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Hello guys.

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So we are going to continue our deployment series already.

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In our previous video, I have already shown you how you can deploy your generative AI application with

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Streamlit web app with the help of Streamlit Cloud.

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And probably the steps were quite easy.

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We just need to put all the code in our GitHub repository.

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And from this we just need to connect it in our Streamlit lab.

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Now, uh, Streamlit lab or Streamlit Cloud, you can basically say in that way, now I am going to

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deploy this entire code solution in hugging face spaces.

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Okay.

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Now spaces actually provides you, uh, you will be able to probably deploy your generative AI applications

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over here or any machine learning applications over here.

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So step by step, we will probably go ahead and I'll try to show you completely in a very much easy

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way here.

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If you just go in spaces, you'll be able to see many, many, many use cases which are specifically

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deployed.

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And you can go ahead and check it out.

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And you can also check out the code.

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Right.

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So, uh, let's go ahead and do this.

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Uh, there are many steps that it will be involved while probably deploying this entire solution in

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the hugging face spaces.

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Over here we are also going to use something called as GitHub action.

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Okay.

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So here if I go ahead and search for hugging face space okay GitHub action okay.

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So here you'll be able to see managing spaces with GitHub action.

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So if you probably go ahead and see this repository this is the code that we are specifically going

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to use.

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So we will be creating an YAML file.

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And we will say hey you need to push in this particular hugging face space and probably do the deployment

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okay.

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So here I will be going ahead and showing you step by step how this things can be implemented.

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So first of all, I will go ahead and create a new file inside this repository.

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Now first of all here I will be using one folder called as dot GitHub.

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So usually whenever you create a CI CD pipeline you really need to create a YAML file.

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And the entire configuration inside that YAML file will actually tell you that how you're going to push

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the code in the deployment servers.

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Right.

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So for that I will be creating this dot GitHub slash workflow okay.

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Workflows.

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So this is the folder that I'm actually going to create.

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And inside this I'm going to create this main dot YAML file okay.

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Now with respect to this main dot YAML file, what I'm actually going to do I will go ahead and copy

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this entire thing.

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So here you will be able to see this is the important code that I will be copying.

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Right.

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So this code is responsible.

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And as soon as we do the commit in the GitHub repository, this will be pushing our entire code repository

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into this particular hugging face token.

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Okay.

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So hugging face uh space okay.

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Here, uh, please observe each and every thing carefully.

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What is the necessary information here.

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You will be able to see it out okay.

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Okay, so let me just do one thing.

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Let me just hide this if possible.

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So first of all, over here, you'll be able to see that, uh, whenever we work with GitHub action,

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most of the parameters will be in the form of key value pairs.

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So this is nothing but syncing to Huggingface hub.

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We are pushing the branch.

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Main job is basically to run this entire thing in the ubuntu latest version.

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We will check out all the code and finally we'll push this to the hub, which is my Huggingface hub,

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and we will be using some secret token that is our F underscore token.

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I will show you how to probably create this particular token and where we need to push.

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We need to push on this specific space ID okay.

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Now how to get this space ID.

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I will be talking about it.

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Okay.

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So let's go back to our huggingface space and let us go ahead and create our new space here.

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I'm just going to write, um search underscore engine underscore LM okay.

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So this will basically be my, uh, application name over here, which I'm actually creating in my space.

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After that, I will go ahead and select a license.

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Let's say I go ahead and select Apache 2.0.

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I know this is a Streamlit app, but other than this it is a for uh, for Grady.

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Also it is supported for static templates.

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Also it is supported if you really want to work with Dockers.

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It is also supporting that.

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Right.

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And here you have a space hardware free by default.

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They'll give you CPU basics with, uh, two Vcpu and 16 GB free Ram.

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Okay.

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You can actually go ahead and use this.

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This will be more than sufficient to go ahead with right then.

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Uh, whether you want to make this space public or private, let's say that I want to go ahead and probably

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create this particular space in public.

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So I will go ahead and click on Create Space.

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Okay.

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As soon as I probably click on Create Space here, you can see that I can clone this entire thing and

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I can start working.

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Okay.

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If you want to go ahead and see how many files are basically present over here inside, none of the

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files are specifically present.

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So what I'm actually going to do from my GitHub, whatever files is there, I need to push to this particular

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Huggingface hub right where this all files will be present.

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Right now, the most important thing is that how do I generate this h.f underscore token or this particular

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token.

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Right.

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So for that what I will do, I will go back to my Huggingface hub or Huggingface.

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I will click on settings button.

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Okay.

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Now inside this settings button I will go and click on something called as Access Token.

