OpenAI is rolling out its GPT-4 API, and they’re prioritizing access to developers who contribute exceptional model evaluations to OpenAI Evals. OpenAI Evals is a framework that simplifies the evaluation process of large language models (LLMs) and LLM systems, providing users with a comprehensive resource for their evaluation needs.
Evals now supports the evaluation of any system, including prompt chains or tool-using agents, through the Completion Function Protocol. Evals simplifies the construction of an ‘eval’, which refers to a task used to evaluate the quality of a system’s behavior.
Getting started with Evals is straightforward. You’ll need to follow the setup instructions and generate an OpenAI API key. Once you have your key, you can specify it using the environment variable. Be aware of any associated costs when running evals, and note that the minimum required Python version is 3.9.
Although Evals currently isn’t accepting submissions with custom code, you can still submit model-graded evals with custom model-graded YAML files. For those interested in building their own evals, Evals provides a guide to walk you through the process.
By writing your own completion functions, you can customize the way your evals operate, giving you further control over the evaluation process. Evals encourages user contributions, and if you believe you have an interesting eval to share, you can open a Pull Request with your contribution.
Tools like Evals become increasingly important as technology continues to evolve. By understanding how to use such tools, you can significantly enhance your ability to evaluate LLMs and LLM systems, ultimately leading to better, more effective solutions.
For more information on OpenAI Evals, visit the official GitHub project page.
Frequently Asked Questions (FAQs) Related to the Above News
What is OpenAI Evals?
OpenAI Evals is a framework that simplifies the evaluation process of large language models (LLMs) and LLM systems, providing users with a comprehensive resource for their evaluation needs.
How can one get started with Evals?
To get started with Evals, you'll need to follow the setup instructions and generate an OpenAI API key. Once you have your key, you can specify it using the environment variable. Be aware of any associated costs when running evals, and note that the minimum required Python version is 3.9.
What types of systems can be evaluated using Evals?
Evals now supports the evaluation of any system, including prompt chains or tool-using agents, through the Completion Function Protocol.
Can Evals accept submissions with custom code?
Evals currently isn't accepting submissions with custom code, but you can still submit model-graded evals with custom model-graded YAML files.
How can one contribute to Evals?
By writing your own completion functions, you can customize the way your evals operate, giving you further control over the evaluation process. Evals encourages user contributions, and if you believe you have an interesting eval to share, you can open a Pull Request with your contribution.
Why are tools like Evals important?
Tools like Evals become increasingly important as technology continues to evolve. By understanding how to use such tools, you can significantly enhance your ability to evaluate LLMs and LLM systems, ultimately leading to better, more effective solutions.
Please note that the FAQs provided on this page are based on the news article published. While we strive to provide accurate and up-to-date information, it is always recommended to consult relevant authorities or professionals before making any decisions or taking action based on the FAQs or the news article.
