Prerequisites
Last updated
Last updated
Before we dive in, let's ensure you have all the necessary prerequisites installed on your computer. Not only are these essential for what we're about to embark on, but they'll also be invaluable tools if you decide to contribute to open-source projects in the future.
Python 3.10 or above should be installed on your machine. If not, .
Pip: Comes pre-installed with Python 3.4+. It is the standard package manager for Python. You can check if it's downloaded by typing the below command in your terminal/command prompt.
If Pip is not installed, you'll get an error. In that case, you must download and install to manage project packages.
Git should be installed on your machine. If you've installed XCode (or its Command Line Tools), Git may already be installed. To find out, open a Terminal or Command Prompt, and enter git --version
. If it's not installed, refer to and install it.
This key is required if you plan to use OpenAI models for embedding and generation.
This is a good starting point if you are less confident with using open-source alternatives. If you want to use open-source models, you can find examples like .
By default, OpenAI currently offers $5 in free credits for new accounts – i.e., the ones with a new phone number and email ID. Alternatively, you can sign up for free credits on platforms like . These free credits should suffice for building your project.
As we advance, we will usetext-embedding-ada-002
in this coursework for generating the vector embeddings () and gpt-3.5-turbo
for text generation.
To create a new OpenAI API Key:
to the OpenAI website.
Navigate to the page to generate your key.
The example ahead only supports Unix-like systems (such as Linux, macOS, and BSD).
Think of Docker as a shipping container for your app. Just as a shipping container can hold all sorts of goods (clothes, electronics, etc.) and be transported anywhere, Docker bundles your app and everything it needs to run into a 'container.' This makes it easy to share and run your app on any computer.
Like Docker, there is a tool called Conda, which is showcased in one of the videos above. Conda lets you create separate environments to manage different sets of Python packages, ensuring your code runs the same way on any computer.
Conda and Docker aim to solve the problem of "it works on my machine" by isolating your project and its dependencies.
But the good news is that you have an easy fix. If you are a Windows user, you can use or Dockerize the app to run as a container.
You can download Docker .
You can download Conda .
Now that we have the prerequisites, let's proceed.