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Evaluating OpenAI Agents #1752

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Summary

This PR adds a guide on evaluating OpenAI agents using Langfuse.

Motivation

This cookbook guides users through the typical evaluation process involved in developing AI agents using the open-source tool Langfuse.

It shows how to perform offline evaluation by looping over a dataset and iterating agent metrics (e.g. model, search tool, etc.) It also explains how to do online evaluation, i.e., assessing metrics like costs and latency in a live production environment.


For new content

When contributing new content, read through our contribution guidelines, and mark the following action items as completed:

  • I have added a new entry in registry.yaml (and, optionally, in authors.yaml) so that my content renders on the cookbook website.
  • I have conducted a self-review of my content based on the contribution guidelines:
    • Relevance: This content is related to building with OpenAI technologies and is useful to others.
    • Uniqueness: I have searched for related examples in the OpenAI Cookbook, and verified that my content offers new insights or unique information compared to existing documentation.
    • Spelling and Grammar: I have checked for spelling or grammatical mistakes.
    • Clarity: I have done a final read-through and verified that my submission is well-organized and easy to understand.
    • Correctness: The information I include is correct and all of my code executes successfully.
    • Completeness: I have explained everything fully, including all necessary references and citations.

We will rate each of these areas on a scale from 1 to 4, and will only accept contributions that score 3 or higher on all areas. Refer to our contribution guidelines for more details.

@jannikmaierhoefer jannikmaierhoefer changed the title Add evaluation cookbook Evaluating OpenAI Agents Mar 31, 2025
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