In this lesson, we will talk about the advanced architecture of an LM application.
Remember that in the previous lesson we talked about the toy demos, what we call the basic architecture
of Elm applications.
And if you remember in this program, we talk about level one applications, when we also have when
we only have three components Elm Orchestration Framework and Vector Database.
And we talk about a level two applications.
When a we have these three components plus a what we call a toy user interface.
Case.
So the level one application and the level two applications are toy demos for us.
These are not professional applications.
When we are talking about a professional applications and we are talking about a full stack application,
what we call level three application or professional level application.
In this case, we have a back end framework.
Uh, front end framework.
A back end server.
A front end server.
And then we have external APIs and cloud storage.
Uh, plus the LLM foundational model.
So the most typical advanced architecture we are going to find.
Will be similar to the one you have in this slide.
So for back end server we will use render.
Com a.
For back end framework we will use fast API which is a framework based on the Python language.
We will use an orchestration framework that can be long chain or lambda index.
And we will use one or more than one databases, usually a one vector database and one traditional database.
In the front end a framework we are going to use Next.js, which is a type of react, a framework and
a we will have Vercel.
Com as a front end server.
Next year.
Yes, is based on JavaScript.
So in the backend we are going to play around with Python.
And in the front end we are going to play with JavaScript.
Don't worry, it will be easier and more simple than what you may think.
Then we will have a external APIs.
Connected with the back end framework, also the LM model.
Usually ChatGPT, and in many cases we are going to use cloud storage to store a our private files like
PDFs, for example.
And in many cases we are going to use S3 from Amazon Web Services.
So as you can see, the difference between a basic architecture and an advanced architecture is important.
A these are much more complex solutions.
And you need to understand that besides this architecture, we will need to work with a validation frameworks,
with LM ops, with a LM cache, etc., etc. we will examine all these elements in detail in the program.
In the next lesson, we are going to preview a professional LM application.