Hey there, Ethan here.
And in this video, we'll be setting up our project of our reflection agent.
So we'll create the project directory, and we'll use poetry to create our virtual environment and to
install our dependencies.
We'll then open PyCharm and configure it to point to the virtual environment we are using.
And we'll create a dot env file that will hold all of our open AI API keys and Lamb-smith API keys,
because we're going to be using Lamb-smith for tracing.
By the way, all of the code of this video and the rest of the series is going to be on GitHub.
So for this section it will be on the branch one.
Start here.
So in case you need to compare something you want to check out which versions I'm using.
So feel free to check it out.
Alrighty let's go and CD into desktop and I will creating a new directory.
And I'm going to call it Land Graph Course.
And let's go into this new directory and let's initialize our poetry environment.
So I'm going to write poetry init it.
I'm going to click enter and continue with the setup.
And right now I have my poetry environment setup and I have a pyproject.toml file.
Let's check it out.
Nothing is yet installed.
So let's go now and install everything.
So I'm going to write poetry add and let's install Beautifulsoup.
And we need this because link chain will use this library when it's going to download files from the
web that we're going to ingest into our vector store.
Let's install link chain link graph link chain hub.
And we also want link chain community because we're going to be using third party loaders for loading
our documents.
Let's also install the SDK for our search engine.
And I want to install chroma as our open source vector store.
We want Python env for our environment variables.
Black and I thought for formatting.
And lastly let's also install Pytest because we're going to be writing tests and we love writing tests,
don't we?
And writing tests in generative applications is something which is super important.
That's why it was really important for me to include testing in this course.
And let's hit enter and install all those packages.
So it's going to take a minute.
So let me just fast forward it.
And all of our packages are installed.
We want now to open everything in PyCharm.
So I'm going to select the project directory.
It's going to be here.
And we can see that PyCharm detected my poetry environment I'm going to approve it.
And we are now indexing all of our packages.
And if we'll take a look at our pyproject.toml file, we can see all the versions that we are using
at the moment.
And I will be updating the courses repository to be with the latest link chain and Landgraf versions
all the time.
Alrighty, let's go and create a new file and it's going to be our dot env file, which is going to
hold all of our environment variables.
So I'm simply going to paste them in and I'm going to put the OpenAI API key the API key.
And we're going to enable Laxmi Tracing.
We're going to call the Linux Mint project Chirag.
We'll be needing our API key for our search engine.
And I defined the Python path to point to the project's root directory.
Alrighty.
Let's create now our main file.
And here we want to simply write the boilerplate code to first load the environment variables.
And then to print something we'll print hello Advanced Rag.
And let's as a sanity check run it and see that everything is working amazing.
So we can see everything is working correctly.
And if you want you can go to the courses repository at the branch one.
Start here to check out the code.
In the next video we'll cover the repository structure.