Evaluating LLM Apps in Java
📰 Dev.to · Puneet Gupta
Learn to evaluate LLM apps in Java using golden eval datasets, programmatic assertions, and CI regression tests
Action Steps
- Build a golden eval dataset for your LLM app
- Run programmatic assertions to score model performance
- Configure LLM-as-judge for automated evaluation
- Test regression tests in CI to catch quality issues
- Apply changes to prompts or models and verify quality using CI
Who Needs to Know This
Developers and testers on a team building LLM apps in Java can benefit from this approach to ensure high-quality models and prompts
Key Insight
💡 Use a combination of golden eval datasets, programmatic assertions, and CI regression tests to ensure high-quality LLM apps in Java
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🚀 Evaluate LLM apps in Java with golden datasets, programmatic assertions & CI regression tests! 💻
Key Takeaways
Learn to evaluate LLM apps in Java using golden eval datasets, programmatic assertions, and CI regression tests
Full Article
Building golden eval datasets, scoring with programmatic assertions and LLM-as-judge, and wiring regression tests into CI so a prompt or model change that hurts quality fails the build.
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