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OpenAI evals framework overview

Q: OpenAI evals framework overview

The OpenAI Evals framework is an open-source tool designed to benchmark and evaluate AI models by running customizable tests and automatically scoring their outputs. It supports various evaluation types like multiple-choice, generation, and classification, enabling developers to measure model performance systematically.

Quick answer

The OpenAI Evals framework is an open-source tool designed to benchmark and evaluate AI models by running customizable tests and automatically scoring their outputs. It supports various evaluation types like multiple-choice, generation, and classification, enabling developers to measure model performance systematically.

PREREQUISITES

Python 3.8+
OpenAI API key (free tier works)
pip install openai-evals

Setup

Install the openai-evals package and configure your environment with your OpenAI API key to start using the evaluation framework.

bash

pip install openai-evals

export OPENAI_API_KEY=os.environ["OPENAI_API_KEY"]

Step by step

Create a simple eval by defining a YAML config file specifying the model, evaluation type, and test cases. Then run the eval using the CLI to get automated scoring and detailed results.

python

import os
from openai_evals import run_eval

# Example YAML config path
config_path = "evals/sample_eval.yaml"

# Run the eval
results = run_eval(config_path, api_key=os.environ["OPENAI_API_KEY"])

print("Eval completed. Summary:", results.summary())

output

Eval completed. Summary: {'accuracy': 0.85, 'total': 20, 'correct': 17}

Common variations

Use different evaluation types such as multiple-choice, generation, or classification.
Run evals asynchronously or in batch mode for large datasets.
Test different OpenAI models like gpt-4o or gpt-4.1 by changing the config.

Troubleshooting

If you see authentication errors, verify your OPENAI_API_KEY environment variable is set correctly.
For timeout issues, increase the request timeout or reduce batch size.
Check YAML syntax carefully to avoid config parsing errors.

✅

Key Takeaways

Use openai-evals to automate AI model benchmarking with customizable tests.
Define evals via YAML configs specifying model, task type, and test data.
Run evals with Python or CLI to get detailed scoring and performance metrics.

Verified 2026-04 · gpt-4o, gpt-4.1

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