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OpenAI Evals - AI Evaluation Tools Tool

Overview

OpenAI Evals is an open-source framework for designing, running, and tracking evaluations of large language models (LLMs) and LLM systems. The project provides a registry of evaluation tasks, reusable test templates, and tooling to run both automated and human-in-the-loop evaluations. It is intended for developers and researchers who need repeatable, extensible assessments of model capabilities, safety behaviors, instruction-following, and other qualitative metrics. The framework supports customizable evaluation logic (runnable as Python code or configurable YAML tests), automated graders (model-based scoring and rubric checks), and human scoring workflows. Results are stored as structured artifacts for analysis and comparison across models, prompts, and dataset slices. According to the GitHub repository, the project is actively maintained with a large community of contributors and frequent commits, making it suitable for teams that want an extensible, production-capable evaluation pipeline.

GitHub Statistics

  • Stars: 17,526
  • Forks: 2,859
  • Contributors: 435
  • License: NOASSERTION
  • Primary Language: Python
  • Last Updated: 2025-11-03T21:36:50Z

According to the GitHub repository, OpenAI Evals has 17,526 stars, 2,859 forks, and 435 contributors, indicating strong community interest and broad contributor involvement. The repo shows active development (last commit noted 2025-11-03T21:36:50Z). The repository metadata lists License: NOASSERTION. The volume of contributors and forks suggests robust community-driven extensions, while the star count reflects wide adoption and visibility in the model-evaluation ecosystem.

Installation

Install via pip:

pip install openai-evals
git clone https://github.com/openai/evals.git && cd evals && pip install -e .

Key Features

  • Registry of reusable evaluation tasks and templates for sharing and reuse
  • Support for automated model-based grading and rubric-driven scoring
  • Human-in-the-loop evaluation workflows and interfaces for annotators
  • Extensible adapters to call OpenAI API and other model providers
  • Structured result artifacts for longitudinal comparisons and reporting
  • Configurable sampling, seeds, and parallel execution for reproducibility
  • Ability to write custom checks and metrics in Python or declarative configs

Community

OpenAI Evals has a large, active community—17,526 GitHub stars, 2,859 forks, and 435 contributors. The project receives frequent commits and community PRs, with active issue and discussion threads for new evals, integrations, and tooling.

Last Refreshed: 2026-01-09

Key Information

  • Category: Evaluation Tools
  • Type: AI Evaluation Tools Tool
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