Now in this lesson of the course, I will show you how I built this agent system to produce for me viral
social media posts.
And the fact is, I'm using inside perplexity to make the research for me.
Because if you don't know, actually, for a day of recording this video, perplexity note integration
was released only a few days ago inside an addon, and it allows our agents to be ten times better when
it comes to the research.
And this type of content.
Make thousands of likes with millions of views and in general.
In this video I will show you step by step how to build this automation that produces for you.
This entire content also publishes it on other social media.
Actually, a lot of social media such as Instagram, TikTok, Facebook, LinkedIn, Pinterest, or even
we can publish it on YouTube and more.
And for now, even before we build it step by step, let me guide you through what it does.
So firstly, we've got our agent that creates an idea for our content.
It produces a title tidal description hashtags.
And then we will use this idea.
So as you can see right now perplexity is making the research.
And so we'll be using this content for further steps.
After it's done.
It saves the data inside Google Sheets for tracking.
Then it gives the data for the graphic idea, a agent that produces for us the prompt to generate an
image.
So here we've got the prompt.
And then this prompt is sent over to HTTP request.
So here we are using GPT image one model to generate for us infographic.
Then it's converted to the file.
We get an image URL by using Cloudinary and we set up our credentials kind of credentials.
So IDs for our social media we upload an image to the blog.
So the content to straightforward publish that on TikTok, Instagram, Facebook, LinkedIn and Pinterest.
And the process is pretty straightforward because after we generate our image now look it's within just
seconds.
So it's being published on Instagram, TikTok, Facebook, LinkedIn and Pinterest within seconds.
Again, and at the end, our data is saved inside Google Sheets and just look simply what content we
received.
So we've got a description for the post.
We have our image and everything again is published, you know, every day by our automation and on
our five social media platforms without us doing anything afterwards after we set up this entire project.
So this is actually the indicator to watch this video to the end.
It's so powerful.
You can automate a lot of different things with this automation.
And so with all that being said, let's build it from scratch from start to finish.
Basically, this video will be quite long, however, you know, after you set it up once.
So this entire project, it works for you whenever you sleep, it posts every day and create valuable
content.
But let's start with our trigger, which is our schedule.
Note so we say we would like to trigger this automation at midnight every day.
Of course you can change the trigger interval, for example, to hours, weeks, days.
So you know you can trigger between two days or so.
Then right away we go ahead to our next step, which is our agent.
And it's to create for us an idea so I can rename it, create an idea, a agent.
Um, by this agent, we want to get the title, description and hashtags for the content.
Right.
Um, so yeah, we can just define below and we'll be using the prompt, um, system message and also
for different, um, actually extensions for this agent.
So I can say this is the most comprehensive step inside this automation because we'll be using a lot
of again extensions.
But um, I gathered every information for you inside the file.
You can download in the resources of this material.
So first we've got a prompt.
So research the most recent and interesting news about artificial intelligence and automation.
Create content for me based on the latest developments in these areas.
And there is a very important fact you can modify this system to generate for you any type of the content
you wish.
Let's say you want to have that for the healthcare tech.
I don't know, maybe for sports cars.
Okay, news for the sports cars or any sports kind of, you know, so in general what you do, you can
actually go ahead to ChatGPT and you can type, all right.
And take this entire piece of the text and transform that to let's say healthcare industry.
All right.
For the specific case again I'm the same thing you can do with system message.
So just copy it because it's structured for AI and automations as you can see.
But it's simple.
It's simple as that.
To go ahead ChatGPT and tell okay just customize it for me for healthcare.
So for example let me show you.
So I typed customize for me these instructions for the recent news from football I provided my system
message and then you can see we've got a system message here, an expert content creator for short form
posts about recent football, football, football news.
And then we've got football news and instead of a agents automations.
So you do it by this way.
And this automation I can say is really versatile.
Okay.
You can just, you know, create different contents.
Even you can have these multiple automations for different type of the content.
Again.
So also in the resources of this material, you can download the entire template for automation.
And when you do this you just click on these three dots and you click on import from file.
So let's just pick perplexity posting machine.
And then you just have this entire project, you know, setup inside an addon.
However, let's now move on to setting it up, setting it up step by step.
So what we have inside again we need to provide the prompt.
Um, yeah.
