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Streamlit for Data Science

You're reading from   Streamlit for Data Science Create interactive data apps in Python

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Product type Paperback
Published in Sep 2023
Publisher Packt
ISBN-13 9781803248226
Length 300 pages
Edition 2nd Edition
Languages
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Author (1):
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Tyler Richards Tyler Richards
Author Profile Icon Tyler Richards
Tyler Richards
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Table of Contents (15) Chapters Close

Preface 1. An Introduction to Streamlit 2. Uploading, Downloading, and Manipulating Data FREE CHAPTER 3. Data Visualization 4. Machine Learning and AI with Streamlit 5. Deploying Streamlit with Streamlit Community Cloud 6. Beautifying Streamlit Apps 7. Exploring Streamlit Components 8. Deploying Streamlit Apps with Hugging Face and Heroku 9. Connecting to Databases 10. Improving Job Applications with Streamlit 11. The Data Project – Prototyping Projects in Streamlit 12. Streamlit Power Users 13. Other Books You May Enjoy
14. Index

Integrating external AI libraries – an OpenAI example

2023 has surely been the year of generative AI, with ChatGPT taking the world and developer community by storm. The availability of generative models behind services like ChatGPT has also exploded, with each of the largest technology companies coming out with their own versions (https://ai.meta.com/llama/ from Meta and https://bard.google.com/ from Google, for example). The most popular series of these generative models is OpenAI’s GPT (Generative Pre-trained Transformer). This section will show you how to use the OpenAI API to add generative AI to your Streamlit apps!

Authenticating with OpenAI

Our first step is to make an OpenAI account and get an API key. To do this, head over to https://platform.openai.com and create an account. Once you have created an account, go to the API keys section (https://platform.openai.com/account/api-keys) and press the button Create new secret key. Once you create the key...

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