diff --git a/docs/knowledge-retrieval-audit.md b/docs/knowledge-retrieval-audit.md deleted file mode 100644 index 0b5ecbd8d..000000000 --- a/docs/knowledge-retrieval-audit.md +++ /dev/null @@ -1,266 +0,0 @@ -# Knowledge retrieval audit - -This audit covers the existing file-backed knowledge system and a bounded -manifest optimization. The [accepted scope](https://github.com/InferMatrixLab/InferRSI/issues/190) -owns the comparison protocol, revision pins and acceptance criteria. CPU -retrieval correctness and latency do not establish agent task quality, model -performance or an inference-service gain. The frozen 20-pair experiment -observed a **40.01% paired-median reduction in hot relevance-collect latency**, -with a **95% bootstrap interval of 38.38%–41.06%**, on the local CPU setup. -The frozen 24-case quality comparison preserves -every serialized output exactly; the quality figures below describe existing -retrieval behavior, not an improvement introduced by this manifest patch. - -## Construction and ownership - -Complete procedures live in -[`skill_library`](../src/inferrsi/data/skill_library/README.md): `SKILL.md`, -sidecar metadata, owner-local references, cases, scripts and licenses. The -registry maps stable names to categorized paths and backends. -[`build_skill_index.py`](../tools/build_skill_index.py) derives packaged JSON -abstracts and source-file hashes from those owners; it does not create another -editable procedure authority. Hand-maintained repository knowledge records -retain their own IDs, source revisions, applicability and verification limits. -[`catalog.py`](../src/inferrsi/catalog.py) validates and reads contribution, -dependency and peer records from their existing package-data directories. - -| Axis | Meaning | Boundary | -| --- | --- | --- | -| Kind | `skill`, `knowledge`, `case` | Generated packaged skill abstracts are `knowledge`; checkout procedures are `skill` | -| Tier | `contribution`, `dependency`, `peer` | Repository relationship, independent of kind and empirical validity | -| Authority | `package`, `checkout`, `store` | Qualified identity ownership; collisions require explicit authority | -| Origin, state, applicability | Where guidance came from and where it may apply | Import or candidate state does not establish validation, permission or promotion | - -[`KnowledgeReader`](../src/inferrsi/knowledge_operations.py) normalizes these -sources into complete Bundles. A package reader retains one catalog/library -snapshot. Checkout reads reload their current bytes; the optional -[`KnowledgeStore`](../src/inferrsi/knowledge_store.py) retains exact revisions in -an explicitly selected local SQLite workspace. Store writes publish candidate -bundles transactionally and do not edit the package or checkout. - -A Bundle revision covers normalized metadata, every included resource hash and -resolved dependency revisions. Packaged records with `skill_documents` retain -the entire shared library as a conservative dependency closure. Returning a -small context therefore does not imply constructing a small Bundle. Reading -content never executes its procedure or scripts. - -The editable architecture artifacts are retained with this campaign: -[English SVG](../evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.svg), -[Chinese SVG](../evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.svg), -[Chinese PNG](../evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.png) -and [source/rebuild notes](../evidence/knowledge-retrieval-20261027/results/architecture/SOURCE-NOTES.md). - -![Knowledge architecture, English preview](../evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.png) - -## Entrypoints and actual context delivery - -| Entrypoint | Matching and ordering | Returned material | -| --- | --- | --- | -| `knowledge search` / `search_knowledge()` | All query tokens must occur in serialized catalog JSON; occurrence-count score, then ID | Catalog records; no complete Bundle construction | -| Default `collect()` | Whitespace-token AND substring matching over normalized metadata plus entrypoint; qualified identity order | Validated items; `material=True` adds the entrypoint body | -| `collect(relevance=...)` | Eligible generated packaged skills; distinct lexical words weighted by title, summary, tags/applicability and core; score then qualified ID | Same validated items; explicit IDs preserve caller membership/order | -| `collect(context_bytes=...)` | Mandatory complete core/references/readsets/licenses/notices, then optional complete owner resources ranked by cue or path | Separate exact-revision `contexts`, explicit omissions and UTF-8 body-byte accounting | -| `read()` / `resource()` | Explicit owner and optional/required exact revision | Complete Bundle view or selected exact resource bytes | - -The merged [PR #129](https://github.com/InferMatrixLab/InferRSI/pull/129) -implemented the optional selection and context path; it is present in the -current source. The Python API returns context resources and omissions; -[`cli.py`](../src/inferrsi/cli.py) exposes `--relevance` and `--context-bytes`, -prints complete context bodies in text mode and returns the full envelope with -`--json`. `KnowledgeStore.collect()` delegates those same options to its reader. -An external agent must consume the returned material; these calls do not -automatically activate skills or execute a workflow. - -For generated packaged skills, `material=True` still means `record.json`, not -the canonical `SKILL.md`. The latter is supplied through the optional context -view or exact resource access. Item limits and serialized `max_bytes` accounting -remain separate from context-body bytes. An oversized mandatory context is -omitted atomically; the selected item may still be returned. - -The entrypoints are not interchangeable. The Python collect API supports -`repo`, `tier`, `backend` and `scenario`, but the current collect CLI parser and -dispatch do not expose them. The generator's README example -`inferrsi collect --repo-type inferrsi ...` consequently uses an unsupported -flag. This is a separate usability correction; this patch does not modify the -parser or regenerate catalog content. - -## Redundant manifest work and the bounded change - -Previously `Bundle.manifest()` hashed resource bytes during dependency -validation and again for its returned resource inventory. Directory -dependencies also rebuilt a sorted resource traversal. Required resource paths -were reparsed after the same content keys had already passed path validation. - -The change creates one sorted resource digest map per manifest call, reuses it -for direct and directory dependency checks, and returns that same map. Present -string required paths reuse the earlier content validation; missing, unsafe -and malformed requirements retain their validation path. Nothing is cached -across calls: the frozen dataclass still contains mutable dictionaries, so each -manifest must observe changed metadata, bytes, resources and dependencies. - -The remaining work is deliberate in this slice: each Bundle still validates -its complete closure, and collection still constructs eligible Bundles before -selection/output budgeting. Cross-Bundle caching, metadata-first indexes and -selection changes require their own mutation/identity contracts and evidence. - -[`test_bundle_manifest.py`](../tests/test_bundle_manifest.py) compares the -manifest and revision with the complete digest formula, checks one resource -hash per manifest call, and exercises mutations, deletion, unsafe paths, -required resources and dependency revisions. Existing reader/selection/store -tests cover source drift, stale projections, checkout changes, budgets and -revision rejection. The paired CPU report retains fresh/reused reader results, CLI costs, -exact output parity and all measured regressions. - -## Constructed retrieval evaluation - -The [prospective packet](../evidence/knowledge-retrieval-20261027/README.md) -contains 16 development and 8 withheld synthetic cases, covering natural -phrasing, symbols, multiple terms, backend filters and negatives. An explicitly -configured Codex `gpt-6.1-sol` / `xhigh` author labelled relevant identities from -original shipped procedure content before inspecting rankings. These are -partial, source-grounded AI judgements, not human gold labels, production logs, -a statistically representative sample or an exhaustive relevance inventory. -The withheld queries stayed hidden from the runtime author and orchestrator -until the runtime candidate was fixed. No query, label or budget was tuned -after the quality result. - -Both API entrypoints use `repo="inferrsi"`, the same case backend and `limit=5`. -Search takes `query=cue`; relevance collect takes `query="", relevance=cue`. -Default collect is a separate diagnostic with `query=cue`. The context/material -mode adds a 1,048,576-byte item budget and 65,536-byte context-body budget. - -| API mode | Success@5, 20 positives | MRR@5, 20 positives | Empty items, 4 negatives | -| --- | --- | --- | --- | -| Catalog search | 4/20 (20%) | 0.2000 | 4/4 | -| Default collect diagnostic | 4/20 (20%) | 0.2000 | 4/4 | -| Relevance collect | 20/20 (100%) | 0.9625 | 2/4 | -| Context/material item ranking | 20/20 (100%) | 0.9625 | 2/4 | - -Development search/default Success@5 was 3/14 and MRR@5 0.2143; withheld was -1/6 and 0.1667. Relevance/context-item Success@5 was 14/14 and 6/6, with MRR@5 -0.9464 and 1.0000 respectively. Each split had two negatives: search/default -returned empty items for both, relevance/context for one. Full per-case outputs -and byte digests are retained in -[`quality.json`](../evidence/knowledge-retrieval-20261027/results/quality.json). -All **96 outputs per revision** had exact canonical-serialization parity, -including identity order, revisions, resource hashes, omissions and byte -accounting. Source and complete-corpus identities also matched their initial -snapshots at the end. The manifest patch therefore preserved this measured -behavior; it did not create the relevance path or its higher scores. That path -was already delivered by #129. - -The item metrics do not establish delivery of the correct procedure body. A -separate **post-hoc diagnostic**, not a changed frozen gate, found labelled-owner -contexts delivered in **19/20** answerable cases. In `withheld06`, the correct -`performance_ceiling_analysis` item is first, but its complete mandatory context -requires **170,782 bytes**, more than the frozen **65,536-byte** budget. -`context_limit` omits that owner's context atomically; 51,702 bytes of other -candidates' contexts are still returned. Calling this 20/20 correct body -delivery would hide the limitation. - -Three source-backed examples explain the measured boundaries: - -- `DefaultStager` (`dev02`) yields no search/default items because this symbol - is absent from their indexed record text. Relevance examines the canonical - core and finds `dcp_async_save_performance` first; context mode delivers its - two required resources, **12,636 bytes**. A metadata projection miss does not - mean the underlying procedure lacks the answer. -- The negative `sourdough levain hydration recipe` (`dev16`) returns five - systems skills through relevance and two contexts totaling **38,037 bytes**. - The scorer accepts any positive substring overlap; `recipe` also occurs in - unrelated systems procedures as `recipe`/`recipes`. It has no calibrated - no-answer threshold or generic-term penalty. -- For `dev14`, `claim_contract` is fourth: broader performance/evidence skills - precede the more specific validator-freeze answer. Broad word overlap can - therefore dilute first-position precision even when Success@5 is satisfied. - -## Prospective CPU latency result - -Twenty paired groups (ten AB, ten BA) measured four fixed hot-query types on the -local Intel Core i7-8565U / Windows 10 / CPython 3.12.6 setup. The frozen paired -median reduction was **40.01%**, with 95% bootstrap interval **38.38%–41.06%**, -satisfying the prospective CPU retrieval gate. The measurement loop retained -640 API calls and 160 CLI processes over 836.162 seconds. All 400 cross-version -output pairs and 80 exact CLI stdout pairs matched; source/corpus identities -remained unchanged. Independent read-only review reproduced the raw statistics -and bootstrap exactly. - -Regressions are explicit: API search `dev01` p50 **+1.19%**; CLI search `dev05` -p50 **+2.50%**; CLI relevance decode p95 **1.810 → 3.046 ms (+1.236 ms, +68.31%)**. -No cause is established by these observations. Each per-query p95 uses only -20 repeats, not additional query types or a service tail guarantee. OS cache, -clock/power state and background load were uncontrolled; no service/model/agent -benefit is inferred. - -[performance.md](../evidence/knowledge-retrieval-20261027/results/performance.md) -retains the complete per-mode/query p50/p95 tables for all 48 revision-specific -groups, methodology and limitations; [latency-summary.json](../evidence/knowledge-retrieval-20261027/results/latency-summary.json) -preserves exact nanosecond summaries, and [benchmark.json](../evidence/knowledge-retrieval-20261027/results/benchmark.json) -retains all raw observations and output digests. The baseline profile and #129 -trace remain separate diagnostics. - -## Local validation and remaining qualification - -The complete local pytest attempt reported **10 failed, 1,340 passed, 6 skipped, -2 errors and 135 subtests passed**, in 953.11 seconds. Rechecking the eleven -selected failing/erroring functions on both revisions gave 9 failed, 4 passed -and 3 errors per side. The CRLF fixture initially failed, then errored during -the polluted focused run; isolated from the large-parameter fixture, both -revisions reproduced 1 failed/1 passed with `Skill metadata must remain -unchanged`. All initial failures/errors were thus reproduced on the baseline. -This remains a failed whole-suite result. - -The observed blockers involve Windows environment-variable length, GBK -decoding, unavailable Bash, temporary-path differences, an asset-manifest -snapshot and unavailable `os.getpgrp`, plus the CRLF fixture behavior above. -All 20 new manifest regressions passed; the runtime author