September 2026
Intermediate
216 pages
5h 33m
English
Content preview from AI Evals in Practice
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Chapter 15 — Final Project: Complete Evalkit with CI and Dashboard
We have arrived. Over fourteen chapters, you have built evalkit from a single type definition to a comprehensive evaluation system with datasets, scorers, runners, regression detection, RAG metrics, agent evaluation, human annotation, production monitoring, cost tracking, and integration bridges. In this final chapter, we assemble everything into a production-ready package.
You will build three things: the complete evalkit package with a clean public API, a CI pipeline that runs evaluations on every pull request, and a reporting dashboard that visualizes quality trends over time. By the end, you will have a system you can deploy on your own LLM projects immediately.
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