fix(gooddata-eval): compare attribute-filter elements as a set, not a sequence - #1806
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fix(gooddata-eval): compare attribute-filter elements as a set, not a sequence#1806Tomkess wants to merge 2 commits into
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… sequence An attribute filter selecting exactly the same elements scored as a mismatch when the agent emitted them in a different order than the fixture listed them. _split_and_normalize_filters serialises each normalised filter with json.dumps(..., sort_keys=True). That orders the dict KEYS -- field_uri, state, type -- and never descends into the list under state["include"], so the two serialisations differed and check_filters compared them with ==. `include`/`exclude` name a SET of elements. An agent has no reason to keep their order stable between runs, so any question needing a multi-element attribute filter passed or failed partly at random -- non-determinism inside scoring, reported as `filters_correct: false` and indistinguishable from the agent genuinely filtering wrongly. Found on what-is-cross-border-approval-rate-in-the (micai_diagnose_master, gpt-5.2): metrics and dimensions correct, filters_correct false, with expected ["Inter-region", "Intra-region"] against actual ["Intra-region", "Inter-region"]. Both select every non-Domestic, non-Unknown row. Sorting during normalisation rather than comparing as sets keeps the canonical JSON string that normalized_filters reports for debugging, and keeps both sides in one place. `key=str` because a mixed-type list would raise TypeError from inside scoring, which is worse than the mismatch this fixes; malformed filter values are reported by validate_cross_references separately. The other two normalisers were checked and are unaffected: _normalize_ranking_filter and _normalize_date_filter emit only scalars, so state's element lists are the only ordered value in filter normalisation. Multiple attribute filters already compared order-insensitively, since _split_and_normalize_filters collects entries into a set -- the set was right, the list inside each member was not. 7 tests, 6 of which fail against the previous version; the 7th is the negative control that a genuinely different element set still fails. 921 passed, lint and format clean. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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📝 WalkthroughWalkthroughAttribute filter normalization now sorts list-valued state entries before scoring. Tests cover permutations, distinct values, state keys, labels, and mixed-type values. ChangesAttribute filter scoring
Estimated code review effort: 2 (Simple) | ~10 minutes Merge Risk: 🟡 Moderate · up to Some mixed-type attribute filters can still receive different scores solely because their values are ordered differently. The sorting logic and a regression test for this case should be corrected before merging. 🚥 Pre-merge checks | ✅ 4 | ❌ 1❌ Failed checks (1 warning)
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I sort the filters, soft and neat Comment |
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In `@packages/gooddata-eval/src/gooddata_eval/core/scoring.py`:
- Line 178: Update the state normalization around raw_state so list sorting uses
a canonical JSON key that distinguishes values by type, ensuring permutations
such as [1, "1"] and ["1", 1] normalize identically. Preserve the existing
filtering and non-list values, and add a regression test covering this
mixed-type ordering case.
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Review finding, and correct. `key=str` maps 1 and "1" to the same key, so Python's stable sort leaves THEIR relative order exactly as the agent emitted it -- and the ordering bug this PR fixes survives for that one pair. [1, "1"] and ["1", 1] still serialised differently and still scored as different filters. The key is now the element's own canonical JSON. That keeps what str() was chosen for -- a mixed-type list must not raise TypeError from inside scoring -- while distinguishing the types the comparison downstream also distinguishes. Safe here because these values are always parsed JSON, so json.dumps cannot fail on them; that provenance is what makes it a total ordering. Two tests: the type-collision pair now compares equal without making 1 and "1" interchangeable as element sets, and a heterogeneous list sorts without raising. The first fails against key=str. 923 passed, lint and format clean. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
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The bug
An attribute filter selecting exactly the same elements scores as a mismatch when the agent emits them in a different order than the fixture lists them.
_split_and_normalize_filtersserialises each normalised filter withjson.dumps(..., sort_keys=True). That orders the dict keys —field_uri,state,type— and never descends into the list understate["include"]. So the two serialisations differ andcheck_filterscompares them with==.Reproducible with no workspace and no network:
attribute_okbeforeincludeidentical orderincludereversedinclude3 shuffledexcludereversedWhy it matters
include/excludename a set of elements. An agent has no reason to keep their order stable between runs, so any question needing a multi-element attribute filter passed or failed partly at random — non-determinism inside scoring, reported asfilters_correct: falseand indistinguishable from the agent genuinely filtering wrongly.Found on
what-is-cross-border-approval-rate-in-the(micai_diagnose_master, gpt-5.2): metrics and dimensions correct,filters_correctfalse, expected["Inter-region", "Intra-region"]against actual["Intra-region", "Inter-region"]. Both select every non-Domestic, non-Unknown row — confirmed against the live workspace, wherecross_border_namehas exactly Domestic / Inter-region / Intra-region / Unknown.It also silently taxed the alternatives mechanism: admitting an order-insensitive answer via fixture candidates needs one per permutation — 2 for two elements, 6 for three.
The fix
Sort the element lists during normalisation. Sorting rather than comparing as sets keeps the canonical JSON string
normalized_filtersreports for debugging, and keeps both sides in one place.key=strrather than a baresorted(): a mixed-type list (["A", 2]) would raiseTypeErrorfrom inside scoring, which is worse than the mismatch this fixes.validate_cross_referencesalready reports malformed filter values separately, so this only has to stay comparable.Scope — the adjacent normalisers are clean
Checked rather than assumed:
_normalize_ranking_filteremits{dim_uri, metric_uri, top, type}— all scalars._normalize_date_filteremits{dataset_uri, from, to, type}— all scalars.So
state's element lists are the only ordered value in filter normalisation.Worth noting the contrast: multiple attribute filters already compared order-insensitively, because
_split_and_normalize_filterscollects entries into aset. The set was right; the list inside each member was not. That makes this a one-line change with no structural risk.Tests
7 added. 6 fail against the previous version; the 7th is the negative control. They pin the boundaries a "sort it" fix could plausibly break:
includeof the same elements still differs fromexcludeof them921 passed, lint and format clean.
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