect your Naarden with
Cloudinary open AI.
And here we've got full AI to generate the video.
You can go ahead and watch this material about the click 2.1 plus Naarden or even Vo three content machine
because again, we've got pretty similar steps.
For an example, in the Vo three content machine we've got full AI, and here also we've got the HTTP
request for full AI right there.
Also we've got let me see.
Um, even here we've got the method of how you can publish the content.
So for an example if you wish instead, or even for the further steps, you can provide the data and
then publish the content on TikTok or YouTube shorts.
So again, in this video I will guide you through the entire project.
However, we won't build it because it's kind of wasting our time to repeat setting up the same notes
over and over again and through different automations.
That's why, again, I will guide you through each step and it will be very clear.
So with all that being said, let's dive in.
The first step we've got in this animation is schedule trigger.
So actually I like to use it when it comes to the content generating some articles I don't know, maybe
YouTube videos or even any content.
So to begin with the first step is our trigger.
So here I like to use the specific trigger when it comes to publishing, like creating any content,
you know, maybe some images, videos, posts on LinkedIn and so on.
So I run it like every day or every second day.
So you can choose even like let me show you, you can click on Add Note and add another trigger.
You can just add a other triggers such as trigger manually and let's say on a form.
So it's your choice.
My preference is schedule trigger.
Um, right after our trigger, we've got our a agent that creates for us the prompt.
So let's preview what we have and the prompt we've got create a prompt to use for image generation.
And by the way remember in the resources of this material you've got the JSON file to download for this
entire project with the instructions with the system messages.
With all of the steps set up, you need to only set up your credentials.
Okay.
However, um, let's go back to the point.
So in the prompt we've got create a prompt for um to use for image generation.
And in the system message we've got the purpose capabilities interaction style and example output prompt.
So we exactly specify the theme of the image because later will turn this image into the video.
So the theme of this image is a cat as you can notice like here, every descriptive scenario featuring
a tabby cat sitting and setting a clever trap for a mouse with cheese.
Natural cozy home settings described in the warm, realistic photographic style.
So the point is we are just describing the system message for this specific case.
So these specific videos, because they get millions of views.
However still remember with this automation you can customize the system messages all of the steps for
a specific purpose.
It's not that hard at the end if you have your automation created.
Um, then just setting up your system message like instructions for different purpose is the smallest
problem ever.
Okay, um, because you've got the entire system.
So let's go ahead to ChatGPT and do this stuff.
And for the capabilities design unique image prompt with precise character actions and setting details
include props like kitchen tools or common household items for realism, so I don't want to read it
all.
However, you know this is the entire concept interaction, style, writing clear, rich, descriptive
language.
Avoid headings or instructions in the output, just the image prompt itself and example output.
So we've got our prompt.
And this is pretty everything for this agent.
So again we've got the prompt system message and also the chat model.
Obviously we need to have the chat model to run a agent.
And afterwards we've got the we've got the prompt.
So we've got an output.
Also you can use output parser.
So let's say you specify the name of the variable which is the prompt.
Um and yeah you provide only one um specific variable to return.
However um it's not needed for that case okay.
It's pretty simple straightforward.
So we've got clever.
Tabby cat crouches quietly on a sunlit kitchen floor as green eyes locked on a small mouse near a piece
of golden cheese perched on a wire mesh trap.
Perfect.
So this is our, um, create prompt, um, part of this automation.
Next, what we do, we generate image.
And we've done it many times in the course.
Really many times in the, in the course um, by using open AI image model.
And why?
Because it's the best for now for generating images.
Okay.
So what do we do?
We provide an URL.
Um, and again we set it up many times and other automations in this course?
Um, so yeah.
So we've got our URL where we specify we want to generate image here authentication I use predefined
credential type OpenAI OpenAI account and send body JSON body.
So inside what we have we've got the model.
We've got the prompt quality and size.
So for this type of the video we want to specify the size which is vertical.
That's why we've got the size.
Um okay.
This is the step.
We run it.
We get the b64 file.
And then in some shape of form we need to convert it to base64, um, to the file.
I'm sorry.
So we use convert to file.
And inside we just provide this specific variable.
So we just drag and drop it here.
And afterwards we've got the file which is called data.
Um and we can view it what we have we've got a mice perfect and a cat.
That's cool.
So we'll be animating that turning that from image to video with really nice model which is minimax.
But uh, for now, um, in some way.
We need to take this file and upload it to the hosting platform.
Okay.
Because afterwards we want to just put it into into our model of the full AI, which is minimax.
So we use Cloudinary.
Um, also we've covered that in the course I think um, a few times.
So this is the platform that allows us to do this stuff.
So here inside you need to provide there in this link you need to provide your cloud name.
Um, so pay in mind if you copy my, um, JSON template just inside here, provide your cloud name.
Um, I showed it many times in this course how to do this.
