Evaluating LLM Apps in Python
📰 Dev.to · Puneet Gupta
Learn to evaluate LLM apps in Python for better quality control and automation
Action Steps
- Build a golden eval dataset for testing LLMs
- Run programmatic assertions to score LLM performance
- Configure LLM-as-judge for evaluation
- Test regression tests and integrate with CI/CD pipelines
- Apply quality checks to prevent prompt or model changes from hurting performance
Who Needs to Know This
Developers and data scientists working with LLMs can benefit from this to ensure high-quality models and automate testing
Key Insight
💡 Use golden eval datasets and programmatic assertions to automate LLM evaluation and ensure high-quality models
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Automate LLM evaluation with Python! 🚀
Key Takeaways
Learn to evaluate LLM apps in Python for better quality control and automation
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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