separately reported -80 targeted passes and a selected baseline run reported 104 passes. Default -isolated wheel/sdist builds succeeded after an earlier no-isolation attempt -failed for missing setuptools. All 469 packaged data files and the packaged -runtime source matched the source byte-for-byte. Exact qualifications and the -wheel digest are in -[`validation-summary.md`](../evidence/knowledge-retrieval-20261027/results/validation-summary.md). -The evidence inventory tests subsequently passed **23 tests**; the read-only -inventory check reported **no errors, 9 bundles and 120 verified hashes**. -`ruff check src tests tools` passed. A wheel-only, site-disabled smoke read -108 records and reproduced all four `DefaultStager` output hashes from the -formal candidate quality result. Its first harness attempt stopped at an -unresolved temporary short-path import-origin check before retrieval; -normalizing the expected path fixed that harness check. No package defect -was established by that retry. Remote CI is pending at PR creation. Rerun -the full suite on a clean supported Linux environment; local baseline -reproduction is not cross-platform qualification. - -Independent reviewers performed read-only checks; their model/effort settings -are unknown and are not listed as material authors. The review record retains -the pre-measurement validator corrections, quality/body-delivery distinction, -raw benchmark recomputation and diagram check. These checks are separate -from human/maintainer goal acceptance, merge and issue closure, which remain -with the authorized owner. - -Follow-up work should remain separately scoped: first make canonical-body -discovery and API/CLI filtering consistent; then evaluate generic-term weighting -and no-answer behavior with independent labels; then distinguish item discovery -from complete required-body delivery and make required bytes visible before -choosing a budget. A later performance slice may address repeated full-library -closure/hash work across Bundles, but only with explicit mutation and revision -contracts. This patch changes none of those behaviors. - -## Quality limits and historical evidence - -Less hashing cannot repair retrieval behavior. Default collect still has AND -substring matching and identity order. Optional relevance still uses literal -word overlap, positive-score eligibility and fixed field weights: it does not -resolve synonyms, infer task intent or provide calibrated no-answer confidence. -Whole-resource context can still exceed a budget, and callers still need to -follow omitted links through exact revisions. These are existing boundaries; -any observed misses or false positives must be reported with the measured cases. -No score, order, query, context budget or omission rule changes in this patch. - -The closed [issue #128 owner report](https://github.com/InferMatrixLab/InferRSI/issues/128) -records accepted delivery of bounded whole-resource software and its comparison -packet: 36 attempts, 34 task PASS and 2 INCONCLUSIVE. It reports that C used -25.74% more input/output tokens than B, with no accepted reduced-cost/preserved-quality -benefit. Those are historical owner-reported results, not a rerun or new -independent verification by this audit. This work preserves that conclusion; -retrieval metrics and CPU parity cannot upgrade it to agent efficacy. diff --git a/docs/plans/2026-10-27-knowledge-retrieval.md b/docs/plans/2026-10-27-knowledge-retrieval.md deleted file mode 100644 index b1d6a61c9..000000000 --- a/docs/plans/2026-10-27-knowledge-retrieval.md +++ /dev/null @@ -1,46 +0,0 @@ -# Knowledge retrieval implementation plan - -**Goal:** Reduce repeated work in `Bundle.manifest()` while retaining the same -validated manifest, revision and retrieval results. - -**Architecture:** Reuse resource digests and validated content paths within one -manifest call. `Bundle.metadata`, `Bundle.content` and `Bundle.dependencies` -remain mutable, so no digest or manifest survives that call. Keep the existing -package snapshot, checkout and store ownership boundaries. - -**Scope:** `src/inferrsi/knowledge_operations.py`, focused regression tests in -`tests/test_bundle_manifest.py`, and the source-grounded audit in -`docs/knowledge-retrieval-audit.md`. Catalog/source bytes, scoring, query -semantics, ordering, budgets, omissions and dependency closure are unchanged. -Performance gates, revision pins and frozen measurement inputs belong to the -governing acceptance issue and its evidence packet, not reusable defaults. - -## Plan -> code -> test -> review - -1. Inspect the reader, selection helper, store and existing tests. Compare the - alternatives: local digest reuse is bounded; persistent Bundle caching is - unsafe with mutable inputs; changing selection is outside this slice. -2. Add a small synthetic Bundle fixture with file and directory dependencies. - Verify the complete manifest and revision against the existing digest - formula; count hashing calls and verify each resource is hashed once per - call. Verify repeated calls detect changed bytes, removed resources, unsafe - paths, changed metadata/requirements and changed dependency revisions. -3. In `Bundle.manifest()`, build one sorted resource digest map after content - validation and required-resource checks. Reuse it for dependency validation - and the returned resource inventory. Reuse validated required paths while - preserving missing/unsafe-path validation and existing error categories. -4. Run `python -m pytest tests/test_bundle_manifest.py - tests/test_knowledge_operations.py tests/test_collect_selection.py - tests/test_knowledge_store.py` and `python -m ruff check - src/inferrsi/knowledge_operations.py tests/test_bundle_manifest.py`. - The accountable parent runs the full suite, installed-package checks and - paired performance/quality protocol after its independent fixture freeze. -5. Review the diff for persistent caching, changed resource closure, digest - order, invalid-input behavior, private data and unrelated changes. Record - actual checks separately from pending measurements. Commit with the actual - configured identity, DCO sign-off and material-agent attribution; hand the - revision to the accountable parent for independent review and integration. - -The audit distinguishes the delivered optional whole-resource context from -historical efficacy claims. It does not reinterpret the prior campaign or -claim that less hashing improves selection quality or agent outcomes. diff --git a/evidence/knowledge-retrieval-20261027/README.md b/evidence/knowledge-retrieval-20261027/README.md deleted file mode 100644 index 2680a2c73..000000000 --- a/evidence/knowledge-retrieval-20261027/README.md +++ /dev/null @@ -1,50 +0,0 @@ -# CPU knowledge retrieval evidence - -Acceptance scope and ownership: [InferRSI #190](https://github.com/InferMatrixLab/InferRSI/issues/190). -This packet tests a manifest implementation that preserves retrieval behavior. -The frozen quality/parity and paired CPU performance gates passed. Campaign -acceptance, merge and issue closure remain with the authorized owner. - -| Segment | Contents | -| --- | --- | -| `plan/` | Prospective protocol, current freeze, preserved first freeze and pre-measurement review amendment | -| `validator/` | Standard-library runner, 16 development and 8 withheld synthetic cases with source-grounded partial relevance labels | -| `results/` | Complete quality comparison, paired raw API/CLI measurements, baseline profile, #129 delivery trace, editable EN/ZH architecture artifacts and qualified local software/environment summaries | -| `patch/` | Fixed runtime candidate and exact source identity | - -The current prospective freeze is -`a465367319f3058398eb1f8579ee5d4174b8cb90457793e90788fb5796151057`. -Independent review corrected completeness checks and removable assertions before -formal candidate measurement; `plan/amendment-1.md` records the change. The -withheld split was released only after the runtime candidate was fixed. Fixture -text and labels did not change between freezes. Root `.gitattributes` preserves -evidence bytes; copying or committing must retain the recorded hashes. - -The full quality result has **96 outputs per revision, exact parity and unchanged -source/corpus identities**. For 20 labelled answerable cases, search/default -collect score Success@5/MRR@5 = 0.20/0.20; relevance/context-item ranking scores -1.00/0.9625. Four labelled negatives return empty items in 4/4 search/default -cases and 2/4 relevance/context cases. These are unchanged existing #129 -behaviors, not a quality improvement from this runtime patch. - -Context-item ranking does not establish correct body delivery. A post-hoc -inspection found the labelled owner's context delivered in **19/20** positive -cases. `withheld06` finds its correct item first but requires 170,782 context -bytes against a 65,536-byte budget, so that owner's context is omitted. This -diagnostic does not change the frozen quality gate. Synthetic, AI-authored, -partial source labels are not human gold judgements or complete Recall; no -agent-task efficacy or production-distribution claim follows. - -The 20-pair CPU result observed **40.01%** hot-relevance paired-median latency -reduction, 95% interval **[38.38%, 41.06%]**, with all 400 output pairs and -80 CLI stdout pairs equal. [performance.md](results/performance.md) retains -all per-mode/query p50/p95 rows, including search regressions and CLI relevance -decode p95 **1.810 → 3.046 ms**. Independent read-only recomputation passed; -reviewer model/effort is unknown and no human/maintainer acceptance is recorded. - -See the [audit](../../docs/knowledge-retrieval-audit.md) for source contracts, -per-query examples, failure qualifications and follow-up priorities. Local -software verification includes a failed whole-suite run whose initial failures -were reproduced on baseline, successful focused manifest checks and successful -isolated wheel/sdist construction; it must not be described as a green full -suite. No model, GPU or inference-service benchmark ran. diff --git a/evidence/knowledge-retrieval-20261027/patch/README.md b/evidence/knowledge-retrieval-20261027/patch/README.md deleted file mode 100644 index 788fc65eb..000000000 --- a/evidence/knowledge-retrieval-20261027/patch/README.md +++ /dev/null @@ -1,11 +0,0 @@ -# Runtime patch boundary - -The evaluation-material author changed no runtime source. `candidate.json` -records the independently authored runtime commit and exact Python-source -digest used by the formal comparison. The implementation reuses digest/path -work within a manifest call; it introduces no cross-call mutable cache. - -Runtime integrity tests and independent review belong beside those revision -records. Exact-output parity does not replace mutation or unsafe-path regression -checks. Later evidence/documentation integration must preserve the tested -runtime bytes; merge and issue closure remain with the authorized owner. diff --git a/evidence/knowledge-retrieval-20261027/patch/candidate.json b/evidence/knowledge-retrieval-20261027/patch/candidate.json deleted file mode 100644 index 0b34d0947..000000000 --- a/evidence/knowledge-retrieval-20261027/patch/candidate.json +++ /dev/null @@ -1,12 +0,0 @@ -{ - "schema_version": 1, - "governing_issue": "https://github.com/InferMatrixLab/InferRSI/issues/190", - "baseline_sha": "4817f92121df73fd9cd5fb4a319e3c56a68b4a5b", - "candidate_runtime_sha": "407bb244651bec1c68f4b3e94b0c697b233c4a09", - "runtime_author_commit": "864fd74e709a1411e4f8dfd3051cc9b737d8c333", - "candidate_python_sources_sha256": "d6edbaf975cf3bc00902d6aa7cf2bb955dc58b3e37c74f59bb226c5f0d2fa261", - "scope": "Reuse sorted resource digests and validated paths within each Bundle.manifest call. No cache survives a call and retrieval outputs must remain identical.", - "runtime_source": "src/inferrsi/knowledge_operations.py", - "runtime_regressions": "tests/test_bundle_manifest.py", - "integration_note": "Evidence, audit, diagrams and read-only inventory registration are integrated separately; compare their packaged runtime source to this fixed tested candidate. No merge or issue closure is implied." -} diff --git a/evidence/knowledge-retrieval-20261027/plan/README.md b/evidence/knowledge-retrieval-20261027/plan/README.md deleted file mode 100644 index e61d8bbcf..000000000 --- a/evidence/knowledge-retrieval-20261027/plan/README.md +++ /dev/null @@ -1,45 +0,0 @@ -# Frozen evaluation protocol - -Governing acceptance: [InferRSI #190](https://github.com/InferMatrixLab/InferRSI/issues/190). -The machine-readable protocol is `protocol.json`; the freeze manifest commits -protocol, independently constructed inputs and validator bytes before candidate -measurement. This packet is authored by Codex `gpt-6.1-sol` / `xhigh`. - -1. Read the shipped source content, construct 16 development and 8 withheld cases, - and label defensible relevant package identities by original resource paths. - Do not consult rankings while labelling. The partial labels are sufficient - for Success@5/MRR@5, not complete Recall. The queries are synthetic and have - no production-distribution claim. -2. Validate fixture references and freeze all authored inputs and scripts. Keep - withheld queries/labels outside the runtime author's and orchestrator's view - until the candidate revision and source digest are fixed. -3. Profile the read-only baseline separately. Run quality/parity and the frozen - 20 balanced paired groups with one interpreter and an equal complete corpus. - Each process explicitly imports the selected checkout rather than a possibly - unrelated editable install. Keep all raw timings and exact-output digests. -4. Report search and relevance retrieval separately at identical API scope - (`repo=inferrsi`, `limit=5`). Report default collect, context delivery and CLI - startup separately. The current collect CLI lacks repo/backend filters; - its wider-scope startup cost is not an equivalent retrieval-quality result. -5. Apply frozen gates, self-check output integrity and submit artifacts for an - independent review. This evaluation does not establish model task efficacy, - full-library recall, service throughput or OS filesystem-cache-cold