Conversational AI, especially ChatGPT, has become extremely popular over the past year. By January 2023, ChatGPT was the fastest-growing consumer software application in history. While many are familiar with and frequently use its web interface, we will explore its API (Application Programming Interface).
The API access allows you to interact with ChatGPT in a Jupyter Notebook or any other coding environment. It radically speeds up the development and deployment of many natural language processing tasks such as text summarization, sentiment analysis, topic modeling, and text transformations (such as translation, grammar correction, and style adjustments), and chatbot development. I will show you how to perform some of these tasks during the seminar.
I hope that by the end, participants will be well-equipped to start innovating with ChatGPT and develop their own applications.
I assume participants have basic Python knowledge and know how to work with containers (such as lists and dictionaries), control flow (like for loops and if statements), and functions.
Please run test_environment.ipynb. It checks the versions of your python and some packages (like pandas, openai). If the notebook returns all OK, you should be able to run the code without issues. If some FAILs are returned, you need to install/update those packages first.
You can recreate the python environment using the odsc-chatgpt.yml conda environment file by running these two commands in the terminal:
conda env create -n odsc-chatgpt -f odsc-chatgpt.yml
conda activate odsc-chatgpt
You should be able to run src/ODSC - ChatGPT API.ipynb now.
You will need an API key to query ChatGPT. Follow the instructions here to obtain one. Note that the API access is not free, check out pricing here. For reference, it costs me maybe $0.05 to develop and test the code for this presentation.
Andras Zsom ([email protected])
This project is licensed under the MIT License.