We can provide a prompt.
And this is the message which is really white.
I spend a lot of time on setting it up.
All right.
So let me actually show you we can choose the expression.
And inside we have we have the system message.
So we are an expert content creator for short form posts about AI and automations.
We have the purpose.
It's pretty obvious you can just read it and for which purpose it is.
So it's designed for platforms like TikTok, Instagram Reels, YouTube shorts, you know, um, there
we would like to create interesting, surprising or viral worthy insights.
So again, we are using perplexity in that case.
And in summation, to make the interior research, we connect it with ChatGPT model.
So together they are so powerful.
You know, like we've got the best.
Just imagine we've got the best model to make a research on the internet.
And then we allow this entire tool to talk with ChatGPT and work together like it can't be weak or I
don't know, it can be bad.
Um, and you will see everything in this video.
We have the content type, we've got the output format.
So as I said, we would like to get the title, description and hashtags.
How to use the think tool.
We specify the time because in the agent like remember it doesn't know which time it is for now, but
by providing this variable.
So we've got two curly brackets and then dollar sign and yeah the comment now we give it the time.
So here you can you can see the time.
We've got 2025 June 14th.
Um yeah.
So it's perfect.
Um, for the JSON output format.
Uh, we want to also use it for the structured output parser.
So we want to get title description hashtags.
We've got also formatting rules.
But for now you can just stop the video or even go over here to the document and just read it.
So let's move on.
And for this case we'll have um our chat model which is OpenAI.
Inside I like to use GPT four or mini.
It's pretty efficient.
Okay, then for the tools, we want to use either our think node.
So we've got think tool.
We'll customize it later.
And perplexity.
It's pretty important if you are using right now your nar den and you can't see perplexity you need
to update your cloud.
Okay?
So make sure you have the latest update and then update.
Um, and also additionally we want to get um structured and specific output format.
So structured output parser.
So let's organize it very quickly.
We've got structured output parser.
And now let's set everything up.
So firstly let's start with the think node.
And we want to use think node to actually you know refine the responses from perplexity and open AI.
Um so make sure we have the content which is relevant.
Um so just automate I can say automate um, the working process between these two nodes.
And let me show you what I have for you, because I provided this description for the think node.
Let's just paste it here and I will explain you how it works.
So we've got your filtering and reasoning and reasoning assistant and review the information gathered
below.
Your job is to confirm the news is from the last three days.
So today is we provide a date, make sure it is related to a tools agents or automations and and in
general again you can customize it for your specific content.
So again go ahead to ChatGPT and type right.
It's for the football.
Or I can do like the following stuff.
I can just copy it.
And now just type now for it okay I can just type now for it.
And it will customize this data for the football as you can see like here UN news and confirm.
All right.
Yeah but I can type for football.
Football?
Um, yeah, I can just do this and then I will get the content for the football.
So football matches, transfers, injuries, controversies, records or viral moments.
Um, so again, you can do this.
And what we have inside, um, make sure it's related to a tools agents or automations.
Reject anything older or unrelated to a system updates or automation breakthroughs.
And if the news meets all criteria, summarize the key insights or topic in 1 or 2 sentences for content
creation.
Um, so again, we kind of this is kind of the guard for this automation to make sure everything is
correct.
Um, it's cool because actually again with this agent we are using four different nodes for the structured
output parser.
We'll be using just a simple, um, text.
So here we want to get the title description and hashtags.
So this is simple JSON code.
Okay.
And for the perplexity, maybe let's change the order for the perplexity.
Um, now what we do, we actually in the text we use this option.
So we let I to define this parameter.
So it takes the information from our agent.
All right.
What we create.
So it uses I again.
But now we need to create our credential with perplexity.
So how you do this you create on you click on the create new credential.
And then you need to provide your API key for this case.
Go ahead to perplexity API.
You can click here on API settings or even perplexity.
Let's click on perplexity.
And then in the account and all settings you can find your API keys right there.
Also you need to provide your credits.
So I provided some dollars but it's pretty cheap.
Um so yeah you can do this.
Um go ahead to API keys, create new key and just take it and provide in your API key bracket.
Click on save and it's done.
Then what you can do, you can choose the model.
So for this case I like to use Sonar or Sonar Pro so we can use sonar.
