Seen the OpenAI Dev Day Wanderlust Assistants API demo and wondering how to implement a similar web app in full Python? It's all thanks to the new Assistants API feature and its integrated Function Calling.
In this video, I prototype a Streamlit version of the app. Through this quick overview, you'll learn to:
- leverage Streamlit's Session State for a clean reactive app using an MVC-like pattern
- configure an OpenAI Assistant API 's Function calling feature to have OpenAI talk with your app by mapping user intent to predefined functions
- layout a chatbot and Plotly map through columns and configured by Streamlit secrets
At the end of this video, you will be able to interactively experiment with the new Assistants API through a Streamlit app and have natural language control the flow of your app.
00:00 Intro
00:45 Python App Skeleton
01:55 Configure GPT to generate code?
03:24 Everything in Session State
05:23 Session State is Everything
06:31 GPT-4 Controls Everything
08:28 The Last Stretch
10:21 Easy Peasy
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🔗 Links
- Source Code: https://github.com/andfanilo/social-media-tutorials/tree/master/20231116-st_assistants
- How Language Model Hallucinations Can Snowball: https://arxiv.org/abs/2305.13534
- Someone did ask about open-sourcing the demo: https://community.openai.com/t/openai-devday-demo-repo-access/478895
🔧 My tools (Affiliate links to support me)
- 📕 Streamlit Official Book - https://amzn.to/3QuRPwl
- 📷 Main Camera - https://amzn.to/3QvTosB
- 📷 Main Lens - https://amzn.to/3svYCwq
- 🎙️ Microphone - https://amzn.to/47l5ewA
- 🎵 Music & Sound Effects - https://www.epidemicsound.com/referral/a2p22s
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🪶 I tried my hand at motion graphics & design in this video, and I'm quite happy with the result, plus it was a lot of fun! I hope you liked the small animations too, let me know in the comments I want to keep improving this
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#streamlit #python #datascience #dataapps