Hello guys.
Welcome to this new amazing module on building generative AI application using Landgraff.
Now Landgraff is an amazing library that is available in long chain and with the help of Landgraff,
you will be able to build stateful multi actor application with Llms used to create agents and multi-agent
workflows.
Right?
And one amazing thing about this agents will be that they will also be able to communicate with each
other, right?
Specifically, if you're working in some data science projects, you know, you'll be having data analysts,
you'll be having data scientists, you will be having product managers, you'll be having program managers.
And, you know, while developing the entire project, there will be a lot of communication with all
these specific roles, right?
With respect to requirements, with respect to development and many more things.
Now we can actually create those kind of projects with the help of completely different, different
multi agents.
You know, each and every agent can specifically perform different different tasks.
Let's say for my project, I want to probably create a multi-agent, uh generative AI application where
I may have a data analyst, I may have a data scientist, I may have a program manager.
And I can probably implement all the functionalities with the help of this AI agents itself.
Right?
And that is what in order to efficiently manage this entire workflow and the stateful management, we
specifically use line graph.
Okay.
Now in the upcoming videos, you'll be seeing some amazing projects where I will be showing you the
importance of line graph.
Now, compared to other LLM frameworks, it offers this core benefits, that is cycle controllability
and persistence.
Line graphs allows you to define the flows that involves cycles essential for most Agentic uh, architectures,
differentiating it from uh Dag based solutions.
Okay, so there will be a lot of things that we will be discussing as we go ahead.
Um, why this module or why this library is super important?
Because, see, uh, if you have already seen this particular post lang graph or what Lang has actually
done is that they are also coming up with this Lang Graph Studio.
Okay, now, with the help of this studio, what you will be able to do is that you will be able to
create all these workflows just by drag and drop.
Right now, this particular studio is just available in Mac.
Okay, but don't worry, as soon as it gets uploaded from both Windows and Mac, I will start making
the videos on that.
Also just by doing drag and drop here you can see just by doing drag and drop you will be able to implement
the entire workflows.
And right now in our course till this entire studio does not come as an open source availability.
What we will do, we will try to write the code for all these things, okay.
And that will be the best thing to probably learn, because once you learn all those things, working
with the studio will be super easy, right?
So here you can just see an example, right?
When we are specifically running this entire workflow.
Right?
How step by step it is able to run.
Right.
So here you can also see here you can also see an example.
This is my workflow that is probably running up I'll ask a specific question who created you.
So step by step it will probably go to the agent.
It will take an action.
It will go and execute each and every code.
And it will go ahead and execute and show us the output response.
That is the most amazing thing, right?
So, uh, right now in this upcoming series, what we are going to do, first of all, we are going
to develop this with the help of Python programming language.
And along with that we will also be using a library called as line graph.
But once this studio is available, I will also show you all the examples with respect to that.
And probably it should be available in some time.
Okay, that I will keep a note on that and I'll keep on updating my course itself.
So this was just about line graph to give you an introduction.
But here please make sure that you remember this.
It is a library for building stateful multi actor application with LMS used to create agents and multi-agent
workflow.
And this agents will be able to communicate with itself and it will be able to perform various tasks.
And that is what I'm actually going to show you in the next video where we will deep dive more into
line graph and we will be developing some good projects.
So yes, this was it from my side.
One very important thing that I really also want to note that we will first of all start with Google
Colab, right?
We will work with Google Colab wherein we will go ahead and write our code, will execute and show you
each and everything.
Let's say I will give you one example.
This is one of the first project that we will specifically work on, where we will create a simple chatbot
application with the help of line graph.
And here you will be able to see that this kind of graphs will also be visible.
These are nothing but these are nodes right These are relationship that also we have learned in the
graph database.
And we'll see step by step how we will be executing all these things.
Right.
So yes this was it from my side.
I will see you all in the next video.
Thank you.