Um so it's pretty it's pretty pretty.
Everything all right.
So we are using perplexity, um, to make the research for us.
Um, so now what we can do, we, we can execute the workflow and see if that works.
So now we can see our AI agent, um, connected to ChatGPT.
Then it went to perplexity.
Now, um, it used think tool even to do the entire stuff.
And at the end we've got the content.
So, you know, like we've got here, let me show you and tidal, OpenAI or Free Pro Meta's major arm
moves big news in the AI world.
OpenAI just rolled out its new model.
003 Pro.
That's perfect.
Even when you click on logs here and you can see the entire process.
So what I've done.
Firstly it came to ChatGPT.
It gave the input.
So yeah ChatGPT created for us some data.
Then it went to perplexity and asked to research the latest news and developments related to artificial
intelligence and automation.
So again, like the combination of ChatGPT and perplexity is so powerful.
We used ChatGPT, then perplexity.
Then with the data from perplexity, we used again ChatGPT then we refined our knowledge, and with
the think tool again, actually twice here.
And at the end, um, after checking all of the data, we went through OpenAI chat model to give us
the response.
All right.
And also we've got the structured output format.
So we've got this entire data again title description hashtags.
That's truly amazing.
After this agent that is pretty complex.
I need to say, um, we go, we move on to Google Sheets.
We want to save the data.
So there we just pick up and row in sheet.
Um, we pick our document, which is, for our case, Daily News.
Um, let me show you because you can also, um, you know, like, copy it from the resources of this
material.
So just click on the link, then click on the file, make a copy and you can use it.
However inside we've got title description hashtags status.
So in progress or done image URL.
Um additionally for this entire project will be generating an image remember.
So after the entire process is finished.
Also we want to store image URL to have the access.
All right.
So inside Google Sheet we just store the data and we make sure our content is published because it's
done every day.
Um so we pick our Google Sheets.
And then we pick sheet one and we just map our specific fields for the title.
We provide a title for the description.
We provide the description for the hashtags, we provide the hashtags and for the status we type in
progress.
We execute the step.
So now I'm actually going to wait.
All right.
And status and progress.
Description title.
Hashtags.
Everything is correct.
Um okay.
After our Google Sheets, we provide another agent.
So we pick a agent right here.
Okay.
And then, uh, we click define below.
Um, in the prompts we move on to our file.
Um, so I provided everything here for you.
You know, instead of just typing, um, that from scratch, just you can just copy it.
Also, we don't waste a lot of time in this video to create the prompt system message.
Like, it takes a lot of time.
Like trust me, creating this system message took me, I don't know, maybe one hour or so because I
had like a lot of different errors and different problems.
So yeah, like it's it's ready for you to use.
You don't need to do anything.
Just, just just copy and paste it.
I hope you actually also appreciate it.
But what we can do for now, we can copy this prompt.
Um, so we can provide a prompt.
And there the system message.
So just select all by clicking Ctrl A and Ctrl C to copy.
Also also here you can copy the content paste there and simply um let's quickly preview what we have.
Again a system message.
You're a visual prompt engineer.
Um, so this agent creates for us the prompt.
Um, it's pretty important.
And we've got the prompt requirements.
So like, yeah, all of the requirements for the model and example output.
And it's pretty straightforward.
For this case, we are using, um, open AI model.
So for all mini um, let's scroll down for mini.
So it should create for us the content.
That's pretty everything.
We don't have any additional nodes extensions such as think tool.
And so uh, but we've got the prompt, a vibrant, a dynamic scene depicting two key elements of AI
advancement.
On one side, the OpenAI O3 uh Pro model represented a sleek, glowing digital assistant, engaging
with users through interactive holographic displays.
Uh, pretty complex prompt.
Um, it's due to our actually, it's due to our system message.
So again, we want to have really a professional prompt to use and to create our image.
Um, and for now I can say and create prompts.
Uh, part is ready for for us is already created also from my ready automation.
Um, let me take sticky notes.
So we see what happened, what is happening?
So for now, we create that, um, yeah.
We created the part to create the prompts and then, uh, we move on to generate image.
Actually not images, but image.
Let me change it.
So we've got image.
And the first thing we want to take our HTTP request.
So inside we'll be creating uh yeah.
We'll be just creating our image uh with GPT image one uh model.
