The video demonstrates how to create dynamic web components using OpenAI’s new structured outputs feature, highlighting its advantages over the previous JSON mode, such as guaranteed schema adherence and cost-effectiveness. The presenter showcases various generated components, emphasizes the importance of defining complex schemas, and encourages viewers to explore additional resources and join the Patreon community for further learning.
In this video, the presenter demonstrates how to create a dynamic component generator using the new structured outputs feature from the OpenAI API. The session begins with a simple example of a generated component, followed by a more complex card design that includes six segments, each with image placeholders. The presenter also showcases the generation of a simple form and discusses the implementation of dark and light modes. Throughout the video, the focus is on utilizing structured outputs to enhance the reliability and consistency of the generated components.
The video explains the concept of structured outputs, highlighting its advantages over the previous JSON mode. While JSON mode provided a valid JSON structure, it lacked guaranteed schema adherence. The presenter notes that the new structured outputs achieve 100% adherence to the specified schema, making it comparable to function calling in terms of reliability. Additionally, the latest model supports outputs of up to 16,000 tokens and is 50% cheaper for input tokens, making it a cost-effective solution for developers.
The presenter then dives into the practical application of structured outputs by generating various components, including a colorful customer feedback card and a gallery with navigation arrows. The generated components are returned in structured JSON format, which can be easily parsed and displayed as HTML. The video also introduces an “autocoder” feature that allows users to create Python applications through iterative prompts, demonstrating how the model can improve and convert code across different programming languages.
The video emphasizes the importance of defining complex schemas when using structured outputs, recommending the use of the Pydantic SDK for schema definition. The presenter illustrates how to set up a math reasoning task, where the model provides step-by-step solutions, and how to handle refusals programmatically within the JSON object. This structured approach simplifies the prompting process and enhances the overall user experience when interacting with the API.
Finally, the presenter discusses the benefits of becoming a patron, which includes access to code files, courses, and one-on-one consulting opportunities. The video concludes with a brief overview of the documentation for structured outputs, highlighting its capabilities for UI generation, data extraction, and moderation. The presenter encourages viewers to explore the resources available on their website and consider joining the Patreon community for further learning and collaboration. Download the full Project files for this project at my Patreon along with 250+ other projects: https://www.patreon.com/posts/generate-web-new-109662046