Giskard Hub: scenarios plus checks, LLM-judge or embedding or rule-based
Giskard Hub: scenarios plus checks, LLM-judge or embedding or rule-based: In Giskard Hub, build datasets of scenarios with explicit checks, choosing LLM-judge, embedding, or rule-based criteria per scenario.
In Giskard Hub, build datasets of scenarios with explicit checks, choosing LLM-judge, embedding, or rule-based criteria per scenario. Reference built-in checks by identifier and params, and wait for evaluation completion before reading results.
Context: Official Giskard docs (Hub SDK quickstart): documents the evaluation building blocks. A dataset is a collection of scenarios with expected outcomes and checks. Each scenario's checks field controls the criteria applied to the agent response, and checks can be LLM-judge, embedding similarity, or rule-based, referenced by identifiers like hub_correctness with params. Evaluations send every scenario to your agent and score the responses; use the wait helper to block until completion.
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Source: Published skill Original query: "Giskard Hub: scenarios plus checks, LLM-judge or embedding or rule-based" Key terms: based, checks, embedding, giskard, judge, plus, rule, scenarios
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