latency. - -The primary performance statistic is the median of 20 paired reductions, each -formed from the median latency of four fixed hot relevance queries. The 95% -percentile bootstrap resamples complete paired groups with seed `19020261027` -for 10,000 iterations. The prospective issue bar requires at least 20% median -reduction and a lower confidence bound above zero. No trimming or post-hoc -choice of the fastest query, summary or run is allowed. - -Exact parity covers the complete canonical serialization, with readable -projections for identity order, revisions, resource-hash inventories, omissions, -collision metadata, material bytes and context bytes/budget. The API timer -excludes the evaluator's serialization and hashing work. Full CLI timings -include process creation, imports, command work and stdout capture; decoding is -measured separately. Fresh-reader API calls include reader construction; -reused-reader calls follow one untimed pass across all four hot queries. - -No candidate has been timed while this protocol is being authored. Missing or -incomplete evidence remains INCONCLUSIVE. Existing #128/#129 evidence stays -historical and is not relabelled as this campaign's measured result. diff --git a/evidence/knowledge-retrieval-20261027/plan/amendment-1.md b/evidence/knowledge-retrieval-20261027/plan/amendment-1.md deleted file mode 100644 index 79e2534f6..000000000 --- a/evidence/knowledge-retrieval-20261027/plan/amendment-1.md +++ /dev/null @@ -1,28 +0,0 @@ -# Pre-measurement amendment 1 - -Independent review found two fail-closed defects after the first packet freeze -and before any formal candidate evaluation or timing: - -- Positional `zip` comparisons could silently ignore missing output rows. A - synthetic candidate with incomplete API/CLI measurements could satisfy the - timing gate without complete evidence. -- Fixture and warmup checks used Python assertions, which optimized Python could - disable. - -The validator now requires the exact case-by-mode sets once per side, the full -pair-ID range and each prescribed AB/BA order. Missing, extra or duplicate rows -or pair IDs make the comparison INCONCLUSIVE and prevent a performance PASS. -Quality comparison explicitly checks its complete expected set, including all -96 rows per side for the full 24-case run. Keyed comparisons replace `zip`. -Critical checks raise explicit exceptions; child processes set PYTHONOPTIMIZE=0 -and record optimization flags. Synthetic selfchecks cover incomplete/duplicate -quality rows, missing benchmark rows and duplicate paired groups. - -The original `plan/freeze-v1.json` is preserved with content digest -`2a90de774129b06597c3c99e5b06d05bf735026829deb84376d06a985cdcc276`. -Before this supersession, only source-label/static validation and -baseline-v-baseline mechanics had run, never formal candidate measurement. -The revised `plan/freeze.json` -supersedes it prospectively. Fixture text, relevance labels, scoring rules, -query workloads, numeric gates and bootstrap method/seed are unchanged. The -runtime candidate was already fixed before the withheld fixture was released. diff --git a/evidence/knowledge-retrieval-20261027/plan/freeze-v1.json b/evidence/knowledge-retrieval-20261027/plan/freeze-v1.json deleted file mode 100644 index cde2e7481..000000000 --- a/evidence/knowledge-retrieval-20261027/plan/freeze-v1.json +++ /dev/null @@ -1,13 +0,0 @@ -{ - "schema_version": 1, - "frozen_at_utc": "2026-10-27T11:17:10.632059+00:00", - "files": { - "plan/protocol.json": "dc0fbbb4438a072fe1dbc530f5a60a4b1e1e779cc32697fd9adccc0eac3bc4fc", - "plan/README.md": "12e0bb007b6a4ce7a4177e1843ae46ab3327fdd7fcc6591c3332db5684f83c3d", - "validator/development.json": "d2f428c41787bfa6279e8a0b56532e76554482ab98dca553e7e9febe287e8dfb", - "validator/withheld.json": "5bf9b8e55871a986cf7848959bf83e401821939acd13ee067563dc83952182e9", - "validator/evaluate.py": "47d36dd7b0a0967cb74ae53a31646b8bf063958b3845769447c6e8af8f42e5e1", - "validator/README.md": "2ca7c11a3add1a277c7c60dc24820d8fe5077e239d5deaf4ea6b0fe1195abe7c" - }, - "content_sha256": "2a90de774129b06597c3c99e5b06d05bf735026829deb84376d06a985cdcc276" -} diff --git a/evidence/knowledge-retrieval-20261027/plan/freeze.json b/evidence/knowledge-retrieval-20261027/plan/freeze.json deleted file mode 100644 index ac0c62625..000000000 --- a/evidence/knowledge-retrieval-20261027/plan/freeze.json +++ /dev/null @@ -1,17 +0,0 @@ -{ - "schema_version": 1, - "revision": 2, - "supersedes_content_sha256": "2a90de774129b06597c3c99e5b06d05bf735026829deb84376d06a985cdcc276", - "frozen_at_utc": "2026-10-27T11:22:45.564236+00:00", - "files": { - "plan/protocol.json": "91f2966ddf7d37683cd2a79cd995ec1ad7b41993ea1e6c2cd008db48a3b99351", - "plan/README.md": "12e0bb007b6a4ce7a4177e1843ae46ab3327fdd7fcc6591c3332db5684f83c3d", - "validator/development.json": "d2f428c41787bfa6279e8a0b56532e76554482ab98dca553e7e9febe287e8dfb", - "validator/withheld.json": "5bf9b8e55871a986cf7848959bf83e401821939acd13ee067563dc83952182e9", - "validator/evaluate.py": "e5b8c99f6955420e67bb0d9fbcc4c08a6c8a95d857385a5d9f0a0f2f74e0f194", - "validator/README.md": "e9b5f55e2b74b184a6bf2d31e342074e120663fa48286d6b14496491bc39eea4", - "plan/amendment-1.md": "4feac787c0fff35bab49b04f1dc2fdd7648febc25a770a59d359f7d7ddb30c2c", - "plan/freeze-v1.json": "a1f727ea4914b194469e5183cc2df6c7ec2b42614cc294dc14c0ec0fbd8dcb05" - }, - "content_sha256": "a465367319f3058398eb1f8579ee5d4174b8cb90457793e90788fb5796151057" -} diff --git a/evidence/knowledge-retrieval-20261027/plan/protocol.json b/evidence/knowledge-retrieval-20261027/plan/protocol.json deleted file mode 100644 index 4dbc1827b..000000000 --- a/evidence/knowledge-retrieval-20261027/plan/protocol.json +++ /dev/null @@ -1,58 +0,0 @@ -{ - "schema_version": 1, - "campaign": "knowledge-retrieval-20261027", - "governing_issue": "https://github.com/InferMatrixLab/InferRSI/issues/190", - "baseline_sha": "4817f92121df73fd9cd5fb4a319e3c56a68b4a5b", - "author": {"tool": "Codex", "model_id": "gpt-6.1-sol", "effort": "xhigh", "role": "evaluation-material-author"}, - "scope": "CPU-only offline retrieval software behavior and latency; no model, engine, service, production-distribution, complete recall or agent-efficacy claim", - "fixture": { - "total": 24, - "development": 16, - "withheld": 8, - "construction": "Independent source-content judgements made without retrieval rankings; synthetic questions, not private production logs or a statistically representative sample.", - "release": "Withheld text and labels must not be read by the runtime author or orchestrator before the candidate revision and runtime source digest are fixed. Freeze manifest commits their exact bytes." - }, - "quality": { - "repo": "inferrsi", - "limit": 5, - "entries": { - "search": "catalog.search_knowledge(query=cue, repo='inferrsi', backend=case_backend, limit=5)", - "relevance": "KnowledgeReader.collect(query='', relevance=cue, repo='inferrsi', backend=case_backend, limit=5)", - "context_material": "Same relevance call with material=True, max_bytes=1048576, context_bytes=65536", - "default_diagnostic": "KnowledgeReader.collect(query=cue, repo='inferrsi', backend=case_backend, limit=5); report separately" - }, - "answerable_metrics": ["Success@5 = mean(any labelled relevant identity in ordered top five))", "MRR@5 = mean(1 / first labelled relevant rank), or zero if absent"], - "denominator": "Answerable cases only; report entrypoint and development/withheld splits plus per-case judgements. Labels identify defensible relevant results, not an exhaustive relevance inventory. Do not call this Recall.", - "no_answer": "Separate count, returned identities and no_match behavior; do not include in Success/MRR and do not treat empty lists as proof that the corpus has no answer.", - "equivalence": "All four modes on every case must have exactly equal canonical JSON bytes between revisions, including order, omissions, resource hashes, revisions, material and context budgets. Retain byte count, SHA-256 and readable projection of each exact output.", - "serialization": "json.dumps(value, sort_keys=True, ensure_ascii=False, separators=(',', ':'), allow_nan=False).encode('utf-8')" - }, - "performance": { - "pairs": 20, - "order": "Pair 0 AB, pair 1 BA, alternating for 10 groups of each order. A=baseline, B=candidate. Each side runs in a new isolated subprocess, sequentially. No concurrency.", - "hot_cases": ["dev01", "dev05", "dev09", "dev13"], - "warmup": "One untimed hot relevance collect per hot case on the same KnowledgeReader, followed by one default dev05 and one context_material dev09 warmup before measurements; record reader record/library cache population. Reuse this reader for hot measurements. Cold measurement creates a new reader inside the timed interval. OS filesystem caches are not evicted or claimed cold.", - "api_workloads": ["hot and fresh-reader relevance for all four hot cases", "search for all four hot cases", "hot and fresh-reader default collect using dev05", "hot and fresh-reader context_material using dev09"], - "timing": "perf_counter_ns around API call only; output serialization/hashing outside API timer. Warm measurements include normal output construction. Raw nanoseconds retained per query/pair/side/mode.", - "cli": "Separate full process subprocess.run([same_python, '-S', '-m', 'inferrsi', ...]), UTF-8 decode+JSON parse timing and raw stdout SHA-256/byte count. search uses --repo-type inferrsi; collect does not expose repo/backend filters and is explicitly an unfiltered CLI diagnostic. No CLI numbers pooled into the hot-API gate.", - "cli_cases": ["search dev05", "default collect dev05", "relevance collect dev05", "context/material collect dev09"], - "summaries": "Per mode/query/side p50 and p95 from all raw observations using linear interpolation at (n-1)*p. No trimming, outlier removal, retries or stopped-run pooling.", - "primary_estimator": "For each pair, take median of its four hot relevance query latencies for each side. Paired reduction r_i = 1 - median(candidate_queries_i) / median(baseline_queries_i). Report median(r_i). Each pair is one resampling unit, preserving its query set.", - "bootstrap": {"method": "percentile bootstrap of paired reductions; each draw samples 20 reductions with replacement, then computes their median", "iterations": 10000, "seed": 19020261027, "confidence": 0.95, "quantiles": [0.025, 0.975], "quantile_method": "linear interpolation at (n-1)*p"}, - "gate": {"minimum_paired_median_reduction": 0.20, "lower_95_percent_bound_must_exceed": 0.0}, - "limits": "Machine background load and filesystem-cache state remain observational limits. This is neither OS-cache-cold nor an engine/service benchmark. Cold/API/CLI regressions reported individually. Estimated bounded run length 5-10 minutes; actual elapsed and every completed sample retained. An incomplete run is INCONCLUSIVE.", - "completeness": "Before summary/gating require pair IDs exactly 0..19 once each with prescribed alternating AB/BA order and each side's exact16 API plus4 CLI case-by-mode set, no duplicates or extras. Quality requires the complete expected24x4 output set per side. Missing/duplicate/extra structure is INCONCLUSIVE and cannot satisfy the performance gate." - }, - "source_control": { - "loading": "Explicit checkout/src overrides editable installs; -S excludes site initializers and editable hooks. Explicit exceptions verify inferrsi, catalog, knowledge_operations and CLI resolved inside requested source tree. Critical checks do not use removable Python assertions. Children set PYTHONOPTIMIZE=0 and record sys.flags.optimize; parent optimization is recorded. Same interpreter for both versions.", - "identity": "Record explicit git HEAD, dirty tracked-source status, all Python source relative-path SHA-256s and aggregate; all shipped repo_packs/**/*.json, knowledge_packs files and entire skill_library relative-path file SHA-256s, aggregate, counts and bytes. This covers contribution, dependency and peer records plus their package and library resources. Ignore incidental __pycache__/.pyc only. No personal absolute paths or host names in artifacts.", - "corpus": "Both variants must have exactly equal complete shipped corpus digest; do not use a reduced custom corpus. Corpus inventory covers all shipped records and library resources, not merely retrieved items.", - "freezing": "Freeze protocol, fixture and validator scripts in plan/freeze.json before candidate timing. Separate withheld fixture remains sealed until candidate freeze. A validator change requires a new freeze manifest and explanation; never silently amend frozen evidence." - }, - "diagnostics": { - "profile": "Optional baseline-only cProfile with relative/sanitized source labels; keep counts, total and cumulative times. Profiling time is excluded from benchmark samples.", - "trace_129": "Execute distinct search, default, relevance and context/material modes on an independently authored development cue; record selection method/ranking flag, revisions, context resource roles and omissions. This tests merged #129 delivery code paths, not historical #128 task efficacy.", - "integrity": "Mutation/stale-index/dependency/path/checkout/revision regression tests belong to runtime patch verification; evaluator parity does not replace them." - }, - "verdict": "FAIL for observed parity/metric/performance-gate failure; INCONCLUSIVE for missing required measurements or unequal/unverified corpus/source; PASS only for this bounded CPU retrieval campaign after all required evidence and independent review. Merge/issue closure remains with acceptance owner." -} diff --git a/evidence/knowledge-retrieval-20261027/results/README.md b/evidence/knowledge-retrieval-20261027/results/README.md deleted file mode 100644 index 540c91afa..000000000 --- a/evidence/knowledge-retrieval-20261027/results/README.md +++ /dev/null @@ -1,37 +0,0 @@ -# Completed bounded retrieval results - -The full 24-case quality comparison and 20-pair CPU benchmark passed their -prospectively frozen gates. This is local offline retrieval evidence; -human/maintainer acceptance, merge and Issue closure remain separate. - -- `quality.json`: 96 outputs per revision exactly equal; 20 partial-labelled - positives and