Trial Ragas metrics against a small human-reviewed fixture

Choose one metric question at a time

Ragas documents faithfulness and several context-precision variants. Select the exact variant and required fields for the evaluation question. Faithfulness concerns support from supplied context; a context-precision variant may depend on reference information or a judge in a different way. Record metric class, package version, model configuration, and inputs. Do not silently swap reference-dependent and reference-free variants and compare their scores as though only the application changed.

Evidence: Faithfulness metric [1]Context Precision [2]

Build four authored edge cases

Create a correct answer supported by context, a supported answer drawn from an obsolete policy, an unsupported claim beside relevant context, and a missing required exception. The expected diagnostic behavior differs across these cases. A context-support metric may accept the obsolete-policy answer even though product acceptance rejects it. That disagreement is useful evidence about metric scope, not necessarily a software defect. Preserve the full passages and authored answer snapshots instead of generating fresh answers during this first scoring-only trial.

Inspect extracted claims and relevance decisions

Run the chosen metrics on fixed inputs and retain case-level reasons and any observable intermediate judgments. Compare them with the local labels. If a compound claim is split differently, inspect how that changes the denominator. Check negation, numerical qualifiers, and source applicability with human-owned acceptance criteria. An apparently precise decimal score should not hide an unexplained claim extraction or context-labeling error. Keep timeouts and evaluation errors in the record rather than averaging only completed scores.

Separate scorer testing from application testing

First establish what the metric does on authored answer snapshots. Then connect the actual RAG application and generate fresh outputs on a held-out set. Preserve model and retrieval configuration so changes in answers are not mistaken for changes in the metric. Count application calls and judge calls separately when measuring cost. A successful local metric execution does not establish the data-retention, hosted-reporting, or endpoint behavior of every possible configuration; verify the actual data path used in your trial.

Decide where the metric can influence release

Use the trial to identify which failures the score reliably surfaces and which require deterministic checks or direct review. A proposed gate should preserve critical case-level failures even when the average improves. Keep fixture IDs, package versions, raw outputs, scoring reasons, and unresolved disagreements portable. If the metric’s scope does not match the release question, retain it as a diagnostic signal instead of promoting it into an unexplained pass/fail authority for the entire application. Keep one fixture where the correct response declines an unsupported question. A metric selected for ordinary answers may need a separately defined interpretation for justified abstention.

Common questions