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-: Hey guys, Eden here.

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So this is a very cool part of this course,

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and we're going to be implementing something

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that's called a documentation helper.

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So we're going to plug in the documentation

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of a certain package and we're then going to be able

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to query with the LLM questions about the documentation, how

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to use it, examples, a lot

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of very cool and interesting stuff.

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And we're even going to use it in order to build this tool.

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So you'll see this dog feeling it's very, very cool.

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Now we're going to build this end-to-end.

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So it means running the chain that will get us this result.

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And also writing the front end

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and the user interface that will help us interact

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with it in a very elegant and convenient way.

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We're going to be cover a lot of topics over here,

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vector databases, retrieval, similarity search, memory,

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insider chat, Streamlit as a front end builder.

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We'll even dive into the lang chain source code

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to understand what's happening underneath the hood.

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So the first part of this project is

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to find a documentation,

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and we're going to take the lang chain

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documentation as an example.

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We're going to download it.

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We then are going to turn it into vectors.

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So we're going to take every page in the documentation,

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chunk it up, and then embed it, turn it into a vector,

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store it into a vector store,

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and then we're going to be using

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that in order to write a chain.

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So that would be the second part of this project.

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So in the second part, we're going to be writing a chain

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that is going to use the vector database in order

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to find us the correct chunks that we need in order

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to answer that question.

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After that, we're going

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to be implementing the user interface,

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and we're going to be using a package which is called

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Streamlit, which is very, very easy to use.

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And finally, we're going

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to be integrating memory into our chat.

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So we want our chat to have the memory ability

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to reference things that we asked it in the past.

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So that's an introduction for what we're going to build

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and let's go build it.

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And one last request, if you can please find the time

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to leave me a review on Udemy.

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This really encourages me as a content creator

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to continue in growing this course,

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and it helps other students decide whether this

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course is a good fit for them.

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So I would appreciate very much if

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you can leave me a review.

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Okay, now let's go and write some code.