four negative probes. Existing #129 relevance-item behavior - was preserved, not introduced or improved by this manifest patch. -- `benchmark.json`: 20 balanced groups, 640 API calls and 160 CLI processes; - hot relevance paired-median reduction 40.0068267%, 95% interval - [38.3789227%, 41.0592071%]. All 400 output pairs and 80 stdout pairs equal; - final source/corpus identities unchanged. -- `performance.md` and `latency-summary.json`: complete per-mode/query p50/p95 - display, including regressions. CLI relevance decode p95 rose - 1.810 to 3.046 ms; no cause or blanket tail improvement is inferred. -- `context-delivery-diagnostic.json`: post-hoc API-response context presence - for 19/20 labelled owners, separate from the frozen item-ranking metric. -- `baseline-profile.json` and `baseline-trace-129.json`: separate source/path - diagnostics, excluded from performance samples. -- `validation-summary.md`, `environment.md`, `independent-review.md`: local - failed-suite/baseline reproduction, package checks, hardware/interpreter - limits and independent read-only review with unknown reviewer model/effort. -- `architecture/`: editable EN/ZH SVGs, PNG previews, source, layout checks - and reproducible source notes; these diagrams establish software contracts. - -Files named `dry-run-*` are baseline-v-baseline mechanics only and explicitly -INCONCLUSIVE. Their two cases/two paired groups are not pooled into formal -results. Validator synthetic selfchecks include optimized Python and missing -measurement cases; they are not retrieval performance samples. - -The whole Windows pytest attempt was not green. All initial failures/errors -were reproduced on baseline; focused manifest/inventory checks, isolated -package construction and wheel-only source/output parity checks passed. -Remote CI is pending at PR creation. No model, GPU, service, production-query -or agent-task experiment ran, and partial AI-authored source labels are not -human gold or complete Recall. diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/SOURCE-NOTES.md b/evidence/knowledge-retrieval-20261027/results/architecture/SOURCE-NOTES.md deleted file mode 100644 index bc6a14dee..000000000 --- a/evidence/knowledge-retrieval-20261027/results/architecture/SOURCE-NOTES.md +++ /dev/null @@ -1,42 +0,0 @@ -# InferRSI knowledge architecture diagrams - -Original SVG author configuration: **gpt-6.1-sol / xhigh**, explicitly configured for this delegated diagram task. The SVGs use editable text and vector shapes. No unknown-author draft or code was reused. The supplied reference image informed only the visual treatment: four horizontal panels, light backgrounds, green retrieval panel, blue contracts, solid data-flow arrows, dashed reference/review lines and an evidence strip. - -Evidence baseline: the explicitly selected baseline checkout at commit `4817f92121df73fd9cd5fb4a319e3c56a68b4a5b`. All diagram files and the rendering script stay in the selected output directory; the baseline is read-only. - -Content sources read: - -- `docs/knowledge-base.md`: canonical ownership, authority boundary, registry versus generated catalog, matrices, frozen evidence, explicit use. -- `docs/knowledge-operations.md`: default Collect, independent relevance/context opt-ins, exact revisions, complete mandatory resources and byte accounting. -- `docs/knowledge-store.md`: explicitly authorized local store, candidates only, immutable history, reviewed repository maintenance. -- `src/inferrsi/catalog.py`: legacy catalog search tokenization, filtering, occurrence-count ordering and ID tie-break. -- `src/inferrsi/knowledge_operations.py`: Bundle revision, package/checkout/store identity rules, record.json material, API filters, limits and omission behavior. -- `src/inferrsi/_skill_selection.py`: generated packaged skill validation, deterministic lexical weights, complete-file context, licenses/notices and optional resource selection. -- `tools/build_skill_index.py`: stable registry input, fixed committed source snapshot, source-file hashes and generated `kind=knowledge` catalog records. - -Interpretation limits: - -- Canonical skill content is organized under `hardware/`, `frameworks/`, `repositories/`, `methods/` and `workflows/`. These ownership categories are distinct from Skill/Knowledge/Case kinds, contribution/dependency/peer relationships, and backend compatibility qualification. Applicability is a metadata field. -- This is an architecture/contract diagram, not a count of skills or proof of task performance, hardware compatibility, licensing clearance or empirical validation. -- `knowledge search` and Collect remain separate retrieval modes. Collect's metadata filters are labeled as Reader API features; the figure does not imply that every API filter has a corresponding Collect CLI flag. -- Generated packaged skill records retain `kind=knowledge`. Packaged `material` returns the record entrypoint (`record.json`); the separate context view supplies canonical SKILL.md and complete mandatory references within an explicit UTF-8 resource-body byte budget. -- If mandatory context resources exceed the context byte budget, that owner's context is omitted. The selected item can still be returned in `items`; context omission is not item omission. -- The projection is not an editable content authority, and the stable-ID registry is not the generated catalog. Source commits, local Bundle revisions and tested engine revisions have different meanings. -- Local store writes do not mutate package/checkouts, evidence or matrices, and they do not promote candidates. The bottom dashed connections describe references/review, not automatic feedback or execution. -- A performance implementation that reuses digest/path work inside one manifest does not add a new database, persistent cache or scoring method; it does not change this architecture. - -From this architecture-artifact directory, rebuild with the existing bundled Python runtime: - -```powershell -& '' './build_diagrams.py' -``` - -Pillow checks text widths and card heights; SVG XML parsing checks structure; CairoSVG renders 3200 × 2100 PNG previews from the 1600 × 1050 vector source. Fonts are Segoe UI (English) and Microsoft YaHei with Noto Sans SC fallback (Chinese). Text remains editable in SVG; preview rendering uses installed system fonts. - -Independent review clarified the English fourth-column budget line to -“Required set over budget: omit context.” Codex `gpt-6.1-sol` / `xhigh` applied -that one-line source correction, regenerated the assets/layout checks and -visually inspected the English PNG. The Chinese text already expressed the -required-set boundary and was unchanged. This states the context omission -contract without implying that optional-resource overflow omits the whole -context. diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/build_diagrams.py b/evidence/knowledge-retrieval-20261027/results/architecture/build_diagrams.py deleted file mode 100644 index 27c1b6014..000000000 --- a/evidence/knowledge-retrieval-20261027/results/architecture/build_diagrams.py +++ /dev/null @@ -1,239 +0,0 @@ -"""Original editable InferRSI knowledge diagrams, based on the pinned audit tree. - -Author configuration: gpt-6.1-sol / xhigh, explicitly configured for this delegated task. -Run with the bundled Python runtime. Requires existing Pillow and CairoSVG. -All output is confined to this script's directory. -""" -from __future__ import annotations - -from dataclasses import dataclass -from html import escape -from pathlib import Path -import json -import xml.etree.ElementTree as ET - -import cairosvg -from PIL import Image, ImageFont - -OUT = Path(__file__).resolve().parent -WIDTH, HEIGHT = 1600, 1050 -BASELINE = "4817f92121df73fd9cd5fb4a319e3c56a68b4a5b" -PALETTE = { - "ink": "#1e293b", "body": "#526782", "muted": "#7c8da8", - "panel": "#f6f8fc", "panel_stroke": "#dce5f1", - "card": "#ffffff", "card_stroke": "#c5d3e8", - "blue": "#5482ff", "blue_fill": "#edf3ff", "blue_ink": "#2149bc", - "green": "#37ad70", "green_fill": "#effaf4", "green_ink": "#238051", - "purple": "#966bd7", "line": "#a9b8cc", -} - - -@dataclass -class Card: - y: int - h: int - title: str - lines: list[str] - style: str = "plain" - line_height: int = 20 - - -EN = { - "title": "InferRSI Knowledge Architecture", - "subtitle": "Canonical sources → build & authorities → retrieval → exact reads & explicit use", - "top_note": "K0/K1 foundation · K2 operations", - "heads": ["1 · CANONICAL SOURCES", "2 · BUILD & AUTHORITIES", "3 · RETRIEVAL", "4 · READ & USE"], - "cards": [ - [ - Card(185, 125, "Complete skill library", ["SKILL.md: name + procedure", "metadata.json: state + applicability", "references/ + cases/: owner-local", "Licenses and source inventories"]), - Card(326, 120, "Imported catalog sources", ["repo_packs/ + knowledge_packs/", "Existing IDs, tiers, scope and sources", "Contribution · dependency · peer"]), - Card(462, 147, "Typed source identities", ["Git commit + inspected paths", "Paper version · document snapshot", "Internal run + artifact identity", "Source pin ≠ content revision", "Frozen evidence stays at its owner"]), - Card(625, 129, "Ownership and qualification", ["hardware/ · frameworks/", "repositories/ · methods/ · workflows/", "State ≠ validation ≠ permission", "Backend scope ≠ compatibility", "Unknown provenance/licenses retained"], "dashed", line_height=17), - ], - [ - Card(185, 103, "Stable-ID registry", ["skill-index.json", "Skill IDs → paths + backend", "Separate from generated records"]), - Card(304, 172, "Source-pinned projection", ["tools/build_skill_index.py", "Fixed source commit + per-file SHA256", "inferrsi..skills.*", "kind=knowledge · packaged-skill index", "Imported state belongs to the record", "Projection ≠ content authority"], "blue"), - Card(492, 145, "Explicit authorities", ["package: installed bundle, read-only", "checkout: selected root, read-only", "store: authorized local candidates", "Create / Update retain immutable history", "Adaptations need a distinct derived ID"]), - Card(653, 101, "Bundle identity contract", ["Qualified ref = :", "Metadata + content + resources", "+ dependency revisions → SHA256"], "blue"), - ], - [ - Card(185, 125, "Legacy: knowledge search", ["Catalog JSON discovery", "AND substring tokens", "Occurrence count; ties by ID", "Existing repo/backend/tier filters"]), - Card(326, 145, "Default: Collect", ["Query + metadata filters (reader API)", "Deterministic qualified-identity order", "IDs · revisions · limit · max_bytes", "No-match / omissions / collisions explicit", "Packaged material → record.json"], "green"), - Card(487, 267, "Two independent opt-ins", ["relevance: separate lexical cue", "Discovery: generated packaged skills", "4 title · 3 desc · 2 tags/applicability", "1 full core; score ↓, then qualified ref", "Ranking → item and byte limits", "Explicit IDs keep members + order", "context_bytes: explicit byte budget", "Whole-file core + required references", "Optional owner files selected by cue", "Stale projection → index_unavailable"], "green"), - ], - [ - Card(185, 125, "Exact-revision access", ["read(ref, revision) / resource(...)", "Full dependency-closed Bundle", "Ambiguous identity is an error", "Unavailable old bytes never use latest"]), - Card(326, 187, "Complete context contract", ["Full canonical SKILL.md", "+ declared refs + provenance readsets", "+ required licenses and notices", "Exact UTF-8 resource-body bytes", "Required set over budget: omit context", "Mandatory instructions never truncated", "Other links still need exact reads"], "blue"), - Card(529, 101, "Inspectable returned material", ["Ref + revision + paths + SHA256", "Sources · attribution · limitations", "Whole resources + explicit omissions"]), - Card(646, 108, "Agent chooses explicit use", ["Goal + authorization + applicability", "Read before acting; honor limitations", "Reading never executes or promotes"], "dashed"), - ], - ], - "evidence_head": "5 · RETAINED EVIDENCE & REVIEWED MAINTENANCE", - "bottom": [ - ("Frozen evidence", "Plans · results · patches · validators"), - ("Reference Matrix", "Sources · inspected scope · extraction"), - ("SearchSpace Matrix", "Resource × optimization-stage coverage"), - ("Reviewed repository changes", "Content + matrices + projection refresh"), - ], - "reference_note": "Frozen evidence: read-only references.", - "review_note": "Reviewed content + matrices; store candidates are not repository coverage.", - "legend": ["Contract", "Retrieval", "Data flow", "Reference / review"], - "footer": "InferRSI · source 4817f92121df · no automatic execution or promotion", -} - -ZH = { - "title": "InferRSI 知识库架构", - "subtitle": "规范内容源 → 构建与权威边界 → 检索 → 精确修订读取与显式使用", - "top_note": "K0/K1 内容基础 · K2 读写操作", - "heads": ["1 · 规范内容源", "2 · 构建与权威边界", "3 · 检索", "4 · 读取与使用"], - "cards": [ - [ - Card(185, 125, "完整技能库", ["SKILL.md：名称、描述与完整步骤", "metadata.json：溯源、状态与适用性", "references/ 与 cases/：归属技能本地", "保留许可证与来源清单"]), - Card(326, 120, "导入的目录来源", ["repo_packs/ + knowledge_packs/", "保留既有 ID、层级、范围与来源", "贡献对象 · 依赖对象 · 同类参考"]), - Card(462, 147, "按类型保存来源身份", ["Git 提交与已检查路径", "论文版本、文档版本或快照", "内部运行与产物身份", "来源版本 ≠ 本地内容修订", "原始证据保留于冻结产物的所有者"]), - Card(625, 129, "内容归属与验证边界", ["硬件 / 框架 / 仓库 / 方法 / 工作流", "状态 ≠ 实测验证 ≠ 使用授权", "后端适用范围 ≠ 兼容性认证", "未知来源与许可证保持未知"], "dashed"), - ], - [ - Card(185, 103, "稳定 ID 注册表", ["skill-index.json", "技能 ID → 分类路径与 backend", "与生成的目录记录是不同对象"]), - Card(304, 172, "固定来源的生成投影", ["tools/build_skill_index.py", "固定来源提交与每个文件的 SHA256", "inferrsi..skills.