So we've got the method which is post inside, um, our document, we've got the URL.
And in this course I can say many times we used this HTTP request to generate our images.
So for now I won't go more in depth.
Um, let's just, uh, copy and paste the information.
So we've got, um, yeah.
Um, authorization, predefined credential type.
We've got the generic, um, here what we have actually let's see, um, inside we've got open I.
So we just pick open I and there just connect your OpenAI account.
As simple as that.
For the next content we need to enable the body.
And in the body we need to provide the JSON code.
So let's send the body up using JSON.
And inside the JSON just provide a code and it simply indicates let me show you.
It simply indicates that we want to use the model which is GPT image one, the prompt to generate high
quality image with this prompt.
And there we provide the output from our agent to generate for us, um, the prompt and this is the
this is the value.
So we indicate we want to get only one image this size.
Uh, 1024 by 1024 output format.
This is JPEG.
Uh, yeah.
So we are just using it and afterwards we just create our image, we click on Execute step and we need
to wait approximately 30s.
When the process is done, we are ready to move forward.
We received the B64 JSON format.
So then what we want to do?
We want to format it, actually turn it into the file.
We are using the node which is convert um to file and then move base64 string to file.
Um it's pretty straightforward.
We just put base64 JSON.
So this entire code we just click on execute step and then we have our image.
Let's view it.
Um that's perfect okay.
We've got some problems.
But you know um it happens.
So here it cutted the text.
Yeah.
But still it's highly professional even.
Remember we can regenerate the image for now.
So let's do it very fast.
After it's done we have our b64 JSON format and we need to turn it into the file.
For this case we'll be using the node which is converts convert to file and then move base64 string
to file and just simply provide this variable inside the input field and click on execute step.
And then we can just preview the file.
So view here and it's perfect.
So even like look so far what what we've done we used our agent to create for us an idea.
So here title description hashtags.
We used perplexity to make the best research possible.
Think tool to just guard everything and check if everything is at the point.
Also open AI.
So this is really powerful agent.
Then we save the data.
Then we used a agent to create the prompt for an image.
We generated an image and we've cut an image.
So the entire content.
That's pretty amazing.
But for now let's move forward.
So we need to get image URL.
For this case we'll be using again HTTP request will be connecting with the Cloud Deanery, which is
an application that allows us to do this stuff.
So when you go to our file and you can see we've got the method which is post URL, um, and different
parameters.
So let me guide you through step by step how to do this.
Um so in general in the URL you provide this URL change the method to post.
However, in the URL um, just notice you've got your cloud name.
This is the great moment to move on to Cloudinary.
So type Cloudinary that API, just click on upload API reference.
Um, just sign up for free and the right top corner, just click on sign up with Google.
After you do it, click on home in the left top corner and just take your cloud name.
Just copy it and provide insight inside this part so your cloud name, just paste it here.
Perfect.
Next we need to send the body.
And inside the body.
In the body content type, we need to pick form data.
We'll be providing two parameters.
So the parameter one which is the file and parameter two.
Uh we want to upload the preset.
So our preset from Cloudinary I will show you everything step by step.
Um, firstly um let's provide the form data for the parameter first.
Like the first parameter we want to pick an a then binary file name.
Um, this is the file.
And for the input data field name we just provide the file name.
For this case it's the data as you can notice here.
So we just type data for the next parameter.
Uh we provide a form data.
And then um let's go over here.
We provide the exact name which is this one.
So upload preset.
Um and for this case we need to provide our preset name, but before we need to create it, let's go
ahead to um Cloudinary click in the left bottom corner, um, on settings and in the upload field,
actually in the in the upload tab click on Add Upload preset.
Also in the Cloudinary you've got the free trial.
Actually, you know like free subscription, you can you can do a lot off of it.
So even I have the free subscription for my other automations.
So there I've got a lot of capacity, but let's move on and provide the preset name.
Let's name it as an Aiden test.
Click on unassigned and click on save in the right top corner right here.
Then what you want to do.
You want to pick the name.
So and then test and paste it here.
So let's execute this step for now.
So we can notice everything is perfect even Let's rename it as get get image URL.
Perfect.
Nice.
Also other steps.
And this is create an idea a agent.
And this is graphic idea agent.
