In this lesson, we are going to talk about the challenges of the rack technique.
Well, you have in the attached material a one document talking about the main challenges of the rack
technique.
A I don't think, uh, now is the best moment to go in detail about this.
I just wanted to give you the idea that in the rack technique, like in almost anything, you know,
in in programming, you have like a basic way of doing things, and then you have like an advanced way
of doing this or to improve, you know, the basic functionality.
So with the rack technique, it happens the same.
You have like a basic way of doing things, and then you can start optimizing the different steps you
are using.
In the case of the rack technique, we have two main phases of the of the technique that what we call
the retrieval phase when we are storing data, and what we call the response generation phase when we
are searching for an answer.
So in both of them you have ways to optimize the performance of the phase.
Right.
So we will see more about that uh, later in next, uh lessons.
But it was important for us to tell you that we have some challenges in the, in the, in the, in the
way.
Right.
So, so on every phase of the rack technique, we are able to use some optimization techniques to improve
the performance.
So we will see some techniques to overcome the challenges in each of the phases later.
In the next lesson, we are going to talk about the main considerations to select the right orchestration
framework in our opinion.
So we are going to give us to give you the, the our honest opinion about a how to decide from long
chain llama index or the API of open AI.