*", "kind=knowledge；packaged-skill 索引", "imported 描述目录记录自身状态", "生成投影 ≠ 内容权威"], "blue"), - Card(492, 145, "显式选择三类权威", ["package：已安装内容，只读", "checkout：指定技能根目录，只读", "store：获授权的本地候选内容", "Create / Update 保留不可变历史", "改编须使用不同 ID 并记录派生来源"]), - Card(653, 101, "完整包身份契约", ["限定引用：:", "元数据、正文、资源字节", "+ 依赖修订 → SHA256 内容修订"], "blue"), - ], - [ - Card(185, 125, "既有入口：knowledge search", ["对目录 JSON 进行发现检索", "AND 子串匹配", "按出现次数排序，再按 ID 排序", "保留 repo/backend/tier 等筛选"]), - Card(326, 145, "默认入口：Collect", ["查询与元数据筛选（Reader API）", "默认按限定身份确定性排序", "ID、修订、条数与 max_bytes 上限", "显式报告无匹配、遗漏和身份冲突", "包目录的 material 返回 record.json"], "green"), - Card(487, 267, "两项相互独立的可选能力", ["relevance：独立的词法提示", "发现范围仅限生成的已打包技能", "标题 4、描述 3、标签/适用范围 2", "完整核心 1；分数降序后按限定引用", "排序后施加条数与字节上限", "显式 ID 保留成员与调用者顺序", "context_bytes：显式字节预算", "完整核心与强制引用按整文件返回", "可选本地资源按提示选择", "投影过期 → index_unavailable"], "green"), - ], - [ - Card(185, 125, "读取精确内容修订", ["read(ref, revision) / resource(...)", "读取依赖闭合的完整 Bundle", "未限定的歧义身份直接报错", "旧字节不可用时不替换为最新内容"]), - Card(326, 187, "完整上下文契约", ["完整的规范 SKILL.md", "+ 已声明引用与来源检查材料", "+ 强制保留的许可证和通知", "按 UTF-8 资源正文字节计量", "必需资源超预算：仅省略上下文", "强制指令从不截断", "其他链接仍须按精确修订继续读取"], "blue"), - Card(529, 101, "可检查的返回材料", ["引用、修订、路径与 SHA256", "来源、署名和适用限制", "完整资源及显式遗漏原因"]), - Card(646, 108, "Agent 显式决定使用", ["结合目标、授权与适用条件", "先读取，再按适用限制行动", "读取不会执行内容或提升候选状态"], "dashed"), - ], - ], - "evidence_head": "5 · 冻结证据与经过审查的维护", - "bottom": [ - ("冻结的原始证据", "计划、结果、补丁与验证器"), - ("Reference Matrix", "来源、已检查范围与提取内容"), - ("SearchSpace Matrix", "资源 × 优化阶段的覆盖情况"), - ("经过审查的仓库变更", "规范内容、两个矩阵与投影刷新"), - ], - "reference_note": "冻结证据只作引用；运行时不改写。", - "review_note": "规范内容与双矩阵经审查后变更；store 候选不等于仓库覆盖。", - "legend": ["契约", "检索", "数据流", "引用 / 审查"], - "footer": "InferRSI · 来源 4817f92121df · 不自动执行或提升候选状态", -} - - -def make_svg(locale: str, copy: dict) -> tuple[str, dict]: - chinese = locale == "zh-CN" - family = "Microsoft YaHei, Noto Sans SC, Segoe UI, sans-serif" if chinese else "Segoe UI, Arial, sans-serif" - normal = ImageFont.truetype("C:/Windows/Fonts/msyh.ttc" if chinese else "C:/Windows/Fonts/segoeui.ttf", 15) - bold = ImageFont.truetype("C:/Windows/Fonts/msyhbd.ttc" if chinese else "C:/Windows/Fonts/segoeuib.ttf", 16) - pieces: list[str] = [] - audit = {"locale": locale, "width": WIDTH, "height": HEIGHT, "baseline": BASELINE, - "author_model": "gpt-6.1-sol", "author_reasoning_effort": "xhigh", "text_checks": []} - - def rect(x, y, w, h, fill, stroke, radius=9, dashed=False): - dash = ' stroke-dasharray="4 4"' if dashed else '' - pieces.append(f'') - - def text(x, y, value, size=15, color=None, weight=400, anchor="start", spacing=None): - ls = f' letter-spacing="{spacing}"' if spacing else '' - pieces.append(f'{escape(value)}') - - def path(d, color, dashed=False, marker=None, width=1.5): - dash = ' stroke-dasharray="5 5"' if dashed else '' - end = f' marker-end="url(#{marker})"' if marker else '' - pieces.append(f'') - - def card(x, w, item: Card): - special = item.style - stroke = PALETTE["blue"] if special == "blue" else PALETTE["green"] if special == "green" else PALETTE["card_stroke"] - fill = PALETTE["blue_fill"] if special == "blue" else "#ffffff" - rect(x, item.y, w, item.h, fill, stroke, dashed=special == "dashed") - title_color = PALETTE["blue_ink"] if special == "blue" else PALETTE["green_ink"] if special == "green" else PALETTE["ink"] - text(x + 16, item.y + 27, item.title, 16, title_color, 600) - title_width = bold.getlength(item.title) - assert title_width <= w - 30, (locale, item.title, title_width, w) - for i, line in enumerate(item.lines): - measured = normal.getlength(line) - assert measured <= w - 30, (locale, item.title, line, measured, w) - baseline = item.y + 48 + item.line_height * i - assert baseline + 4 <= item.y + item.h - 9, (item.title, baseline, item.y + item.h) - text(x + 16, baseline, line) - audit["text_checks"].append({"title": item.title, "line_count": len(item.lines), "title_width": round(title_width, 2), "available_width": w - 30}) - - pieces.append(f'') - pieces.append(f'{escape(copy["title"])}') - pieces.append('Canonical sources feed source-pinned generated projections and explicit read/write authorities. Legacy search, default Collect and optional lexical selection/context remain separate. Exact-revision reads return complete required resources; the agent decides authorized use. Frozen evidence and reviewed matrices retain their ownership.') - pieces.append('') - pieces.append('') - text(56, 61, copy["title"], 31, PALETTE["ink"], 650) - text(56, 94, copy["subtitle"], 16) - text(1544, 59, copy["top_note"], 14, PALETTE["muted"], anchor="end") - path("M56 113 H1544", PALETTE["panel_stroke"], width=1.2) - - columns = [(56, 330), (414, 362), (804, 358), (1190, 354)] - for index, ((x, w), heading, cards) in enumerate(zip(columns, copy["heads"], copy["cards"])): - pieces.append(f'') - rect(x, 134, w, 642, PALETTE["green_fill"] if index == 2 else PALETTE["panel"], "#b2e5c8" if index == 2 else PALETTE["panel_stroke"], radius=12) - text(x + 20, 164, heading, 14, PALETTE["green_ink"] if index == 2 else PALETTE["muted"], 600, spacing=None if chinese else 1.1) - for item in cards: - card(x + 20, w - 40, item) - pieces.append('') - - for start, end in [(386, 414), (776, 804), (1162, 1190)]: - path(f"M{start + 2} 423 H{end - 4}", PALETTE["blue"], marker="flow", width=1.7) - - path("M232 884 V821 H216 V778", PALETTE["purple"], dashed=True, marker="reference") - text(257, 826, copy["reference_note"], 15, PALETTE["purple"]) - path("M1366 884 V856 H594 V778", PALETTE["muted"], dashed=True, marker="review") - text(660, 848, copy["review_note"], 15, PALETTE["muted"]) - - pieces.append('') - rect(56, 884, 1488, 118, "#fafbfe", PALETTE["panel_stroke"], radius=12) - text(76, 912, copy["evidence_head"], 14, PALETTE["muted"], 600, spacing=None if chinese else 1.1) - for x, w, (title, detail) in zip([76, 436, 796, 1156], [344, 344, 344, 368], copy["bottom"]): - rect(x, 928, w, 56, "#ffffff", PALETTE["card_stroke"], radius=8) - text(x + 15, 950, title, 16, PALETTE["ink"], 600) - text(x + 15, 972, detail, 14) - pieces.append('') - - rect(56, 1021, 14, 11, PALETTE["blue_fill"], PALETTE["blue"], radius=2) - text(80, 1032, copy["legend"][0], 14) - rect(184, 1021, 14, 11, PALETTE["green_fill"], PALETTE["green"], radius=2) - text(208, 1032, copy["legend"][1], 14) - path("M320 1027 H354", PALETTE["blue"], width=1.7) - text(365, 1032, copy["legend"][2], 14) - path("M482 1027 H516", PALETTE["purple"], dashed=True) - text(527, 1032, copy["legend"][3], 14) - text(1544, 1032, copy["footer"], 14, PALETTE["muted"], anchor="end") - pieces.append('') - svg = "\n".join(pieces) + "\n" - ET.fromstring(svg) - return svg, audit - - -def main(): - audits = [] - for locale, copy in [("en", EN), ("zh-CN", ZH)]: - svg, audit = make_svg(locale, copy) - stem = OUT / f"inferrsi-knowledge-architecture.{locale}" - svg_path = stem.with_suffix(f".{locale}.svg") - png_path = stem.with_suffix(f".{locale}.png") - svg_path.write_text(svg, encoding="utf-8", newline="\n") - cairosvg.svg2png(bytestring=svg.encode(), write_to=str(png_path), output_width=3200, output_height=2100) - with Image.open(png_path) as rendered: - assert rendered.size == (3200, 2100) - assert rendered.getpixel((0, 0))[:3] == (255, 255, 255) - audit["svg"] = svg_path.name - audit["png"] = png_path.name - audit["render_size"] = [3200, 2100] - audits.append(audit) - print(f"Created {svg_path.name} and {png_path.name}") - (OUT / "layout-checks.json").write_text(json.dumps(audits, ensure_ascii=False, indent=2) + "\n", encoding="utf-8") - - -if __name__ == "__main__": - main() diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.png b/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.png deleted file mode 100644 index 2bfee9dae..000000000 Binary files a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.png and /dev/null differ diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.svg b/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.svg deleted file mode 100644 index 187773c7e..000000000 --- a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.en.svg +++ /dev/null @@ -1,158 +0,0 @@ - -InferRSI Knowledge Architecture -Canonical sources feed source-pinned generated projections and explicit read/write authorities. Legacy search, default Collect and optional lexical selection/context remain separate. Exact-revision reads return complete required resources; the agent decides authorized use. Frozen evidence and reviewed matrices retain their ownership. - - -InferRSI Knowledge Architecture -Canonical sources → build & authorities → retrieval → exact reads & explicit use -K0/K1 foundation · K2 operations - - - -1 · CANONICAL SOURCES - -Complete skill library -SKILL.md: name + procedure -metadata.json: state + applicability -references/ + cases/: owner-local -Licenses and source inventories - -Imported catalog sources -repo_packs/ + knowledge_packs/ -Existing IDs, tiers, scope and sources -Contribution · dependency · peer - -Typed source identities -Git commit + inspected paths -Paper version · document snapshot -Internal run + artifact identity -Source pin ≠ content revision -Frozen evidence stays at its owner - -Ownership and qualification -hardware/ · frameworks/ -repositories/ · methods/ · workflows/ -State ≠ validation ≠ permission -Backend scope ≠ compatibility -Unknown provenance/licenses retained - - - -2 · BUILD & AUTHORITIES - -Stable-ID registry -skill-index.json -Skill IDs → paths + backend -Separate from generated records - -Source-pinned projection -tools/build_skill_index.py -Fixed source commit + per-file SHA256 -inferrsi.<backend>.skills.* -kind=knowledge · packaged-skill index -Imported state belongs to the record -Projection ≠ content authority - -Explicit authorities -package: installed bundle, read-only -checkout: selected root, read-only -store: authorized local candidates -Create / Update retain immutable history -Adaptations need a distinct derived ID - -Bundle identity contract -Qualified ref = <authority>:<id> -Metadata + content + resources -+ dependency revisions → SHA256 - - - -3 · RETRIEVAL - -Legacy: knowledge search -Catalog JSON discovery -AND substring tokens -Occurrence count; ties by ID -Existing repo/backend/tier filters - -Default: Collect -Query + metadata filters (reader API) -Deterministic qualified-identity order -IDs · revisions · limit · max_bytes -No-match / omissions / collisions explicit -Packaged material → record.json - -Two independent opt-ins -relevance: separate lexical cue -Discovery: generated packaged skills -4 title · 3 desc · 2 tags/applicability -1 full core; score ↓, then qualified ref -Ranking → item and byte limits -Explicit IDs keep members + order -context_bytes: explicit byte budget -Whole-file core + required references -Optional owner files selected by cue -Stale projection → index_unavailable - - - -4 · READ & USE - -Exact-revision access -read(ref, revision) / resource(...) -Full dependency-closed Bundle -Ambiguous identity is an error -Unavailable old bytes never use latest - -Complete context contract -Full canonical SKILL.md -+ declared refs + provenance readsets -+ required licenses and notices -Exact UTF-8 resource-body bytes -Required set over budget: omit context -Mandatory instructions never truncated -Other links still need exact reads - -Inspectable returned material -Ref + revision + paths + SHA256 -Sources · attribution · limitations -Whole resources + explicit omissions - -Agent chooses explicit use -Goal + authorization + applicability -Read before acting; honor limitations -Reading never executes or promotes - - - - - -Frozen evidence: read-only references. - -Reviewed content + matrices; store candidates are not repository coverage. - - -5 · RETAINED EVIDENCE & REVIEWED MAINTENANCE - -Frozen evidence -Plans · results · patches · validators - -Reference Matrix -Sources · inspected scope · extraction - -SearchSpace Matrix -Resource × optimization-stage coverage - -Reviewed repository changes -Content + matrices + projection refresh - - -Contract - -Retrieval - -Data flow - -Reference / review -InferRSI · source 4817f92121df · no automatic execution or promotion - diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.png b/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.png deleted file mode 100644 index 362352b83..000000000 Binary files a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.png and /dev/null differ diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.svg b/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.svg deleted file mode 100644 index 3182564e4..000000000 --- a/evidence/knowledge-retrieval-20261027/results/architecture/inferrsi-knowledge-architecture.zh-CN.svg +++ /dev/null @@ -1,157 +0,0 @@ - -InferRSI 知识库架构 -Canonical sources feed source-pinned generated projections and explicit read/write authorities. Legacy search, default Collect and optional lexical selection/context remain separate. Exact-revision reads return complete required resources; the agent decides authorized use. Frozen evidence and reviewed matrices retain their ownership. - - -InferRSI 知识库架构 -规范内容源 → 构建与权威边界 → 检索 → 精确修订读取与显式使用 -K0/K1 内容基础 · K2 读写操作 - - - -1 · 规范内容源 - -完整技能库 -SKILL.md：名称、描述与完整步骤 -metadata.json：溯源、状态与适用性 -references/ 与 cases/：归属技能本地 -保留许可证与来源清单 - -导入的目录来源 -repo_packs/ + knowledge_packs/ -保留既有 ID、层级、范围与来源 -贡献对象 · 依赖对象 · 同类参考 - -按类型保存来源身份 -Git 提交与已检查路径 -论文版本、文档版本或快照 -内部运行与产物身份 -来源版本 ≠ 本地内容修订 -原始证据保留于冻结产物的所有者 - -内容归属与验证边界 -硬件 / 框架 / 仓库 / 方法 / 工作流 -状态 ≠ 实测验证 ≠ 使用授权 -后端适用范围 ≠ 兼容性认证 -未知来源与许可证保持未知 - - - -2 · 构建与权威边界 - -稳定 ID 注册表 -skill-index.json -技能 ID → 分类路径与 backend -与生成的目录记录是不同对象 - -固定来源的生成投影 -tools/build_skill_index.py -固定来源提交与每个文件的 SHA256 -inferrsi.<backend>.skills.* -kind=knowledge；packaged-skill 索引 -imported 描述目录记录自身状态 -生成投影 ≠ 内容权威 - -显式选择三类权威 -package：已安装内容，只读 -checkout：指定技能根目录，只读 -store：获授权的本地候选内容 -Create / Update 保留不可变历史 -改编须使用不同 ID 并记录派生来源 - -完整包身份契约 -限定引用：<authority>:<id> -元数据、正文、资源字节 -+ 依赖修订 → SHA256 内容修订 - - - -3 · 检索 - -既有入口：knowledge search -对目录 JSON 进行发现检索 -AND 子串匹配 -按出现次数排序，再按 ID 排序 -保留 repo/backend/tier 等筛选 - -默认入口：Collect -查询与元数据筛选（Reader API） -默认按限定身份确定性排序 -ID、修订、条数与 max_bytes 上限 -显式报告无匹配、遗漏和身份冲突 -包目录的 material 返回 record.json - -两项相互独立的可选能力 -relevance：独立的词法提示 -发现范围仅限生成的已打包技能 -标题 4、描述 3、标签/适用范围 2 -完整核心 1；分数降序后按限定引用 -排序后施加条数与字节上限 -显式 ID 保留成员与调用者顺序 -context_bytes：显式字节预算 -完整核心与强制引用按整文件返回 -可选本地资源按提示选择 -投影过期 → index_unavailable - - - -4 · 读取与使用 - -读取精确内容修订 -read(ref, revision) / resource(...) -读取依赖闭合的完整 Bundle -未限定的歧义身份直接报错 -旧字节不可用时不替换为最新内容 - -完整上下文契约 -完整的规范 SKILL.md -+ 已声明引用与来源检查材料 -+ 强制保留的许可证和通知 -按 UTF-8 资源正文字节计量 -必需资源超预算：仅省略上下文 -强制指令从不截断 -其他链接仍须按精确修订继续读取 - -可检查的返回材料 -引用、修订、路径与 SHA256 -来源、署名和适用限制 -完整资源及显式遗漏原因 - -Agent 显式决定使用 -结合目标、授权与适用条件 -先读取，再按适用限制行动 -读取不会执行内容或提升候选状态 - - - - - -冻结证据只作引用；运行时不改写。 - -规范内容与双矩阵经审查后变更；store 候选不等于仓库覆盖。 - - -5 · 冻结证据与经过审查的维护 - -冻结的原始证据 -计划、结果、补丁与验证器 - -Reference Matrix -来源、已检查范围与提取内容 - -SearchSpace Matrix -资源 × 优化阶段的覆盖情况 - -经过审查的仓库变更 -规范内容、两个矩阵与投影刷新 - - -契约 - -检索 - -数据流 - -引用 / 审查 -InferRSI · 来源 4817f92121df · 不自动执行或提升候选状态 - diff --git a/evidence/knowledge-retrieval-20261027/results/architecture/layout-checks.json b/evidence/knowledge-retrieval-20261027/results/architecture/layout-checks.json deleted file mode 100644 index de3298712..000000000 --- a/evidence/knowledge-retrieval-20261027/results/architecture/layout-checks.json +++ /dev/null @@ -1,214 +0,0 @@ -[ - 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Clock/power state and unrelated background load are not held -constant by this evaluator. Twenty sequential paired groups alternate AB/BA; -there are no concurrent baseline/candidate workers. The formal benchmark starts -after software tests, quality comparison and diagram rendering finish. Their -durations are excluded from the latency observations. - -Each result's identity section is authoritative for the actual Python version, -implementation, executable-binary digest, source revision, imported modules, -optimization flags and full source/corpus inventories. Both variants must use -the same interpreter and complete corpus. No personal path, hostname or network -address is needed in these shared records. - -The completed formal runs used CPython 3.12.6 with site initializers disabled -and optimization flag zero on both sides. Their snapshots cover 53 Python -source files and 458 corpus files / 2,883,003 bytes, including 108 knowledge -records and the 342-file / 2,294,958-byte shared library. - -Fresh-reader API measurements construct a new KnowledgeReader; reused-reader -measurements follow the frozen warmup. Every CLI measurement starts a fresh -Python process. The OS filesystem cache is uncontrolled and is not claimed -cold. API wall time, full CLI startup/capture and output decoding are distinct -measurements. This CPU-only experiment runs no model or inference service and -establishes no GPU, service, task-quality or production-distribution benefit. diff --git a/evidence/knowledge-retrieval-20261027/results/independent-review.md b/evidence/knowledge-retrieval-20261027/results/independent-review.md deleted file mode 100644 index 4bd18d0d1..000000000 --- a/evidence/knowledge-retrieval-20261027/results/independent-review.md +++ /dev/null @@ -1,22 +0,0 @@ -# Independent read-only review record - -The accountable orchestrator coordinated independent read-only reviewers and -relayed the findings recorded here. Their model/effort settings are **unknown**; -they made no material repository edits and are not listed as material authors. -This record is not human/maintainer goal acceptance or merge/closure authority. - -| Scope | Observed review result | -| --- | --- | -| Validator before formal measurement | Review found positional truncation could hide missing rows and Python assertions could be disabled. Authors corrected both before candidate measurement; v1 freeze and the prospective amendment remain preserved. The current v2 freeze is `a465367319f3058398eb1f8579ee5d4174b8cb90457793e90788fb5796151057`. | -| Runtime/integrity boundary | Review retained per-call mutation/revision validation and the bounded digest/path reuse scope. Relevant regression checks passed; full Windows suite failures and their baseline reproduction remain qualified. | -| Quality | Review checked 96 exact outputs per revision, unchanged source/corpus identity and item metrics. It separately found labelled-owner contexts present for 19/20 positives, including the 170,782-byte required set omitted against the 65,536-byte budget. | -| Benchmark | Independent recomputation reproduced 20 pairs, ten AB/ten BA, 640 API calls, 160 CLI processes, all 400 cross-version output pairs and 80 exact stdout pairs, all 48 side-specific p50/p95 groups, and the exact 40.0068267% reduction / [38.3789227%, 41.0592071%] bootstrap interval. All 53 source and 458 corpus file identities matched. | -| Regressions and interpretation | Review required retaining API/CLI search p50 regressions and CLI relevance decode p95 1.810→3.046 ms (+1.236 ms), with no inferred cause or blanket tail-latency claim. Each group has 20 repeats; four hot query types remain four query types. | -| Diagrams | Final editable EN/ZH diagrams were reviewed. The English required-set budget wording was corrected; final previews were clear and the Chinese figure content was unchanged. | -| Evidence registration | The minimal nested bundle hash selector retained safe-path/digest checks. Correct/tampered/missing/nonobject field regressions passed; inventory check reported 9 bundles/120 hashes and no errors. | - -The frozen software parity and local CPU performance gates passed. The local -whole-suite run remains failed with its initial failures/errors reproduced on -baseline. Remote CI is pending at PR creation, and human/maintainer acceptance -has not been recorded. Goal acceptance, merge and Issue closure remain with the -authorized requester/repository maintainers. diff --git a/evidence/knowledge-retrieval-20261027/results/latency-summary.json b/evidence/knowledge-retrieval-20261027/results/latency-summary.json deleted file mode 100644 index 22efe4295..000000000 --- a/evidence/knowledge-retrieval-20261027/results/latency-summary.json +++ /dev/null @@ -1,533 +0,0 @@ -{ - "schema_version": 1, - "source": "benchmark.json", - "source_sha256": "85cf49d3bc96df35763f3997abd5af72a5f580787fe952420a56e764fbb5bc89", - "analysis": "Post-measurement display of every frozen per-mode/query summary; no new acceptance gate.", - "positive_delta_means": "candidate slower", - "rows": [ - { - "interface": "api", - "mode": "cold_context_material", - "case": "dev09", - "timer": "call_ns", - "n_baseline": 20, - "n_candidate": 20, - "baseline_ns": { - "p50": 1060605750.0, - "p95": 1570935585.0 - }, - "candidate_ns": { - "p50": 686351850.0, - "p95": 885685090.0000001 - }, - 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0.39935868451070977, - 0.4681914863937914, - 0.39654425028446916, - 0.3316604754684327, - 0.363968338719332, - 0.39880913457301126 - ], - "bootstrap": { - "method": "percentile bootstrap of paired reductions; each draw samples 20 reductions with replacement, then computes their median", - "iterations": 10000, - "seed": 19020261027, - "confidence": 0.95, - "quantiles": [ - 0.025, - 0.975 - ], - "quantile_method": "linear interpolation at (n-1)*p" - } - } -} diff --git a/evidence/knowledge-retrieval-20261027/results/performance.md b/evidence/knowledge-retrieval-20261027/results/performance.md deleted file mode 100644 index a16364b1a..000000000 --- a/evidence/knowledge-retrieval-20261027/results/performance.md +++ /dev/null @@ -1,94 +0,0 @@ -# CPU offline retrieval performance - -The [frozen protocol](../plan/protocol.json) -used **20 paired groups**, ten AB and ten BA, over four fixed development cues: -`dev01`, `dev05`, `dev09` and `dev13`. Repeats do not add query types. Each side -ran in an isolated source-selected subprocess using CPython **3.12.6** with -site initializers disabled; import origins and complete source/corpus digests -were checked. The corpus contained **108 records**, including **60 generated -packaged skills**, within **458 evaluated corpus files / 2,883,003 bytes**. -The shared library accounted for **342 files / 2,294,958 bytes**. There were -**53 Python source files** in the source identity snapshot. - -Hardware was an Intel Core i7-8565U, four physical/eight logical cores, -15.8 GiB RAM, Windows 10 Pro 10.0.19045. Clock/power state and unrelated -background load were uncontrolled; the CPU inventory's 1.80 GHz is not a -clock-lock observation. Fresh-reader calls include constructing a new reader; -hot calls reuse one reader after the fixed warmup. Neither establishes a cold -OS filesystem cache. CLI process/capture time and UTF-8 decode/JSON parse time -are measured separately. Collect CLI lacks the API's repo/backend filters, so -its wider-scope costs are diagnostics, not part of the fair scoped API gate. - -For each pair, the estimator takes the median of its four hot-query latencies -on each revision and computes `1 - candidate_median / baseline_median`; the -primary estimate is the median of those 20 reductions. The frozen 10,000-draw -percentile bootstrap resamples complete paired groups with seed `19020261027`. -The observed reduction is **40.0068267%**, with 95% interval -**[38.3789227%, 41.0592071%]**. This satisfies the prospective issue bar of at -least 20% paired-median reduction and a lower 95% bound above zero. It is an -offline CPU retrieval result for this corpus, interpreter, machine and workload. - -The measurement loop retained **640 API calls and 160 CLI processes** over -**836.162 seconds**; preflight/final inventory work is outside that elapsed -counter. All **400 cross-version output pairs**, including **80 exact CLI -stdout pairs**, preserved their digests. Complete measurement sets and final -source/corpus identities passed. Independent read-only review reproduced all -48 side-specific p50/p95 groups and the exact primary/bootstrap numbers from -the raw observations. - -Regressions remain visible: API search `dev01` p50 rose **31.409 → 31.782 ms -(+1.19%)**, and CLI search `dev05` p50 rose **340.560 → 349.067 ms (+2.50%)**. -CLI relevance decode p95 rose **1.810 → 3.046 ms**, an absolute increase of -**1.236 ms (+68.31%)**. These observations do not establish a cause. Individual -rows are descriptive; no per-row significance gate was prespecified. Each p95 -below is a sample quantile from **20 repeats per revision**, not a service tail -guarantee or evidence for additional query populations. - -Every measured mode/query appears below. Values are milliseconds; positive -deltas mean the candidate was slower. The complete exact-nanosecond summaries -are in [latency-summary.json](latency-summary.json), -with all raw samples and output hashes in -[benchmark.json](benchmark.json). -The baseline [profile](baseline-profile.json) -and [#129 trace](baseline-trace-129.json) -are separate diagnostics excluded from the timing samples. No model, GPU, -inference-service or real-agent-task comparison ran. - -### API call wall time - -| Mode / case | Baseline p50 | Candidate p50 | Delta p50 | Baseline p95 | Candidate p95 | Delta p95 | -| --- | --- | --- | --- | --- | --- | --- | -| `cold_context_material` / `dev09` | 1060.606 | 686.352 | -35.29% | 1570.936 | 885.685 | -43.62% | -| `cold_default_diagnostic` / `dev05` | 999.688 | 614.151 | -38.57% | 1657.808 | 741.097 | -55.30% | -| `cold_relevance` / `dev01` | 1141.533 | 788.233 | -30.95% | 1427.484 | 1146.733 | -19.67% | -| `cold_relevance` / `dev05` | 1061.825 | 683.019 | -35.67% | 1247.372 | 817.370 | -34.47% | -| `cold_relevance` / `dev09` | 1083.634 | 680.551 | -37.20% | 1901.819 | 872.078 | -54.15% | -| `cold_relevance` / `dev13` | 1057.574 | 677.726 | -35.92% | 1766.674 | 844.748 | -52.18% | -| `hot_context_material` / `dev09` | 944.589 | 577.180 | -38.90% | 1495.627 | 780.720 | -47.80% | -| `hot_default_diagnostic` / `dev05` | 882.934 | 504.028 | -42.91% | 1529.218 | 640.953 | -58.09% | -| `hot_relevance` / `dev01` | 1021.204 | 663.073 | -35.07% | 1317.269 | 910.342 | -30.89% | -| `hot_relevance` / `dev05` | 938.521 | 579.671 | -38.24% | 1226.804 | 879.716 | -28.29% | -| `hot_relevance` / `dev09` | 957.842 | 577.391 | -39.72% | 1702.202 | 725.926 | -57.35% | -| `hot_relevance` / `dev13` | 949.685 | 566.260 | -40.37% | 1935.473 | 806.471 | -58.33% | -| `search` / `dev01` | 31.409 | 31.782 | +1.19% | 54.012 | 53.470 | -1.00% | -| `search` / `dev05` | 31.935 | 31.307 | -1.96% | 39.201 | 38.680 | -1.33% | -| `search` / `dev09` | 31.590 | 31.506 | -0.27% | 54.718 | 46.758 | -14.55% | -| `search` / `dev13` | 31.385 | 31.159 | -0.72% | 65.095 | 40.073 | -38.44% | - -### Full CLI process plus stdout capture - -| Mode / case | Baseline p50 | Candidate p50 | Delta p50 | Baseline p95 | Candidate p95 | Delta p95 | -| --- | --- | --- | --- | --- | --- | --- | -| `context_material` / `dev09` | 1413.646 | 1017.286 | -28.04% | 2644.763 | 1423.810 | -46.16% | -| `default_diagnostic` / `dev05` | 1613.022 | 1103.381 | -31.60% | 2133.128 | 1382.574 | -35.19% | -| `relevance` / `dev05` | 1413.156 | 998.828 | -29.32% | 1718.849 | 1369.453 | -20.33% | -| `search` / `dev05` | 340.560 | 349.067 | +2.50% | 487.368 | 451.238 | -7.41% | - -### CLI UTF-8 decode and JSON parse - -| Mode / case | Baseline p50 | Candidate p50 | Delta p50 | Baseline p95 | Candidate p95 | Delta p95 | -| --- | --- | --- | --- | --- | --- | --- | -| `context_material` / `dev09` | 3.289 | 3.296 | +0.19% | 5.639 | 4.242 | -24.78% | -| `default_diagnostic` / `dev05` | 0.022 | 0.022 | -0.45% | 0.030 | 0.032 | +6.81% | -| `relevance` / `dev05` | 1.532 | 1.537 | +0.34% | 1.810 | 3.046 | +68.31% | -| `search` / `dev05` | 0.012 | 0.013 | +2.42% | 0.016 | 0.014 | -11.16% | diff --git a/evidence/knowledge-retrieval-20261027/results/quality.json b/evidence/knowledge-retrieval-20261027/results/quality.json deleted file mode 100644 index c06f2743a..000000000 --- a/evidence/knowledge-retrieval-20261027/results/quality.json +++ /dev/null @@ -1,29464 +0,0 @@ -{ - 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}, - "all/context_material": { - "answerable_count": 20, - "success_at_5": 1, - "mrr_at_5": 0.9625, - "negative_count": 4, - "negative_empty_count": 2 - }, - "all/default_diagnostic": { - "answerable_count": 20, - "success_at_5": 0.2, - "mrr_at_5": 0.2, - "negative_count": 4, - "negative_empty_count": 4 - } - } - }, - "measurement_structure_errors": {}, - "parity_failures": [], - "source_and_corpus_unchanged_at_end": { - "A": true, - "B": true - }, - "completed_at_utc": "2026-10-27T11:29:09.151662+00:00" -} diff --git a/evidence/knowledge-retrieval-20261027/results/validation-summary.md b/evidence/knowledge-retrieval-20261027/results/validation-summary.md deleted file mode 100644 index 4b7265ad1..000000000 --- a/evidence/knowledge-retrieval-20261027/results/validation-summary.md +++ /dev/null @@ -1,46 +0,0 @@ -# Local software and package validation - -These are software checks reported by the accountable orchestrator for the -fixed runtime candidate, separate from the frozen CPU retrieval experiment. -This summary deliberately excludes private local paths and raw command logs. - -| Check | Actual result and qualification | -| --- | --- | -| Whole local pytest run | **10 failed, 1,340 passed, 6 