JupyChat - Michigan Python
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In this engaging talk, Elijah unravels the process of building a ChatGPT plugin using Python, focusing on utilizing Jupyter and FastAPI. He navigates through the process, illustrating how Jupyter can execute Python code and how FastAPI plays a crucial role in building APIs. Further, he provides an intricate understanding of implementing OAuth with Auth0, underlining its importance in enabling secure user authentication and authorization in the plugin.
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JupyChat - Michigan Python
- 1. 📓 JupyChat Writing a ChatGPT plugin in Python that executes Python Elijah Wilson tizz98
- 2. Me 👋 Elijah (Eli) Wilson Staff Software Engineer & Tech Lead at Noteable.io A person with too many side projects Lives in Brighton, MI tizz98 @elijahwilson@fosstodon.org
- 3. ChatGPT ● Large Language Model ● Built by OpenAI ● Recently added plugin support
- 4. ChatGPT Plugins “Do stuff outside of ChatGPT” ● Wolfram ● Instacart ● OpenTable ● Zillow ● Redfin ● Kayak ● Noteable
- 5. JupyChat plugin ● Authenticate with OAuth using Auth0 ● Execute code using Jupyter ● Show images from results of queries, such as charts
- 6. What goes into a plugin? 1. Authentication 2. OpenAPI specification All of this is defined in a single file for ChatGPT to discover: ai-plugin.json.
- 7. High Level Architecture ● User interacts with ChatGPT ● ChatGPT calls our API using known endpoints from OpenAPI document ● Our FastAPI server creates and runs Jupyter notebooks using ZMQ
- 8. ai-plugin.json Here’s what we have so far… ● offline_access allows for refresh tokens ● openai verification_tokens will be provided by OpenAI after installing the plugin ● is_user_authenticated should be dynamic
- 9. Let’s make it in FastAPI! ⚡️
- 10. Install in ChatGPT ● Select “Plugins” ● Develop your own plugin ● Use ngrok to test OAuth
- 11. Add Auth0 Secrets ● Client ID ● Client Secret
- 12. Post-setup config ● Add the callback URL as an “Allowed Callback URL” in Auth0 ● Update your .env with the new verification token
- 13. Try it out! 😎
- 14. Ethics in AI: Implications for ChatGPT Plugins ● Ethical considerations specific to ChatGPT plugins ● Importance of safeguards in plugin design ● Balancing utility and safety
- 15. Noteable.io Plugin ● Build Jupyter notebooks without running Jupyter ● Execute code and get results back in ChatGPT ● Learn new things! ● Get started at https://app.noteable.io https://www.youtube.com/watch?v=Vmg3gBNCYPw
Notes de l'éditeur
- Ethics play a crucial role in the development and deployment of Artificial Intelligence. It is important to consider and address ethical issues to ensure the responsible use of AI. Key ethical principles in AI include: Transparency: AI systems should be transparent and explainable. Fairness: AI systems should not result in unfair outcomes and should avoid perpetuating biases. Privacy: AI systems should respect the privacy of individuals and handle data responsibly. Accountability: There should be mechanisms for holding AI systems and their operators accountable for their actions. However, there are potential ethical challenges associated with AI, such as: Bias: AI systems can unintentionally perpetuate or even exacerbate existing societal biases. Misuse: There is a risk of AI technologies being used in harmful or malicious ways. Privacy breaches: The use of large datasets can potentially lead to privacy breaches and misuse of personal data.
- When it comes to ChatGPT plugins, there are certain ethical considerations that are particularly relevant. First, it is important to design safeguards into plugins to prevent misuse and harmful actions. For example, there could be risks associated with plugins taking harmful or unintended actions, increasing the capabilities of bad actors, or misusing information sent to the plugin. To mitigate these risks, safeguards need to be implemented in the plugin design from day one1. Balancing utility and safety is also crucial. While plugins can greatly enhance the utility of ChatGPT by giving it access to up-to-date information, enabling it to run computations, or use third-party services, it is important to ensure that these capabilities do not compromise the safety and privacy of users1. Lastly, transparency is key. Users should be able to understand how and when plugins are operating as part of the user experience1.