-: Hey guys, Eden here.
So this is a very cool part of this course,
and we're going to be implementing something
that's called a documentation helper.
So we're going to plug in the documentation
of a certain package and we're then going to be able
to query with the LLM questions about the documentation, how
to use it, examples, a lot
of very cool and interesting stuff.
And we're even going to use it in order to build this tool.
So you'll see this dog feeling it's very, very cool.
Now we're going to build this end-to-end.
So it means running the chain that will get us this result.
And also writing the front end
and the user interface that will help us interact
with it in a very elegant and convenient way.
We're going to be cover a lot of topics over here,
vector databases, retrieval, similarity search, memory,
insider chat, Streamlit as a front end builder.
We'll even dive into the lang chain source code
to understand what's happening underneath the hood.
So the first part of this project is
to find a documentation,
and we're going to take the lang chain
documentation as an example.
We're going to download it.
We then are going to turn it into vectors.
So we're going to take every page in the documentation,
chunk it up, and then embed it, turn it into a vector,
store it into a vector store,
and then we're going to be using
that in order to write a chain.
So that would be the second part of this project.
So in the second part, we're going to be writing a chain
that is going to use the vector database in order
to find us the correct chunks that we need in order
to answer that question.
After that, we're going
to be implementing the user interface,
and we're going to be using a package which is called
Streamlit, which is very, very easy to use.
And finally, we're going
to be integrating memory into our chat.
So we want our chat to have the memory ability
to reference things that we asked it in the past.
So that's an introduction for what we're going to build
and let's go build it.
And one last request, if you can please find the time
to leave me a review on Udemy.
This really encourages me as a content creator
to continue in growing this course,
and it helps other students decide whether this
course is a good fit for them.
So I would appreciate very much if
you can leave me a review.
Okay, now let's go and write some code.