- Notebook, not table, with a minimum of 4 CPUs and 8 GB of memory
- Python 3.11 installed on your notebook and a Python package manager like Conda or virtual environment.
- An IDE or code editor of your choice with Python syntax highlighting and LSP support. The workshop will be conducted using Visual Studio Code (VSC). If you are using Visual Studio Code install the following extension
- You should also have Git installed
- ALTERNATIVE - If you are familiar with DevContainers and would like to use it for this workshop, please install the following:
Create an OpenAI account. After your account has been created, you will now need to add USD$5 your account. Click on the gear icon on the top menu bar. This will bring you to the Settings page. From the left menu bar, click on Billing. The Billing page is shown below.
Click on Add to credit balance which brings up the Add to credit balance dialog box. Add your payment method and enter a minimum of USD$5. Once you have confirmed the payment, the billing page will display the amount you have entered.
Click on Dashboard on the top menu bar. Click on API keys to create a new secret key as shown below.
After you have generated your key, keep a copy of the key. You will not be able to view the key again once you dismissed the dialog.
This is a template repository. Clone it to create your own repository based on this template.
You will now need to select ONE of the following methods for running the workshop; either directly on your notebook or in a container.
If you are running the workshop locally, then perform step [2.1] Notebook Setup; otherwise setup according to [2.3] DevContainer Setup. The advantage of running in a container is that there are no Python installation on your notebook.
Open a terminal and to create and activate your environment, eg. for Conda,
conda create geekshacking-workshop
conda activate geekshacking-workshop
Once the environment has been activated, install the packages from the requirements.txt file eg.
pip install -r requirements.txt
Depending on your notebook and your network throughput, this can be anywhere from 5 to 20 minutes.
After you have successfully installed all the packages, test your environment. Open a terminal, if you have not done so. For Windows user, use the cmd rather than PowerShell.
Set the environment variable OPENAI_API_KEY to your OpenAI key that you have generated in step [1.2].
For Windows (case sensitive)
set OPENAI_API_KEY=_secret_key_
For Linux and OSX (case sensitive)
export OPENAI_API_KEY='_secret_key_'
After setting the keys, change directory into 0_test_setup directory and run main.py.
## Linux and OSX
export OPENAI_API_KEY='_secret_key_'
## Windows
set OPENAI_API_KEY=_secret_key_
cd 0_test_setup
python main.py
If you see the following output, the you have successfully setup your environment.
If you are using DevContainer, then open this repository in VSC after install all the required pre-requisites from step [0]. VSC will setup the Python environment and installed all the required packages. This can take about 5 to 20 minutes.
Open a terminal from within VSC, choose cmd for Windows, and perform the OpenAI test as described in step [2.2] above.