skipped, 2 errors, 135 subtests passed**, 953.11 seconds. This is a failed whole-suite run, not a green suite. | -| Focused failure recheck | The same eleven selected failing/erroring test functions, including parameter variants, were rerun separately on baseline and candidate. Each reported **9 failed, 4 passed, 3 errors**. The CRLF case was then isolated from earlier fixture pollution: both sides reported **1 failed, 1 passed**, with `ValueError: Skill metadata must remain unchanged`. All initial **10 failures and 2 errors** were thereby reproduced on the baseline; neither run becomes a passing whole suite. | -| Manifest regressions | All 20 newly added manifest tests passed in the local suite. The runtime author separately reported **80 targeted tests passed**; a separate selected baseline run reported **104 passed**. These scopes are distinct from whole-suite status. | -| Wheel and sdist | Default isolated builds succeeded. An earlier `--no-isolation` attempt failed because setuptools was unavailable in that environment; later isolated build success supersedes that build attempt, not the failed pytest run. | -| Installed artifact contents | All **469 packaged data files** matched the source byte-for-byte, and packaged runtime source matched the evaluated source. Wheel SHA-256: `4da1447422e5690573028373bda9baf8ab54b177031d7ba3d17586cb0533822d`. | -| Evaluation validator | Normal and optimized-Python synthetic selfchecks passed. Explicit source-label checks rejected an absent support marker under `-O`. Exact measurement-set checks reject missing/duplicate rows and pairs. Original two-pair baseline-v-baseline mechanics data passed the revised structural/parity recheck; these remain dry-run evidence. | - -The orchestrator classified the local failures by their observed boundaries: -oversized parametrized pytest names exceeding Windows' 32,767-character -environment-variable limit; GBK decoding; four cases needing unavailable Bash; -two Windows short/long temporary-path cases; one asset-manifest snapshot case; -and a process-control case using unavailable `os.getpgrp`. The CRLF delimiter -harness case failed in the initial whole run, but produced a fixture teardown -error in the focused reruns after earlier fixture pollution. Preserve that -status difference rather than treating the focused counts as an identical -repetition of the initial run. Its subsequent isolated two-case rerun restored -the original failing behavior on both revisions. Those isolated test durations -are software-test execution time and are excluded from retrieval performance. - -The candidate and baseline focused rechecks establish reproducibility of those -initial failures in this local environment. They do not establish Linux CI, -all-platform portability or untested application behavior. A clean supported -Linux environment should rerun the full suite, especially the shell/process, -path and fixture-sensitive tests. CI status and revision-scoped independent -review must be reported separately when available. - -After evidence integration, **23 inventory tests passed** in 1.10 seconds; the -read-only inventory checker reported **no errors, 9 bundles and 120 hashes**. -`ruff check src tests tools` passed. A wheel-only, site-disabled smoke read -108 records and reproduced all four `DefaultStager` output hashes from the -formal candidate result. Its first harness attempt failed an unresolved -temporary short-path import-origin check before retrieval. Resolving the -expected path allowed the smoke to pass; that retry established no package -defect. Remote CI is pending at PR creation. - -The complete 24-case and 20-pair formal results are retained separately in -`quality.json` and `benchmark.json`; both frozen gates passed. Software-check -counts, package hashes and dry-run timings remain distinct from those results. diff --git a/evidence/knowledge-retrieval-20261027/results/validator-selfcheck.json b/evidence/knowledge-retrieval-20261027/results/validator-selfcheck.json deleted file mode 100644 index 92828a172..000000000 --- a/evidence/knowledge-retrieval-20261027/results/validator-selfcheck.json +++ /dev/null @@ -1,4 +0,0 @@ -{ - "selfcheck": "passed", - "entry_python_optimization": 1 -} diff --git a/evidence/knowledge-retrieval-20261027/validator/README.md b/evidence/knowledge-retrieval-20261027/validator/README.md deleted file mode 100644 index ead53dc63..000000000 --- a/evidence/knowledge-retrieval-20261027/validator/README.md +++ /dev/null @@ -1,82 +0,0 @@ -# Reproduce the bounded offline evaluation - -Only Python's standard library is required. Run the script using the same -interpreter for both source checkouts. Commands below use operator-supplied -paths rather than relying on a live main branch or an editable installation. -Do not install or modify either evaluated checkout during a run. - -```text -python -S validator/evaluate.py selfcheck -python -S validator/evaluate.py validate --source --dry-run -python -S validator/evaluate.py identity --source --dry-run --output results/baseline-identity.json -``` - -Identity JSON records the complete `python_sources.sha256`, the actual imported -module paths relative to the checkout, their byte hashes, exact Git revision, -complete corpus inventory and count, library bytes and Python/OS fields without -personal absolute paths or host names. It uses `-S` and prepends the explicit -checkout's `src` to exclude editable-install hooks. CLI subprocesses run the -supported `python -S -m inferrsi` entrypoint under that same source selection. - -Before formal work, freeze the packet once, then obtain candidate identity: - -```text -python -S validator/evaluate.py freeze -python -S validator/evaluate.py check-freeze -python -S validator/evaluate.py identity --source --output results/candidate-identity.json -``` - -Copy `git_head` and `python_sources.sha256` from that identity. Candidate source -and revision, equal complete corpus and all frozen files are checked before -candidate retrieval/timing. Uncommitted tracked runtime sources are rejected. -Paths are accepted locally but are not saved in shared results. The optional -`--python ` selects the worker/CLI interpreter explicitly. - -```text -python -S validator/evaluate.py profile --source --output results/baseline-profile.json -python -S validator/evaluate.py trace --source --output results/baseline-trace-129.json -python -S validator/evaluate.py quality --baseline --candidate --candidate-sha --candidate-source-sha --split all --output results/quality.json -python -S validator/evaluate.py bench --baseline --candidate --candidate-sha --candidate-source-sha --output results/benchmark.json -``` - -The withheld fixture must stay sealed from runtime author and orchestrator until -the runtime candidate revision/source identity is fixed. Only `quality --split -all` opens it, after the source preflight. Profile and runtime trace use fixed -development cases. Trace covers the distinct catalog/default/relevance/context -code paths introduced or retained by merged #129; it makes no claim about that -earlier campaign's agent-task result. - -For a mechanics check only, use baseline for both roots with its revision and -source digest, `quality --dry-run --case-limit 2` and `bench --dry-run --pairs 2`. -Dry runs cannot open the withheld split and always remain INCONCLUSIVE. Keep -their files separate from formal results. There is no formal sample-count -override: changing it requires a new prospective protocol and freeze record. - -Benchmark writes every completed side to the output file immediately, retaining -partial samples with INCONCLUSIVE status if interrupted. Do not pool retries or -partial runs. A complete run stores 20 pairs, ten AB and ten BA, raw API/CLI -nanoseconds, byte-equivalence digests, p50/p95 and the frozen bootstrap result. -Actual duration is recorded; the protocol's duration estimate is not a cutoff. -The script's benchmark PASS means only that its complete timing/parity gate -passed. Overall campaign acceptance also requires full 24-case quality parity, -runtime integrity tests and independent review. - -Completeness is checked by exact case/mode sets and pair IDs/orders, including -duplicates and extras, rather than positional truncation. Missing or malformed -measurement sets remain INCONCLUSIVE. Critical checks use explicit exceptions, -so optimized Python cannot remove them; workers/CLI clear PYTHONOPTIMIZE and -record optimization flags. See `plan/amendment-1.md` for the prospective review -correction and preserved, unmeasured first freeze. - -Canonical digests cover full serializations including every resource hash and -omission. Readable projections retain ordered IDs, exact revisions, inventory -hashes/counts, context resource roles/hashes, omissions and material/context -budgets without duplicating whole library bodies per query. Full CLI captures -also retain the exact stdout byte count/hash and separate UTF-8 decode/JSON parse -time. Catalog search is token-AND; relevance collect is weighted lexical. Their -quality scores are reported independently, not as interchangeable algorithms. - -`freeze.json` commits exact bytes, so CRLF normalization, BOM insertion or any -script/fixture edit invalidates the packet. Preserve bytes when copying it into -the evidence tree. An intentional revision needs a new freeze and documented -supersession rather than replacing prior measured evidence. diff --git a/evidence/knowledge-retrieval-20261027/validator/development.json b/evidence/knowledge-retrieval-20261027/validator/development.json deleted file mode 100644 index 2097991cb..000000000 --- a/evidence/knowledge-retrieval-20261027/validator/development.json +++ /dev/null @@ -1,23 +0,0 @@ -{ - "schema_version": 1, - "split": "development", - "construction": "Source-content-first synthetic questions. Labels were chosen from original shipped procedures before running either retrieval entrypoint. Labels are partial relevance judgements, not an exhaustive corpus annotation.", - "cases": [ - {"id": "dev01", "category": "natural-language", "cue": "Why must checkpoint upload finish before cached staging buffers can be reused?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.dcp_async_save_performance", "source": "src/inferrsi/data/skill_library/frameworks/pytorch/dcp-async-save-performance/SKILL.md", "support": "upload\ncompletion", "rationale": "The lifetime contract distinguishes staging completion from the upload completion needed to reuse cached CPU storage."}]}, - {"id": "dev02", "category": "symbol", "cue": "DefaultStager", "backend": null, "relevant": [{"id": "inferrsi.common.skills.dcp_async_save_performance", "source": "src/inferrsi/data/skill_library/frameworks/pytorch/dcp-async-save-performance/SKILL.md", "support": "DefaultStager", "rationale": "The procedure states DefaultStager version gates, one-worker behavior and cached-storage reuse constraints."}]}, - {"id": "dev03", "category": "multi-term", "cue": "safetensors index sharded downloads", "backend": null, "relevant": [{"id": "inferrsi.common.skills.weight_loading_optimization", "source": "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md", "support": "weight_map", "rationale": "The weight acquisition section verifies downloaded shards against index weight_map keys and distinguishes incomplete files."}]}, - {"id": "dev04", "category": "natural-language", "cue": "How should model loading overhead be separated from per request latency?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.weight_loading_optimization", "source": "src/inferrsi/data/skill_library/methods/weight-loading-optimization/SKILL.md", "support": "Fixed vs per-request split", "rationale": "Its startup accounting procedure separates once-per-process loading/warmup from per-request execution."}]}, - {"id": "dev05", "category": "multi-term", "cue": "fio iodepth achieved depth", "backend": null, "relevant": [{"id": "inferrsi.common.skills.storage_io_measurement", "source": "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md", "support": "Requested versus achieved concurrency", "rationale": "The storage method requires validating achieved I/O depth and explains synchronous/buffered-engine limitations."}]}, - {"id": "dev06", "category": "natural-language", "cue": "How can I attribute disk traffic to the loader process rather than the whole device?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.storage_io_measurement", "source": "src/inferrsi/data/skill_library/hardware/host/storage-io-measurement/SKILL.md", "support": "pidstat", "rationale": "The skill separates per-device iostat measurements from per-process pidstat attribution and application outcomes."}]}, - {"id": "dev07", "category": "backend-filter", "cue": "UB split buffer branch matrix", "backend": "ascend", "relevant": [{"id": "inferrsi.ascend.skills.ascendc_tiling_design", "source": "src/inferrsi/data/skill_library/hardware/ascend/ascendc-tiling-design/SKILL.md", "support": "Universal four-element template", "rationale": "The AscendC design procedure explicitly enumerates multi-core split, UB split, buffer plan and branch matrix."}]}, - {"id": "dev08", "category": "backend-symbol", "cue": "multi_stream_lazy_reclaim", "backend": "ascend", "relevant": [{"id": "inferrsi.ascend.skills.torchnpu_device_memory_lifecycle", "source": "src/inferrsi/data/skill_library/hardware/ascend/torchnpu-device-memory-lifecycle/SKILL.md", "support": "multi_stream_lazy_reclaim", "rationale": "The source-derived allocator procedure explains the option's event-query tradeoff and retained-HBM verification."}]}, - {"id": "dev09", "category": "multi-term", "cue": "LMCache skip_l1 retain", "backend": null, "relevant": [{"id": "inferrsi.common.skills.kv_tier_management", "source": "src/inferrsi/data/skill_library/repositories/lmcache/kv-tier-management/SKILL.md", "support": "skip_l1", "rationale": "The MP-mode procedure contrasts L1 store deletion with retained prefetched keys and describes their RAM costs."}]}, - {"id": "dev10", "category": "symbol", "cue": "find_latest", "backend": null, "relevant": [{"id": "inferrsi.common.skills.checkpoint_recovery_consistency", "source": "src/inferrsi/data/skill_library/methods/checkpoint-recovery-consistency/SKILL.md", "support": "find_latest()", "rationale": "The recovery procedure describes selecting a complete global iteration using find_latest and complete rank coverage."