Okay, so here you have the notebook.
This is the main document for you to to read.
And the slides which include a summary of the contents you see in the notebook.
You will also be able to download the code of this exercise from GitHub.
But see here in the notebook the the main steps we are taking in order to to build this Rag application.
So we are going to use the PDF full stack application.
Uh, we build in the in a in a previous lesson, the second application we have built in this block.
And we are going to include some changes to this, uh, to this file.
So remember that you will need to add the OpenAI key in the dot env file in the back end.
Remember you don't want to share this, uh, OpenAI key with anyone.
So remember to update your dot.
Gitignore file in order to avoid you to share the contents of this file.
When you load the content of the project into your GitHub repository.
Okay, so this is important.
Second thing you will need to add the imports, uh, for launching an OpenAI in the back end routers
PDFs.
Uh py file okay.
So remember that, uh, in your case you will have to use a different way of, uh, importing because
you will have to include the changes, uh, of the uh, version 010 from launching.
You know, about that.
We are going to include a reminder video, uh, in this, in this blog as well.
But we have included the reminder several times.
You have a reminder in the in the level one applications block, and you also have the reminder in the
level two applications block.
So remember that the the main change of the uh, version 010 is that instead of importing, for example,
OpenAI in this way from long chain import OpenAI, now you need to use a new package called called long
chain OpenAI to do from long chain OpenAI import OpenAI.
So you remember the changes.
So so please, uh, modify this, uh, code with the new code you need then after you have done it.
You will have to change the code in the in the functionality.
Right.
So this is the simple functionality we, uh, started using in the previous app.
You remember that we initially did a very simple thing and then went to the poem writing.
So this is the simple, uh, and the simple functionality just for you to try it with this, with this
app as well.
You know how to try it.
It's the same way we we did it in the, in the previous exercise.
And now is where uh, here you have the A code you need to enter in the same back end routers pdfs.py
in the same file.
This is the code you need to enter in order to, uh, make a rack technique work in this, uh, in this
application.
Okay.
And in order for this to work, you will need to add all these, uh, imports in the in on the top of
the file.
Okay.
So you will be able to check this new functionality with a, with, uh, your terminal.
Okay.
So this is a way to ask a question to your, uh, PDF, a document.
Okay.
But we are not going to include the front end, uh, changes here.
So this is going to be your first to do, uh, task.
Okay.
So this is going to be your homework.
So we are including a first version of the rack code.
And it will be for you to, uh, update the front end with the knowledge you already have and to fine
tune the, the back end, uh, in that way.
Okay.
So, uh, what we want is that the user selects one PDF file, and then he can enter a question about
it in the in an input box below the main PDF list, uh box.
And after the question is submitted, the answer is displayed below.
Okay.
So take a look at this and try to prepare the front end for uh, this application.
Okay.
So let's go to the next lesson where we are going to deep, uh, to dive deeper into the most advanced
LM application of the, uh, program.
So let's go there in the next video.