Let's click on rename graphic.
Um graphic idea.
Idea I agents.
Nice.
Um and there is the point.
So we have we've created the prompts and we generated our image.
Um, and also we got an URL.
However, for now there is the fact we need to kind of have some external tool to publish on different
social media, actually to publish our post.
So combine everything together and publish it on our social media.
For this specific case, I'm using the Dado, which is amazing platform that allows us to do this stuff.
So when I go ahead to blow the dough, you've got your free trial.
So in general, when you sign up, you've got seven day free trial, so you can use it totally for free.
And this is an amazing platform that lets you, um, yeah, just take your content and publish on multiple
social media.
And overall, I will put the link in the resources of this material.
So actually feel free.
Um, yeah.
To open, um, this blue data platform via my link.
By this way, you help me.
Thank you so much.
Nevertheless, for now, let's continue and we can click on Start Free Trial.
So simply I can just log into my account.
You need to do this.
And then let me show you.
When you click on the settings you can actually log in and upload to different platforms.
So it can be Twitter, LinkedIn, Facebook, TikTok, Instagram threads, Pinterest, or even YouTube.
As you can see there, I've got my accounts that I will be using for this specific case for this video.
Um, so yeah, you just go over here and you click on login for an example with Google.
All right.
You just click here.
You log in with Google and then after you do this not not Google however Facebook.
Um, nevertheless after you do this, um, you can copy your account ID that will be using in the next
step for this automation because we'll be choosing edit um fields.
So we'll set up the specific value.
We'll be using JSON.
And then inside our document um you've got the JSON format.
So simply what you want to do, you just take it um you just take paste it here and then inside for
an example Facebook, you go ahead to potato, you copy account ID and you paste it here.
Okay.
You just remove it.
You paste for the Facebook page ID um, we need to take it from Facebook.
So just move on to your Facebook page account, click on Account Settings privacy and then settings.
Um, move on to page details right here and then click on Page Transparency.
So from there you can just take your page ID, copy it.
Um just paste here.
Um, do it by this way and for other things.
So Instagram I can go ahead to blog I can log in with Instagram, I can copy account ID, paste it here
for um, there for the Pinterest again.
Again, the same stuff, um, like this platform.
So it allows you, um, to publish the content.
Also make it really easy to do because remember, also there is a fact, um, when it comes to publishing
the content on TikTok, even Instagram, Facebook, these platforms are really sensitive when it comes
to actually uploading the content from which sources, from which platforms.
And I can say not a lot of platforms have the access to do this.
However, potato can do this.
So it's directly connecting to these platforms and it's posting the content for us.
It's a really great platform because actually you need to remember we'll be able to publish the content
to approximately ten different platforms.
It's huge.
One type of the content to different platforms, ten of them.
It's a big amount.
And for me, it's really I think even this plan is really affordable.
So after the free trial, you pay $29 for the month.
However, again, you may have um, yeah, a lot of different automations and you can use it.
But let's move on to our Nadine.
So we have our edit fields.
Um, yeah.
We've we've got our edit fields node.
We can execute the step and we will get variable for each specific.
Uh yeah.
Specific code specific ID.
But after edit fields we we need to upload the URL inside the upload.
So what we do we just take the content and we upload it to the Plato.
For this case we use the method which is post inside our document.
We've got this URL.
So back end conversion to media.
We just provide it here.
Then what we do for the authorization we pick the generic credential type header authentication.
So we pick generic credential type header authentication.
And then we create new credential.
So I will show you how it works I've got upload it.
And here in the name just type protocol and Dash API key.
This exact name um it's defined by the um if you if you don't provide this exact name, you provide
something else.
It won't work.
Simple as that.
For the value you need to provide API key, go ahead to blog in the settings.
Um, just move down and click on copy API key.
Just provide it here and then I'm just simply delete it paste it and you've got your credential created.
For now, let's close it.
So you do it by this way when it comes actually, um, to the other things, to the other settings inside
this node, we need to send and body.
So in general we only send the URL.
So we simply send the URL from um the previous node.
In general we click on send body.
Then what we do uh we are using JSON.
Now we are using fields below.
Then we provide the name which is URL.
Again type the specific field.
And for the URL we provide um here the URL from there.
So we've got the URL get image url JSON item.