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Now over here you'll be seeing that I've created so many access token to start with, I will just go

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ahead and write new and let's say I will go ahead and, uh, create my token over here.

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But please make sure to select the type as right.

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Okay.

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So let's see whether it is right or not.

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No, it is fine grained.

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Uh, let me just go ahead and create my access token once again.

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So I'll be going over here.

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I will click on new token.

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I will write token one okay.

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This will be the name of the token and type I will go ahead and select as right.

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The reason why I'm selecting as right.

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Because I need to push something into the hugging face hub in inside this particular space.

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Right.

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So all the files I need to push it over here.

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So for this I need to write I need to get an right access token.

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So I will go ahead and generate a token.

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And I'll make sure to copy this specific token okay.

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And this particular token I will store it in my notepad so that I will be using this where I will be

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using it and talk about it okay.

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So let me just go ahead and close this after creating the token.

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Now I'll go back over here.

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This is the first step.

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I've created my token right.

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Now the next thing that you'll be seeing over here I have something called as git push git uh https

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hugging face underscore username.

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Now what is my hugging face underscore username?

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It is nothing but Krishna zero six so I will just go ahead and write it over here.

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Krish Krishna zero six okay, so this is my first hugging face token information that I have.

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Sorry.

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The username information that I have that is Krishna zero six.

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Then I will be using the same hugging face token over here then hugging face dot o.

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Then here you'll be able to see.

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I have to also mention the hugging face user name here too.

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So let me just go ahead and write Krishna zero six along with this.

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My space name.

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My space name is very simple.

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I need to use this search underscore engine underscore LM okay.

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So now here I will just go ahead and write search underscore engine underscore LM okay.

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And then this basically goes to the end.

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Please make sure to make the spelling right.

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And finally this is going to my main branch.

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So that is the reason we are pushing this entire information into the main branch.

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And this is my main branch right inside my huggingface space.

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So yes, this was all the information that I need to put over here.

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Now the next thing is that I will go to my settings okay.

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I will click on settings over here okay.

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Uh, inside the settings uh there will be something called as secret and variable.

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Okay.

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Now inside the secret and variable I will click on actions.

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And here I need to go ahead and create my secret key repository secret key.

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The new repository secret key that I am actually going to go ahead and create.

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Right.

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It should be the same name right h f underscore token.

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So as soon as we call this code secrets dot h f underscore token, it is going to take this particular

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token from here.

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Okay.

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And this particular info that I have will be this key.

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Right.

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I will be assigning it over here.

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And then we will go ahead and click on Add Secret.

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Once we add the secret here you can see it is my F underscore token.

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Perfect.

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Now this work is done.

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This is also updated.

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This my entire uh this run where we need to push the code is also updated.

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And as soon as I do this, I'll just go ahead and commit the changes.

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Okay.

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So once I commit the changes, now an amazing thing is going to happen suddenly.

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Just click on this actions.

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Now see this?

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This entire CI CD pipeline is running.

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If I go inside this, these are the steps that will happen on push.

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Right now it is starting the job.

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And here you can see that I am getting some kind of error okay.

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let's see what is the error.

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So here you can see two hugging face spaces.

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Crush engine rejected.

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Main fetch.

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Failed to push some reference things.

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Uh, this is usually caused by another repository pushing to the same reference.

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Okay.

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Now uh hint have locally this is used by another repository pushing to this.

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Right.

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So here uh what is it is basically saying is that I before this, I tried to test one of the repositories.

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And based on that, I was just trying to push it.

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Okay.

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So I will go back to that particular repository and I'm pushing it to the same thing.

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So that is the reason it won't make any sense.

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Let me just do go back to my repository over here okay.

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And let me open that particular repository okay.

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Search engine.

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All right.

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So this is my repository here.

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You can go ahead and see that I have my GitHub workflows.

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And now again what I will be doing I'll be having this entire thing right over here.

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Now let me do one thing quickly over here.

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That what I will do is that I will go back over here in my code.

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Okay?

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And don't worry, because of this error, you may be getting confused because I just tried it before

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earlier, right?

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I will just go ahead and update it just to show you how things happen.

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Right?

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So here I will just update one of the file okay.

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One of the file.

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Yeah.

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And then I will just go ahead and commit it okay.

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So here let me just go ahead.

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So here you can see I will just edit this file okay.

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I will just go ahead and commit it okay.

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I will just commit this particular changes as soon as I commit this changes if I go back to my code

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one amazing thing is basically going to happen.

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Go to the actions and here you will be able to see I have updated the app dot Pi.

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It is telling me to sync to hub.

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Now this entire code is basically with push.

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Right now.