So you can refer to, for example, these videos if you wish.
Um, so you provide your cloud name and in the send body you provide form data parameter type which
is an a then binary file name which is file and and field name which is data.
Because obviously here we've got a data for the parameter type.
We've got the form data upload preset.
And here it's important you need to provide your preset name.
That's perfect.
And just go over to Cloudinary.
And here you will have your preset name.
Uh, maybe let me very shortly show you how it works.
Cloudinary.
So it will take only a few seconds.
Um, let me sign in.
So when it comes to the cloud name, you can copy that from home.
Um, right here at the top.
And you need to provide it in the URL.
And for the preset, you need to click on the settings and then on upload and here at your preset.
So in general you need to copy the name of it and provide it.
Uh right here.
Perfect.
The next step what we have.
So we've got two parts create prompt generate image.
The next step what we do, we actually turn the image into the video.
And here we've got a specific link which is specified for this model.
So minimax Halo zero two Pro image to video.
And here there is something important because let me show you.
We go over to fly and we've got our model which is this one.
So the cost of generating it.
It's approximately $0.50, as you can notice for the six seconds.
Video.
However, if you want to use something cheaper, you've got the model which is image to video standard.
Um, so here it's cheaper.
Also, if you go ahead to API, you pick the table of the content, which is http URL.
Then you go ahead here and you've got the URL you can use for this specific model.
So only probably you need to change from pro to standard.
Let me see.
Um let's see.
Yeah.
You need to change here to standard.
And then you're using standard version.
And the advantage of it.
Um, we go over here.
The advantage of it is that we are we are paying only, um, twice as less, I can say.
So.
$0.27 for six seconds.
Video.
Um, of course, the quality will be just worse.
However, it's not bad, as you can see right there.
Okay.
So we can just use it.
This is the disclaimer if you want to just save money on this automation okay.
So in the URL we've got it.
We've got our model which is generic type header authentication full.
I um so I connected it by providing authorization here, probably the key and the API key as I remember.
Well um, you've got also that in other videos you can go over here and see how you can connect, um,
your full I with an ID, um, and the JSON.
Then what we do, we send the body, we've got the JSON using JSON.
And here we've got our JSON code.
So we provide a URL, JSON URL and aspect ratio which is nine by 16 and a prompt.
So in the prompt we've got a static camera.
We don't have the prompt for for this specific circumstance.
Um, because we've, we had the prompt for only the image.
So we just specify okay, make the camera static.
Because in these videos, uh, you know, like everything is static, cat is not doing like it's not
performing a lot of activities, um, and so on.
And the camera is static.
It's not.
It's not moving.
Perfect.
So it's pretty simple.
Then what we do.
We wait ten minutes.
Because mostly these videos take ten minutes to create.
If I go here to Pro model to requests here, the video took, um, 500 seconds.
Almost.
Um, and there 503 seconds.
Okay.
So we just wait ten minutes.
Um, then what we do, we get the video and we provide the specific URL.
So what we specify, we want to connect with minimax requests.
So this specific tab um this one.
And here we just provide, uh, the request ID the request ID um let me show you this is this ID.
So we just specify we want to take this ID and this is the variable.
So every time it changes and we check the status.
Okay.
So it's pretty simple.
And for that case we only provide our credentials methodget.
So it's very important.
And get video.
You've got the method get and post actually an image to video you've got post.
Similarly with creating image, you've got the post here.
Um, yeah, we don't have the get.
Um, but again we've got method get URL credential and that's pretty everything.
And at the end we've got our Google Sheets where we save the data.
So I provided image prompt here, image URL and video URL.
Also you can find it in the resources of this material.
So the specific Google Sheets I need to say it's pretty straightforward.
So we've got only three columns.
The first one is image prompt image url video URL.
So we just just save our data for further tracking.
Um, to just have the access to all of the videos, images and the prompts.
And for this case, this is everything.
I think these videos are highly professional.
We can generate really nice videos with this specific automation.
It's not that hard, as you may notice.
Actually, we've created many much complicated automations in this course.
I mean, much more so in general yeah this is pretty straightforward automation.
And we've got a lot of HTTP requests.
However from this course for sure you know how to use them properly.
Without a doubt.
We've got one agent scheduled trigger weight node convert to file save information to Google Sheets.
So yeah by this way we generated the system that produces for you this type of the videos.
And also remember if you wish you can go over for example to this video and check how you can, um,
actually publish this specific video that we generate with this automation to our social media.
So for an example, TikTok YouTube shorts here, Facebook, LinkedIn.
For that we are using potato.
So yeah you can you can just use this application.
It's the most it's the best application so far for publishing the content from Nadine for me on social
media.
So yeah, I explained the entire process here in this video probably or even in other video.
And for now I can say thank you for watching.
I hope you enjoyed it and I will see you in the next material.