Understanding StreamLit State (10.3)

This video delves into managing state in Streamlit applications for generative AI. It explains how to maintain user inputs and application state across interactions, enabling more complex and dynamic AI applications. Through practical examples, the video demonstrates the use of session state in Streamlit to track data, user selections, and model outputs, showcasing how to build interactive and responsive AI-driven web apps with Python. Code for This Video: https://github.com/jeffheaton/app_generative_ai/blob/main/t81_559_class_10_3_streamlit_state.ipynb ~~~~~~~~~~~~~~~ COURSE MATERIAL ~~~~~~~~~~~~~~~ 📖 Textbook - Coming soon 😸🐙 GitHub - https://github.com/jeffheaton/app_generative_ai ▶️ Play List - https://www.youtube.com/watch?v=FBmUxUt__rM&list=PLjy4p-07OYzui0nVZzMgoLBeXjG9Oy3hi&ab_channel=JeffHeaton ~~~~~~~~~~~~~~~ CONNECT ~~~~~~~~~~~~~~~ 🖥️ Website: https://www.heatonresearch.com/ 🐦 Twitter - https://twitter.com/jeffheaton 😸🐙 GitHub - https://github.com/jeffheaton 📸 Instagram - https://www.instagram.com/jeffheatondotcom/ 🦾 Discord: https://discord.gg/3bjthYv ▶️ Subscribe: https://www.youtube.com/c/heatonresearch?sub_confirmation=1 ~~~~~~~~~~~~~~ SUPPORT ME 🙏~~~~~~~~~~~~~~ 🅿 Patreon - https://www.patreon.com/jeffheaton 🙏 Other Ways to Support (some free) - https://www.heatonresearch.com/support.html ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ #Streamlit #GenerativeAI #Python #AIApplications #WebApps #SessionState #MachineLearning #AI #DataScience #InteractiveApps #PythonProgramming #T81559 #WebDevelopment