In this lesson, we are going to talk about the selection of orchestration frameworks.
So as you know, right now the main orchestration frameworks are long chain and lambda index.
Lansing is an open source framework.
It facilitates the interaction interaction with one or more LMS at and.
It has multitude of features from the simplest to the most sophisticated, such as load balancing,
fault tolerance or security.
Llama index is also an open source framework.
It also has many functionalities similar to long chain and it has some exclusive functionalities like
for example, the ability to interact with LMS in a distributed manner or the ability to interact with
a broad ecosystem of tools including LAN chain, flask or Docker.
This facilitates the deployment and scaling of applications.
Why do we need orchestration frameworks?
They allow the use of foundational arms in countless applications and with external data.
They avoid the alternative of retraining them.
They eliminate the limits of the context window with what we call the rag technique.
We will see more about that later.
They provide countless connectors for databases, cloud storage, and numerous external APIs, and they
provide many pre-designed tools for frequent tasks like data extraction, transformation, and loading.
What are the criteria?
Uh, the main criteria for choosing the right orchestration framework.
Easy, too easy of use, flexibility, scalability, reliability, and the existence of a support community.
This is very important.
The last one, the existence of a support community.
Because as long as you have a big support community, you have a lot of projects available for you.
You have a lot of people that can help you solve questions, excuse me, or doubts or problems, etc.
so I repeat, the criteria for choosing the right orchestration framework would be ease of use, flexibility,
scalability, reliability, and existence of a support community.
We are going to give you our honest opinion of a long chain llama index, and also the alternative of
OpenAI API in a in a in a next lesson.
So we will apply our own judgment and we will give you our advice, uh, regarding the orchestration
frameworks.
So one last note.
Apart from luncheon and a llama index, you have some alternative orchestration frameworks less popular
right now, like prefect airflow, airflow, Luigi or Daxter.
In our opinion, they are right now.
Not very significant.
And we will well, we we are going to focus our attention in launching Lambda Index and OpenAI.
The API of OpenAI.
But we wanted to tell you that there are other alternative alternatives in the market that right now
are just for a minority.
But in the next months or years, this situation can change.
So it's interesting for you to understand that there are alternatives.
Take a look at them and maybe try some of them for your experimental projects.
So in this lesson we have talked a little bit about a the most important criteria in order to select
your orchestration framework.
In one next lesson, we are going to give you our honest opinion and recommendation about that.
So before doing that in the next lesson, we are going to talk about some other interesting notes regarding
the advanced architecture of LM applications.