That's perfect.
We execute the step and after the process is finished we have the URL.
So now the image is stored inside data instead of the application which is cloudinary with the Cloudinary
we wanted to take an Earl, but then we just simply want to apply that to the potato, because potato
manages our entire content and uploads that on social media.
When you paste this, when you copy this URL and you paste it inside your browser, you should see your
image.
So let's wait.
We've got our image will be using.
That's perfect.
And then it's the perfect time to connect.
Um, yeah.
To connect our content and publish it on social media.
So firstly, let's take a look on the Instagram account.
We'll be using HTTP request.
And there is the point.
We are not connecting to Instagram directly however to potato that connects to Instagram.
So we choose the method which is post inside.
Here we pick this URL.
Okay, so let's pick this URL and then let's just read.
We need to provide the authorization authentication actually, which is the same as previously.
And for the send body we need to provide only the JSON code, so simply let me copy it for the authentication
generic credential type then header authentication data.
So pick the credential we we set up previously send body using JSON and just provide this JSON code.
Just provide it here.
And what it does let me show you.
We've got a post method.
We've got the target target type.
So Instagram for the content we want to take the text from this field.
So this a agent create an idea agent.
So we pick this description for the media URLs.
We pick the media from our model.
And this is our blood idol.
So we just provided there JSON url account id.
So we provide the account ID from our edit fields.
This is for the Instagram.
So we simply drag and drop this Specific variable.
And that's pretty it.
Let's rename it as Instagram.
Instagram.
Now let's execute this step.
So we need to wait a while.
So for now I can see in the description we've got these signs that allow us to go to the new line in
the content.
However in the JSON format we can't have that.
So for now what we can do, I can update the system message and you will have also that in the notion
update later.
So for an example, what I can do let's say in the output format um we can type never use.
That.
So this this sign to go let's say um to go to the next line.
So for now never use um, the sign and the content to go to the next line.
All right.
And for this case, unfortunately we need to repeat the entire process.
So run again this entire automation to actually publish our Instagram post.
But after it's done you can notice our description is set up properly, formatted properly.
So now everything should work.
Let's wait until it generates an image.
It goes through all of the nodes.
So I think it will take 10s more.
So let's wait and preview if it was the problem.
Also remember in really long automations like yeah let's see.
Nice.
It was a problem.
But what I wanted to say actually and long automations many times you will have a lot of problems.
So for an example if this node create an idea agent and other different things.
So you know by setting it up like it takes a lot of time.
But um, yeah, for now we can see it works.
So it published our content on Instagram.
And for this case, let's check it out.
If it worked.
Uh, we can go ahead, um, to our profile and then, like, see one minute ago.
Perfect.
We have our description post, like, you know, like.
Yeah, description, image.
Everything is correct.
Also, if you go ahead to potato, you can click on publish posts and then this post should be visible
right there.
So Instagram created at two minutes ago post URL content.
Also if something fails um, you've got failed posts uh, right there, you know, so it works by this
way.
However, let's move on to other, um, HTTP requests.
So the next thing we'll setup will be the TikTok.
Let's click on it, click Ctrl D and just put it here.
Also again let's click Ctrl D not this one however this one Ctrl D again Ctrl d.
Um.
So let's provide five HTTP requests.
Um I'm sorry.
Let's provide five HTTP requests and for each let's rename it.
So we had our Instagram.
Now we have the TikTok, Facebook, LinkedIn and Pinterest.
And also we need to connect our HTTP request which is also we can rename it.
So.
To each platform.
Remember like this Instagram for an example node is not connected to TikTok and this TikTok node is
not connected to Facebook like it looks like it's connected because it's very close.
However, you know, I wanted to show you to don't run out into some problems, but let's connect each
node with Play-Doh so it processed with all of the nodes at the same time.
And now let's move on to the TikTok for the TikTok.
Actually, for each node.
We don't change anything here, however, only the JSON format.
So let's move on.
Um, in the instructions you've got everything, so let's just paste it said.
And see what we have inside for now.
We've got media URLs, so then we just provide like there, we just provide the URL from.
Um, simply it doesn't work because we've got like other name for the URL, which is if I move on here
I just remove upload two.
You see it works.
So yeah.
Um, it's by this way, um, and then what we have inside, um, we publish the content on TikTok and
it's very important because TikTok is for the videos.
