fix(intrinsics): restore aLoRA offsets and fix groundedness parser#1292
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ajbozarth
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I missed that you marked this draft again, but heres a quick first pass review from Claude
The model frequently mirrors the input span structure from the prompt and nests support_level inside a 'citations' array instead of the flat format specified in the instructions. The parser only handled the flat path, causing correct LLM judgments to be silently downgraded to NOT_SUPPORTED. Also improve the prompt to add explicit flat-format example to reduce structure confusion. Verified on HPC: granite-4.0-micro e2e test 10/10 passes (was 5/10). See issue #1291 for deep analysis. Assisted-by: opencode Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
The HF adapter io.yaml is missing max_completion_tokens, causing transformers to fall back to max_length=153. The model sometimes generates extra fields beyond the required JSON and gets truncated mid-string, producing a JSONDecodeError in result_processor.transform(). Also clean up the stale TODO comment in the context_relevance branch. See issue #1301 for full analysis and upstream fix decision. Assisted-by: Claude Code Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
…te aLoRA offsets generate_with_transformers() used inputs= instead of input_ids= when calling model.generate(), causing pefts aLoRA hook to silently fall back to standard LoRA. This affected context_relevance and uncertainty intrinsics which produce wrong or truncated output without aLoRA. Closes #1286 Assisted-by: opencode Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
…mples Replace first-wins break in nested-citations fallback with a pessimistic aggregate (NOT_SUPPORTED > PARTIALLY_SUPPORTED > FULLY_SUPPORTED) so the result is deterministic regardless of citation order from the LLM. Drop literal placeholder syntax (`, ...` and `...` values) from the two GroundednessRequirement prompt examples; granite-4.0-micro sometimes echoes placeholder text verbatim, producing unparseable output. Clarify context-attribution test comment: extras in actual are intentionally tolerated, not an oversight. Closes #1286 Assisted-by: Claude Code Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
CI status noteThe Tracked in #1272. |
ajbozarth
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Three previous comments addressed cleanly — pessimistic aggregate is the right call. Two new findings on the latest commits: one reliability bug and one test-coverage gap.
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I think that review above is valid, Claude went off the rails when I asked it to re-review and posted that without my permission and without even telling me its findings. |
When an LLM emits `"citations": null`, `judgment.get("citations", [])`
returns `None` (the default only applies when the key is absent). The
set comprehension then raises `TypeError`, which the surrounding
`except (JSONDecodeError, ValueError)` does not catch — propagating
out of the parser instead of falling to the conservative NOT_SUPPORTED
default.
Fix by using `(judgment.get("citations") or [])` so an explicit null
is treated the same as an absent key.
Also adds a unit test for the pessimistic-aggregate path (NOT_SUPPORTED
beats PARTIALLY_SUPPORTED beats FULLY_SUPPORTED across mixed nested
citations on a single span) that was missing from the previous commit.
Closes review comment from ajbozarth on PR generative-computing#1292.
Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
Assisted-by: Claude Code
psschwei
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Reviewed the intrinsics fixes. The two production changes (aLoRA input_ids= and the nested-citation parser) are correct and root-caused — I verified the aLoRA diagnosis against PEFT's get_alora_offsets_for_generate, which silently disables aLoRA when input_ids is absent from kwargs. Leaving three non-blocking suggestions inline, each with a proposed fix. Note the rag.py and test-variant suggestions are paired: the new space-variant assertion fails until the parser normalizes nested labels.
ajbozarth
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Heads up — 4b649f4 looks right (both fixes are exactly what we asked for), but its
parent is 2178bf1, not 71b5611. So it sits on a branch off main rather than on
issue-1291. The PR head is still 71b5611 and both findings still apply on what GitHub
shows.
To land it: git cherry-pick 4b649f42 onto issue-1291 and push (force-push needed since
the existing 71b5611 is what's on remote).
Once that is fixed I think this will LGTM
Pull request was converted to draft
jakelorocco
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approving; nothing here actually needs my review; I will defer to other reviewers. I'll add the do-not-merge label so that others can re-review their suggested changes
When an LLM emits `"citations": null`, `judgment.get("citations", [])`
returns `None` (the default only applies when the key is absent). The
set comprehension then raises `TypeError`, which the surrounding
`except (JSONDecodeError, ValueError)` does not catch — propagating
out of the parser instead of falling to the conservative NOT_SUPPORTED
default.
Fix by using `(judgment.get("citations") or [])` so an explicit null
is treated the same as an absent key.
Also adds a unit test for the pessimistic-aggregate path (NOT_SUPPORTED
beats PARTIALLY_SUPPORTED beats FULLY_SUPPORTED across mixed nested
citations on a single span) that was missing from the previous commit.
Closes review comment from ajbozarth on PR #1292.
Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
Assisted-by: Claude Code
- Add _norm() helper (hoisted before judgment loop) to normalise nested citation labels through the same substring logic the flat path uses, so near-miss labels like "FULLY SUPPORTED" (space) no longer silently downgrade to NOT_SUPPORTED. - Add test_parse_batch_support_output_nested_multiple_citations: exercises the pessimistic-aggregation loop with mixed levels and empty citations []. - Add test_parse_batch_support_output_nested_label_variants: regression guard for space-variant label normalisation; would fail without _norm(). - Replace bare `continue` with pytest.xfail for context_relevance (non-alora) so the case surfaces in the report rather than passing silently. - Fix requirement_check direction threshold: >= 0.5 → > 0.5 to match requirement_check_to_bool() at requirements/requirement.py:52. - Correct uncertainty comment: production check_certainty() returns the raw float; the >= 0.5 bucket is test-only tolerance, not a production mirror. - Restore "with one object for each span" count guidance to the support-batch prompt (accidentally dropped when concrete example was added; necessity prompt already has it). Closes review threads from psschwei on PR #1292. Assisted-by: Claude Code Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
_key() previously matched records on span offsets only. A record pointing to the right span but the wrong source document would pass silently. The existing comment limits the stated non-determinism to count — how many spans get attributed — not to which document a matched span points to. A doc_id mismatch on a present record is therefore a real regression, not tolerable hardware variance. Assisted-by: Claude Code Signed-off-by: Nigel Jones <jonesn@uk.ibm.com>
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@ajbozarth — thanks for catching the branch issue. The cherry-pick is in place: 4b649f4 landed on |
- uncertainty f-string: ">0.5?" → ">=0.5?" to match the actual >= comparison above - context_relevance branch: substring "in" → exact "==" to decouple from the early alora xfail above it; mirrors how context-attribution already uses == Signed-off-by: Nigel Jones <jonesn@uk.ibm.com> Assisted-by: Claude Code
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Intermittent CI failure — not caused by this PR The `code-checks / quality (3.11)` job failed on run 28017020057 with: This test was not touched in this branch. It fails when Ollama is under load late in the CI run (the model gets evicted by `OLLAMA_KEEP_ALIVE=5m` and reload exceeds the 300 s timeout introduced by PR #1302). The root cause and fix are tracked in issue #1318. Retriggering CI. |
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@ajbozarth One for you to check. thanks |
ajbozarth
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LGTM, thanks for addressing all the review
Pull Request
Issue
Fixes #1291
Fixes #1286
Description
Four issues causing intrinsic tests to fail on GPU hardware, fixed in one PR:
model.generate(inputs=)instead ofinput_ids=meant PEFT could never compute aLoRA offsets, falling back to plain LoRA weights and producing wrong outputs_parse_batch_support_output()only handled flat JSON; granite-4.0-micro produces nested format ~70% of the time, silently downgrading valid citations toNOT_SUPPORTEDrequirement_check_aloraandcontext-attributiontests used exact float/list equality; relaxed to direction check (> 0.5) and subset check respectivelymax_completion_tokens, model hits transformers defaultmax_length=153and truncates JSON mid-string; xfailed pending upstream fix (see context_relevance aLoRA adapter: missing max_completion_tokens causes JSONDecodeError in test; consider deprecating #1301)Changes
mellea/formatters/granite/base/util.pyinputs=→input_ids=ingenerate_with_transformers(). One-line fix that restores aLoRA for all intrinsic tests. Absorbed from PR #1294.mellea/stdlib/requirements/rag.py_parse_batch_support_output()to handle nested citation format with pessimistic aggregation (NOT_SUPPORTED > PARTIALLY > FULLY)_norm()helper so near-miss labels like"FULLY SUPPORTED"(space) normalise correctly on both the flat and nested paths(no nested arrays)instructiontest/formatters/granite/test_intrinsics_formatters.pyrequirement_check_alora: direction check (> 0.5, matching productionrequirement_check_to_bool) instead of exact float toleranceuncertainty_alora: direction check (>= 0.5) instead of exact float tolerancecontext-attribution: subset check instead of exact list equality;_key()uses 5-field tuple includingattribution_doc_idcontext_relevance_alora:pytest.xfailbefore transform call (JSONDecodeError from truncation) — see context_relevance aLoRA adapter: missing max_completion_tokens causes JSONDecodeError in test; consider deprecating #1301context_relevance(non-alora):pytest.xfailinstead of barecontinueso non-deterministic GPU results surface in the reportcontext_relevancecondition tightened to exact==match; uncertainty f-string operator corrected to>=0.5?test/stdlib/requirements/test_groundedness_requirement.pyFour new unit tests covering the parser fix:
test_parse_batch_support_output_nested_citations— basic nested format, one citation per spantest_parse_batch_support_output_nested_citations_pessimistic_aggregate— mixed levels on one span →NOT_SUPPORTEDwinstest_parse_batch_support_output_nested_multiple_citations—FULLY + NOT → NOT; empty citations list →NOT_SUPPORTEDtest_parse_batch_support_output_nested_label_variants—"FULLY SUPPORTED"(space) normalises toFULLY_SUPPORTEDHPC verification (single full sweep, granite-4.1-3b + granite-4.0-micro, GPU p4-r30-n1)
test_run_transformers(15 combos)test_core.py(qualitative)test_rag.py(qualitative)test_guardian.py(qualitative)test_groundedness_requirement_documents_in_messagexfails:
hallucination_detection(pre-existing Transformers 5.0),context_relevance_alora(#1301),context-attribution×2 in test_core.py (pre-existing).Follow-up
context_relevance_aloraio.yaml missingmax_completion_tokens(upstream fix needed)Supersedes #1294
Testing
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