Source URL: https://simonwillison.net/2024/Dec/22/openai-openapi/#atom-everything
Source: Simon Willison’s Weblog
Title: openai/openai-openapi
Feedly Summary: openai/openai-openapi
Seeing as the LLM world has semi-standardized on imitating OpenAI’s API format for a whole host of different tools, it’s useful to note that OpenAI themselves maintain a dedicated repository for a OpenAPI YAML representation of their current API.
(I get OpenAI and OpenAPI typo-confused all the time, so openai-openapi is a delightfully fiddly repository name.)
The openapi.yaml file itself is over 26,000 lines long, defining 76 API endpoints (“paths" in OpenAPI terminology) and 284 "schemas" for JSON that can be sent to and from those endpoints. A much more interesting view onto it is the commit history for that file, showing details of when each different API feature was released.
Browsing 26,000 lines of YAML isn’t pleasant, so I got Claude to build me a rudimentary YAML expand/hide exploration tool. Here’s that tool running against the OpenAI schema, loaded directly from GitHub via a CORS-enabled fetch() call: https://tools.simonwillison.net/yaml-explorer#.eyJ1c… – the code after that fragment is a base64-encoded JSON for the current state of the tool (mostly Claude’s idea).
Tags: claude-3-5-sonnet, ai-assisted-programming, generative-ai, openai, apis, ai, llms
AI Summary and Description: Yes
Summary: The text discusses OpenAI’s maintenance of an OpenAPI repository that defines a substantial number of API endpoints and schemas, highlighting the growing standardization around OpenAI’s API format in the LLM ecosystem. It also mentions the use of AI to develop a tool to manage the complexity of navigating this extensive API schema.
Detailed Description:
The content is particularly relevant for professionals in the fields of AI and API integration, showcasing the ongoing evolution and standardization of AI API formats. Here are the key aspects:
– **OpenAPI Repository**: OpenAI maintains a dedicated repository for its OpenAPI YAML definition, which is indicative of their commitment to transparency and ease of use for developers interfacing with their models.
– **API Specifications**: The repository contains an extensive `openapi.yaml` file that:
– Exceeds 26,000 lines of code.
– Defines 76 API endpoints, termed “paths” in OpenAPI jargon.
– Includes 284 “schemas” for JSON messages that can be exchanged with these endpoints.
– **Historical Insights**: The commit history of the `openapi.yaml` file provides valuable insights into the release timeline of different API features, reflecting the evolution of OpenAI’s offerings.
– **YAML Exploration Tool**: To improve usability in navigating this complex schema, a rudimentary tool was developed using Claude’s capabilities. This tool serves as a practical solution for developers who may find it cumbersome to manage extensive YAML files.
– **Standardization in LLM Development**: The mention of the standardization trend among various tools imitating OpenAI’s API format underscores the influence of OpenAI in the LLM and generative AI arenas.
– **Practical Implications**: For developers and professionals focused on AI integration and security, this information highlights:
– The importance of understanding API specifications and the potential compliance issues related to how data is handled across services.
– The innovative use of AI to enhance tool usability, which could inspire additional development in the field of API management.
Overall, the text illustrates a critical aspect of ongoing developments in AI technology, emphasizing standardization, usability, and the evolving nature of API interactions.