However, also we can publish images.
All right.
Um, and then what we do inside, we add the auto music.
So we say it's true.
So it selects for us the music based on our content in general.
We've got other variables.
You can read them and you can go ahead to TikTok API documentation.
Also in the other video in this course, I explained everything more in depth.
Nevertheless, now we are interested in content.
So for the text we provide a text description from create an a and idea a agent.
So this one agent so description.
And again for the media URLs we provide a Dado.
And for the account id we provide the account ID or just uh actually here uh, we just take the account
ID from TikTok.
And for now I can see I don't have the TikTok, so I will leave the value as the static one.
Um, however, again, with the Dado, you can just, uh, when you go to the settings, you can just
log in with TikTok.
So it's simple.
But for now I can say we can execute this step and wait.
Hopefully it works nice.
As you can see, the content is successfully published on TikTok.
So with the music also, and maybe it's not the best format for TikTok because we've got one image and
they're only, you know, we've got only the description.
Uh, however, still, this is a good habit to test out, like different platforms where you can publish
just, you know, just set up the TikTok account, publish this content.
Also, if you are more advanced, you can just experiment with this entire automation.
So let's say instead of just one image because here I'm just look, I'm there in the JSON file.
We've got only one image.
You can create multiple images and then just customize this content for the TikTok.
So create something like this.
Let me show you um, on this account, actually in this course we've got also the automation to publish
this type of the content.
So let's see, do you think with the music and it changes the images and it's pretty nice.
It gets a lot of likes and a lot of views.
But let's go back to our automation and now connect other different fields.
Uh, let's do it pretty fast.
So this is a Facebook, um, just take this code base there.
Um, and here again I need to provide the upload blood idol.
That's perfect.
We can execute the step.
Nice.
The next thing is our LinkedIn.
So again, this is straightforward process.
You just take the JSON code I prepared for you.
Um, nice.
You execute the step.
And the last thing actually last node will be Pinterest.
And there it can be a little complicated.
However, I will show you how how to do this because for Pinterest you need to have your board ID.
This is the point.
You need to have your board ID.
However, Pinterest doesn't provide directly your board ID we need to do some trick.
So let's provide here our data and we need to take this board ID.
Let me show you how to do this.
Go ahead to Pinterest.
Okay.
Um, and then just click on your page and on your profile, actually.
So here, um, let's move on to my profile and on your board.
This is my test board.
And now click on right click Inspect Element.
Then go ahead to the network.
And here just refresh this tab.
And then inside type boards uh resource resource okay.
Just click here.
And now in this resource just take this entire response.
So just take this entire response.
Just copy it.
Go ahead to ChatGPT and type give me my board's ID and just paste this entire code.
And it should give you your boards ID.
Let's wait.
All right.
So it's not that actually um, it's not that simple.
But with this case, um, yeah.
Let's go, let's go.
ChatGPT with this case, you can get your boards ID very simply.
So my boards ID is this one.
Let's move on to Na den and paste it here so I can paste it here.
Um and click Execute Step.
Hopefully it works.
All right.
Um let's see.
Um we can refresh the page and as you can see we've got it.
So this is our post published and it's perfect.
And the last step for this entire project is to uh yeah, save the data, actually make it mark as done
and upload an image URL inside Google Sheets.
For this case I can delete this part.
This part and this part.
Um, change the status to done and provide image URL.
Um, let's provide it from image URL.
Let's execute this step and see if it's done here.
So yeah it's done.
We've got image URL.
So this is pretty everything.
By this way we created really complicated, I can say, sophisticated automation for creating perfect
content for our social media.
So then again, we actually use perplexity to do a research.
We use our think tool OpenAI, and it creates for us an idea with title description, hashtags.
Then we create, we give this information to this agent that creates for us the prompt.
This prompt is is moved forward to the HTTP request.
So we use image ChatGPT image generation model to generate an image.
We convert that to the file.
We get image URL we provide.
Inside this edit fields node, we provide all of the credits actually IDs for our accounts.
Then we connect our blood and our blood uploads.
You know we connect with Instagram and TikTok, Facebook, LinkedIn, Pinterest.
So simply we just post the content on these platforms and at the end we save the data inside Google
Sheets.