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This push has actually happened in my huggingface space, right?

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So I will go ahead and see this particular link.

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Now you'll be able to see the magic right?

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So once I hit this link right it is giving me an error okay.

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Okay, first of all, this readme file.

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It's okay.

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We'll try to fix this.

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But if I go and see in my file section, you'll be able to see that I have my API, I have my requirement

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dot txt and along with this I also have my GitHub workflow right.

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The entire GitHub workflow perfect.

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But still we are getting an error how to fix that particular error, right?

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So what I will do, I will just open my readme file okay.

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And we need to edit this readme file.

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Okay.

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So what I will do, I will just remove this because it requires some special characters like I need

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to add what kind of license is there?

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I will go ahead and say, hey, this is my search engine.

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Okay?

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Then I will ask the SDK that is Streamlit.

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I will add some kind of emoji.

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Okay, something like this and I'll add some color form.

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Let's go and add this and short description.

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So this is nothing but search engine with LM okay.

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Now once I update this quickly, uh, let's commit this changes to the main file.

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Now here, if I go back to my apps in this huggingface space, now this see this entire thing, the

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entire build will start running.

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First of all, it will go ahead with installing all the requirements.txt.

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Right.

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So if I just go ahead and see this right see over here all the requirement dot txt is basically getting

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hit and the container is going to get built up right now.

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And once this is built my entire application will show up over here.

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Right.

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So we'll just wait for some time to just show up the things over here that we are looking for.

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And uh, till then, uh, if I just go back to my files over here, okay, in In my files, please make

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sure to download this readme file, because I need to use this same readme file, uh, inside my GitHub.

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Right.

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So I will make sure to update this entire thing.

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So I will just copy this and I will go back to my app Dot Pi.

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And let's go ahead and update it over here okay.

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So in order to update it I will just remove this and I'll paste it over here.

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I'll commit the changes.

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Okay.

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Now as soon as the commit will happen automatically this particular code is there.

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But again the action will go ahead.

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You know.

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And this is all because the CI CD pipeline is running.

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Whenever I do any kind of commit and all automatically the push will basically happening in the hub

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right in my in my hugging face space.

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Okay.

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Now finally, you can see my entire application start up will start running.

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It is taking some amount of time because there are lot of inbuilt uh, they all the all the requirement

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dot txt libraries will get installed and uh we will just wait for some time.

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It is still building the entire container and the entire application that we really want to run will

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be shown over here.

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And this is how you can actually do the entire deployment just by using the CI CD pipeline.

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And this is what is an example of GitHub actions right here in this main dot YAML file.

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What I have actually done is that I've told, hey uh, on push you have to push it to the main branch

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where we need to push, we need to push it in our hugging face space.

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And that is the information that I've actually given over here.

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Right.

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So this was one of the most easiest way to probably do the deployment.

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And you can probably do any kind of generative AI applications that you really want to do.

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Right.

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So let's do one thing.

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Let's wait for some time and let's, uh, let the build specifically happen.

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And once it happens, I will probably show you the next steps, okay.

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And we will also test out the test out the entire application over here.

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So yeah, let's wait for some time.

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So finally, you can see guys, uh, this entire application has started.

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So we will hide this.

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And here is our entire application working on this particular hugging face spaces.

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And you can probably pass this particular URL, share this URL.

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And you can show everyone that what you have actually developed right now, we will quickly go ahead

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and I will be using my environment variable and I will update my grok API key.

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You can probably get the grok API key over here, paste it, press enter, and after this I will just

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go ahead and search for what is machine learning.

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And I think I should be able to get the answer okay.

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So thinking search thinking invalid tool Wikipedia no need.

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Then from the search itself we are able to get all the information it did not think to probably go to

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Wikipedia and here is my information right now.

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Still, if I go ahead and ask what is generative AI, I should be able to get my response again.

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It is searching from this DuckDuckGo search, um, search for generative artificial intelligence and

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all.

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So here you can see requested tool Wikipedia search arXiv and Wikipedia.

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Right?

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Wikipedia if I keep on second.

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Okay.

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And uh, it is saying that it is not a valid tool, it is not required.

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And here is the information with respect to our generative AI.

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So I hope, uh, you are able to understand this entire deployment mechanism.

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So I hope you are able to understand this entire deployment mechanism.

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You can probably go ahead and deploy anything that you want.

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And I think this hugging face space will be more than sufficient.

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But at the end of the day, I have actually shown you how you can create this entire thing with the

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help of this GitHub workflows, uh, where we have also used GitHub actions.

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So yes, this was it from my side.

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I will see you all in the next video.

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Thank you.

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Take care.

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Bye bye.