Chapter 16 · DeepEval Evals Track

Evals: stop eyeballing AI answers, start asserting on them.

End project: your first DeepEval test suite: pack an AI answer into an LLMTestCase, score it with real metrics (relevancy, faithfulness, hallucination) judged by a second LLM, and gate it with a pass/fail threshold inside pytest, kept cheap with tiered model orchestration. Press Play to see why 'looks good to me' finally retires.

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