OpenAQ is a small team working on a relatively large and complex codebase. The OpenAQ platform serves millions of requests daily and provides essential access to air quality data. The platform’s reliability and long term viability is central to our mission of providing universal access to air quality data. Intentional and carefully written code makes the OpenAQ platform successful and sustainable.
When contributing code to any of the OpenAQ open-source projects, contributors must disclose any use of LLMs. Disclosing the use of LLMs in code contributions will help provide important context for the review process. As part of the review of contributions it is important that contributors have a clear understanding of the code they contribute. Code written by LLMs may obscure the contributor’s understanding and intentions and in turn make contributions harder to review and assess. Contributions wholly written using an LLM are unlikely to be accepted, but may be reviewed on a case-by-case basis.