OpenAI has recently open-sourced a collection of sample applications that demonstrate their Structured Outputs feature, providing developers with tools to build more reliable applications using their language models. The repository, available on GitHub, contains several sample apps demonstrating practical ways to leverage Structured Outputs in NextJS applications.
The Structured Outputs feature ensures that responses and tool calls adhere to a defined JSON schema, bridging the gap between unpredictable model outputs and deterministic workflows. This improvement in reliability is essential for developers utilising OpenAI’s advanced language models.
The sample apps cover a range of use cases, from simple examples to more complex implementations. One app focuses on resume extraction and demonstrates how to display information in a structured format.
Another app explores generative UI, showcasing the dynamic generation of UI components using Structured Outputs. The most complex example is a conversational assistant that combines multi-turn conversations, tool calling, and generative UI.
“Each app demonstrates practical ways to leverage this feature to build applications with NextJS,” said team OpenAI. The company believes that this provides developers with valuable resources to explore and adapt for their own projects.
To get started, the team said that developers can clone the repository, set up the OpenAI API, and follow the README instructions for each sample app. OpenAI also provided additional resources, including documentation on Structured Outputs and Function Calling, as well as an introductory cookbook for hands-on experience with code snippets in Python.
While OpenAI welcomes contributions to improve the sample apps, they note that not all suggestions may be reviewed. The project is licensed under the MIT License, allowing developers significant freedom in using and modifying the code for their own purposes.
OpenAI came up with the update featuring Structured Outputs in its API last year, which claims to enhance the model’s reasoning by ensuring precise and consistent adherence to output schemas. This was demonstrated by GPT-4o-2024-08-06, achieving ‘100% reliability’ in evaluations, perfectly matching the output schemas, and ensuring accurate and consistent data generation.
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