From the course: Creating Advanced AI Applications with Python, APIs, and GitHub Models
Using GitHub Codespaces
From the course: Creating Advanced AI Applications with Python, APIs, and GitHub Models
Using GitHub Codespaces
- [Instructor] Imagine you are tasked with creating a fully functional AI app by tomorrow morning, right? Like me, you have no experience in web development. And in the next few videos, I'll show you one way of going about this using the GitHub ecosystem. So we'll need a couple of things to create an app. You'll need a text editor, you'll need the Python packages that your app will use, and then you need some way of accessing the large language models using their API. So for a text editor, I'm going to use GitHub Codespaces. Now, whenever I need to create a prototype for an AI app, instead of just spending hours setting up my development environment, I just use GitHub Codespaces. It's my personal cloud-based, fully-equipped workstation. And I can access this from anywhere, even on a different device as long as I have an internet connection. Now, especially if I'm working with a team, everyone has the same environment, and I don't have problems, like it works on my machine and so on, right? So the first thing we'll do is we'll create a repository on GitHub, right, so this is my GitHub repository. And if you don't have a GitHub account, create it at github.com, it'll only take a few minutes. So I'm going to head over to create a new repository, and I'm going to give it the name "moneychanger". (keyboard keys clicking) I'm going to give it a description, so this is going to be Currency exchange. I'm going to leave it as Public. I'm going to add a ReadMe file, and then I'm going to go ahead and add a Git Ignore, 'cause I'm going to be using Python, I want to add a Git Ignore with a Python template. And let me go ahead and create my repository. So now that I have my repository, I can head over to Codespaces, select New codespace, and now I go ahead and select the codespace that I just created. So I've got "JohnFernandezmoneyChanger". Because I live in England, the closest region for me is Europe West. A two core machine is plenty for what we need to do, and then I'm going to go ahead and select Create Codespace. And that's it, we're done. We've now created our text editor in the cloud. I'm going to go ahead and create a Python file because that's what we're going to be using. I'm going to call that moneychanger.pi. Now, I've created some starter code called Code Template. So head over to github.com/JohnFernandez/moneychanger, and look for code_template.pi. Go ahead and copy all of the code from here, and let's copy this across to moneychanger.pi. Now, this is going to be a code skeleton or a code template that'll allow us to create our app over the next few videos. All right, so we've seen, in this video, that it's easy to get started with creating our app using GitHub Codespaces. And over the next few videos, we'll develop our app together.
Practice while you learn with exercise files
Download the files the instructor uses to teach the course. Follow along and learn by watching, listening and practicing.
Contents
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Using GitHub Codespaces3m 32s
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Using ExchangeRate-API.com4m 56s
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(Locked)
Challenge: Get_exchange_rate21s
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(Locked)
Solution: Get_exchange_rate5m 46s
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(Locked)
Challenge: Choose an LLM supporting multiple languages24s
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Solution: Choose an LLM supporting multiple languages3m 27s
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Challenge: Create an app layout37s
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Solution: Create an app layout3m 56s
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Challenge: LLM API call58s
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Solution: LLM API call6m 28s
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Function calling: Add function calling code1m 43s
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Challenge: Function calling1m 12s
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Solution: Function calling8m 57s
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Challenge: Using tools when required52s
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Solution: Using tools when required8m 44s
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Deploy the app to production6m 10s
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Working with LangSmith8m 22s
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