Hello guys.
So we are going to continue the discussion with respect to graph DB with Lang Chen.
Now uh, we will be implementing some amazing projects.
Again.
We are going to use the Neo4j's aura DB and we'll see that how with the help of Python programming language,
uh, along with Lang Chain, we can specifically use and create some amazing Jen AI applications.
So before we go ahead and start, uh, we need to set up this specific environment.
And again, uh, to set up this particular environment, uh, we have to make sure that we have all
the necessary libraries.
Um, here are the different kind of Python version I will be specifically using.
Okay.
So first of all, let's go ahead and create my environment.
So I will go to my command prompt.
And here what I will be doing is that I will just go ahead and write conda create minus p okay v and
v python double equal to 3.12.
And I'll give a yes um prompt so that it should continue the execution.
Right.
So now here you'll be able to see that in some time my entire V and V environment will get created okay.
So this is basically getting created.
Let it take some time okay.
And since it is getting created I will also go ahead and create my requirements.
Dot txt okay now in order to work with Python 3.12, you know we have to install Neo4j's and please
be specific with this particular version, right?
Because I tried out different version and it was not working exactly.
When we are specifically working with Python programming language.
Right.
Uh, specifically with 3.12 version.
So this was the right combination.
After a lot of research, uh, I saw and it was probably working in our local.
If you are using Google Colab and all, uh, you don't have to probably, uh, you know, just use this
particular version also automatically, whatever is the compatible thing over there, it will be considering
that right now I have this.
Along with this, I will also go ahead and install my Lang chain.
Then I will write lang chain underscore community.
Okay.
So this is what I'm actually going to use.
Um, not only that, I'll also use OpenAI.
I don't require OpenAI, but let's take this and then I'll also have lang chain underscore grok, because
we will be using uh, open source paid LLM models.
So open source LLM models not paid.
Then I'll have Python uh dot env.
So let's go ahead and install all this libraries.
So first of all I will just go ahead and say hey Conda activate V and we will clear all the screen.
And now let me go ahead and do the installation of all the libraries.
So spelling mistake.
It's okay I will just go ahead and pip install r requirements.txt.
Um lang chain underscore grok.
It's okay because I made a spelling mistake.
Okay.
Please don't forget to save the file.
Okay.
Um, so here you can see all the installation will start taking place.
So once you do this specific installation, uh, it is also necessary that we will go ahead and create
our dot env file.
So here I am going to specifically take my dot env file and um, you know, just to play with some of
the things.
First of all, I'm just going to go ahead and put my grok API key.
Right.
So this I will be requiring it so that I can go ahead and experiment with all my different, different
LLM models.
Right.
Um, different different open source models.
That is the reason we are specifically using this.
So okay, so uh, this was the basic setup.
Please make sure that you have this entire, uh, this version specifically.
You use it because we will be using this version with respect to the neo 4G or ADB, right?
Whenever we want to connect with the database itself and try to insert some kind of datas and all.
Now in my, um, so this was the initial setup.
Uh, in the next section, we are going to see that how we can go ahead and get started.
And again, for this, I've already told you, please make sure that you have the copy of your entire
database information.
And this.
I have told you to save it somewhere, right?
So this information please, you really require it?
Because I will be using this particular database information and try to access my DBS right to for the
insertion purpose.
So yes, uh, this was it.
I will see you all in the next video where we will be continuing the discussion with respect to graph
DB with long chain.