}]}, - {"id": "dev11", "category": "backend-natural", "cue": "Why can larger attention tiles cause register spills and lower parallelism?", "backend": "cuda", "relevant": [{"id": "inferrsi.cuda.skills.diagnose_attention_bottlenecks", "source": "src/inferrsi/data/skill_library/hardware/cuda/diagnose-attention-bottlenecks/SKILL.md", "support": "Tune tile size against resource ceilings", "rationale": "The attention diagnosis weighs reduced IO against register/shared-memory demand, occupancy and spills."}]}, - {"id": "dev12", "category": "backend-filter", "cue": "NUMA CPU affinity placement", "backend": "cpu", "relevant": [{"id": "inferrsi.common.skills.os_process_placement", "source": "src/inferrsi/data/skill_library/hardware/host/os-process-placement/SKILL.md", "support": "CPU affinity: check, then pin", "rationale": "The common host procedure explains NUMA-local process placement, affinity checking and constant placement during comparisons."}]}, - {"id": "dev13", "category": "multi-term", "cue": "gradient activation recomputation residency", "backend": null, "relevant": [{"id": "inferrsi.common.skills.plan_activation_residency", "source": "src/inferrsi/data/skill_library/methods/plan-activation-residency/SKILL.md", "support": "selective retention/recomputation", "rationale": "This procedure compares lifetime reordering, address packing and selective activation recomputation under a legal training DAG."}]}, - {"id": "dev14", "category": "natural-language", "cue": "When does missing validator freeze make a performance claim inconclusive?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.claim_contract", "source": "src/inferrsi/data/skill_library/workflows/claim-contract/SKILL.md", "support": "missing validator freeze", "rationale": "The claim contract explicitly assigns INCONCLUSIVE when a comparison lacks the validator freeze or other essential evidence."}]}, - {"id": "dev15", "category": "no-answer-nonce", "cue": "quasarbanjo xenofloral v7", "backend": null, "relevant": [], "no_answer_rationale": "Constructed nonce identifiers have no intended systems-library answer; report actual returned items separately, not as recall."}, - {"id": "dev16", "category": "no-answer-domain", "cue": "sourdough levain hydration recipe", "backend": "cpu", "relevant": [], "no_answer_rationale": "A constructed cooking request outside this inference/training procedures corpus; this is a labelled negative probe, not proof of exhaustive semantic absence."} - ] -} diff --git a/evidence/knowledge-retrieval-20261027/validator/evaluate.py b/evidence/knowledge-retrieval-20261027/validator/evaluate.py deleted file mode 100644 index d9f02c02d..000000000 --- a/evidence/knowledge-retrieval-20261027/validator/evaluate.py +++ /dev/null @@ -1,547 +0,0 @@ -"""Issue #190's frozen, standard-library-only retrieval evaluation packet.""" - -from __future__ import annotations - -import argparse -import cProfile -import hashlib -import importlib -import json -import os -import platform -import pstats -import random -import statistics -import subprocess -import sys -import time -from collections import Counter -from datetime import datetime, timezone -from pathlib import Path - -PACKET = Path(__file__).resolve().parents[1] -PROTOCOL = PACKET / "plan/protocol.json" -FREEZE_FILES = ( - "plan/protocol.json", "plan/README.md", "validator/development.json", - "validator/withheld.json", "validator/evaluate.py", "validator/README.md", - "plan/amendment-1.md", "plan/freeze-v1.json", -) -MODES = ("search", "relevance", "context_material", "default_diagnostic") - - -def require(condition, message): - if not condition: - raise ValueError(message) - - -def indexed_rows(rows, expected): - counts = Counter((r.get("mode"), r.get("case")) for r in rows) - errors = {"missing": sorted(expected - counts.keys(), key=repr), - "unexpected": sorted(counts.keys() - expected, key=repr), - "duplicates": sorted((key for key, n in counts.items() if n != 1), key=repr)} - return {(r.get("mode"), r.get("case")): r for r in rows}, {k: v for k, v in errors.items() if v} - - -def compare_quality(left, right, selected): - expected = {(mode, case["id"]) for case in selected for mode in MODES} - a, a_errors = indexed_rows(left, expected) - b, b_errors = indexed_rows(right, expected) - errors = {side: error for side, error in (("A", a_errors), ("B", b_errors)) if error} - failures = [{"mode": mode, "case": case} for mode, case in sorted(expected) - if (mode, case) in a and (mode, case) in b and a[mode, case] != b[mode, case]] - return errors, failures - - -def canonical(value): - return json.dumps(value, sort_keys=True, ensure_ascii=False, - separators=(",", ":"), allow_nan=False).encode("utf-8") - - -def sha(data): - return hashlib.sha256(data).hexdigest() - - -def read(path): - return json.loads(Path(path).read_text(encoding="utf-8")) - - -def write(path, value): - path = Path(path) - path.parent.mkdir(parents=True, exist_ok=True) - path.write_text(json.dumps(value, ensure_ascii=False, indent=2, - allow_nan=False) + "\n", encoding="utf-8") - - -def stamp(): - return datetime.now(timezone.utc).isoformat() - - -def freeze(make=False, dry=False): - hashes = {p: sha((PACKET / p).read_bytes()) for p in FREEZE_FILES} - path = PACKET / "plan/freeze.json" - if make: - if path.exists(): - raise ValueError("freeze_exists: never replace an existing freeze silently") - value = {"schema_version": 1, "revision": 2, - "supersedes_content_sha256": read(PACKET / "plan/freeze-v1.json")["content_sha256"], - "frozen_at_utc": stamp(), "files": hashes, - "content_sha256": sha(canonical(hashes))} - write(path, value) - return value - if not path.exists() and dry: - return {"state": "unfrozen_dry_run", "content_sha256": sha(canonical(hashes))} - value = read(path) - if value["files"] != hashes or value["content_sha256"] != sha(canonical(hashes)): - raise ValueError("freeze_mismatch: stop before importing or timing a candidate") - return value - - -def cases(split="development", limit=None): - result = read(PACKET / "validator/development.json")["cases"] - if split == "all": - result += read(PACKET / "validator/withheld.json")["cases"] - return result[:limit] if limit is not None else result - - -def inventory(root, paths): - files = {p.relative_to(root).as_posix(): {"sha256": sha(p.read_bytes()), - "bytes": p.stat().st_size} - for p in sorted(set(paths)) if p.is_file() - and "__pycache__" not in p.parts and p.suffix != ".pyc"} - return {"files": files, "sha256": sha(canonical(files)), "file_count": len(files), - "bytes": sum(v["bytes"] for v in files.values())} - - -def git(root, *args): - run = subprocess.run(["git", "-C", str(root), *args], capture_output=True, check=True) - return run.stdout.decode("utf-8").strip() - - -def source_identity(root): - data = root / "src/inferrsi/data" - source = inventory(root, (root / "src/inferrsi").rglob("*.py")) - corpus = inventory(root, [*(data / "repo_packs").rglob("*.json"), - *(data / "knowledge_packs").rglob("*"), - *(data / "skill_library").rglob("*")]) - library = inventory(root, (data / "skill_library").rglob("*")) - records = [p for p in (data / "repo_packs").rglob("*.json") if "knowledge" in p.parts] - records += list((data / "knowledge_packs").rglob("*.json")) - record_values = [read(p) for p in records] - return {"git_head": git(root, "rev-parse", "HEAD"), - "tracked_source_dirty": bool(git(root, "status", "--porcelain", - "--untracked-files=no", "--", "src/inferrsi")), - "python_sources": source, "corpus": corpus, - "library": {k: v for k, v in library.items() if k != "files"}, - "knowledge_record_count": len(record_values), - "packaged_skill_count": sum(r.get("index_type") == "packaged-skill" - for r in record_values)} - - -def fixture_check(root, selected): - data = root / "src/inferrsi/data" - paths = [p for p in (data / "repo_packs").rglob("*.json") if "knowledge" in p.parts] - paths += list((data / "knowledge_packs").rglob("*.json")) - records = {r["id"]: r for p in paths if "id" in (r := read(p))} - require(len({c["id"] for c in selected}) == len(selected), "duplicate_fixture_case") - for case in selected: - require(case["cue"].strip() and case["category"], "invalid_fixture_case: " + case["id"]) - if not case["relevant"]: - require(case["no_answer_rationale"], "missing_negative_rationale: " + case["id"]) - for label in case["relevant"]: - path = (root / label["source"]).resolve() - require(path.is_relative_to(root) and path.is_file(), "invalid_label_source: " + case["id"]) - require(label["support"] in path.read_text(encoding="utf-8"), "label_support_absent: " + case["id"]) - record = records[label["id"]] - require(label["source"] in record["source_files"], "unbound_label_source: " + case["id"]) - require(label["rationale"] and record["repo"] == "inferrsi", "invalid_label_scope: " + case["id"]) - require(case["backend"] is None or record["backend"] in (case["backend"], "common"), "invalid_label_backend: " + case["id"]) - return {"cases": len(selected), "answerable": sum(bool(c["relevant"]) for c in selected), - "negative": sum(not c["relevant"] for c in selected), - "fixture_sha256": sha(canonical(selected))} - - -def load_source(root): - sys.path.insert(0, str(root / "src")) - modules = {} - for name in ("inferrsi", "inferrsi.catalog", "inferrsi.knowledge_operations", "inferrsi.cli"): - module = importlib.import_module(name) - path = Path(module.__file__).resolve() - if not path.is_relative_to(root / "src/inferrsi"): - raise ValueError("module_origin_mismatch: " + name) - modules[name] = {"source": path.relative_to(root).as_posix(), - "sha256": sha(path.read_bytes())} - return modules - - -def environment(): - clock = time.get_clock_info("perf_counter") - return {"python_version": platform.python_version(), - "implementation": platform.python_implementation(), - "python_executable_sha256": sha(Path(sys.executable).read_bytes()), - "system": platform.system(), "release": platform.release(), - "machine": platform.machine(), "logical_cpu_count": os.cpu_count(), - "perf_counter_resolution_seconds": clock.resolution, - "site_initializers_disabled": bool(sys.flags.no_site), - "python_optimization": sys.flags.optimize, - "filesystem_cache": "not controlled; process cold is not OS-cache cold"} - - -def invoke(mode, case, reader=None): - from inferrsi.catalog import search_knowledge - from inferrsi.knowledge_operations import KnowledgeReader - common = {"repo": "inferrsi", "backend": case["backend"], "limit": 5} - if mode == "search": - return search_knowledge(case["cue"], **common) - reader = reader if reader is not None else KnowledgeReader() - if mode == "default_diagnostic": - return reader.collect(case["cue"], **common) - options = {"material": True, "max_bytes": 1048576, "context_bytes": 65536} if mode == "context_material" else {} - return reader.collect("", relevance=case["cue"], **common, **options) - - -def snapshot(value, compact=False): - encoded = canonical(value) - result = {"sha256": sha(encoded), "serialized_bytes": len(encoded)} - if compact: - return result - items = value if isinstance(value, list) else value["items"] - result["ordered_items"] = [ - {"id": item["id"], **{k: item[k] for k in ("ref", "revision") if k in item}, - **({"resource_count": len(item["resources"]), - "resource_hashes_sha256": sha(canonical(item["resources"])), - "dependencies_sha256": sha(canonical(item["dependencies"]))} - if "resources" in item else {})} for item in items] - if isinstance(value, dict): - for key in ("no_match", "omissions", "collisions", "material_bytes", "selection", - "context_omissions", "context_bytes", "context_budget"): - if key in value: - result[key] = value[key] - if "contexts" in value: - result["contexts"] = [ - {k: v for k, v in context.items() if k != "resources"} - | {"resources": [{k: v for k, v in resource.items() if k != "content"} - for resource in context["resources"]]} - for context in value["contexts"]] - return result - - -def worker(root, request): - modules = load_source(root) - if "expected_source_sha256" in request: - actual = inventory(root, (root / "src/inferrsi").rglob("*.py"))["sha256"] - if actual != request["expected_source_sha256"]: - raise ValueError("worker_source_digest_changed_before_measurement") - from inferrsi.knowledge_operations import KnowledgeReader - action = request["action"] - if action == "identity": - return {"modules": modules, "environment": environment(), **source_identity(root)} - selected = request["cases"] - if action in ("quality", "trace"): - outputs = [] - for case in selected: - for mode in MODES: - value = invoke(mode, case) - ids = [v["id"] for v in (value if isinstance(value, list) else value["items"])] - ranks = [i + 1 for i, identity in enumerate(ids[:5]) - if identity in {label["id"] for label in case["relevant"]}] - outputs.append({"case": case["id"], "mode": mode, - "answerable": bool(case["relevant"]), - "success_at_5": int(bool(ranks)), - "reciprocal_rank_at_5": 1 / ranks[0] if ranks else 0, - "output": snapshot(value)}) - return {"modules": modules, "outputs": outputs} - if action == "profile": - profiler = cProfile.Profile() - profiler.enable() - invoke("relevance", selected[0]) - profiler.disable() - rows = [] - for (filename, line, name), (primitive, calls, total, cumulative, _) in pstats.Stats(profiler).stats.items(): - path = Path(filename) - label = path.relative_to(root).as_posix() if path.is_relative_to(root) else "/" + path.name - rows.append({"source": label, "line": line, "function": name, - "primitive_calls": primitive, "calls": calls, - "total_seconds": total, "cumulative_seconds": cumulative}) - return {"modules": modules, "case": selected[0]["id"], - "mode": "fresh-reader relevance, cProfile diagnostic only", - "profile": sorted(rows, key=lambda r: -r["cumulative_seconds"])[:80]} - reader = KnowledgeReader() - warmups = [("relevance", case) for case in selected] - warmups += [("default_diagnostic", selected[1]), ("context_material", selected[2])] - for mode, case in warmups: - invoke(mode, case, reader) - cache = {"records_populated": reader._records is not None, "library_populated": reader._library is not None} - require(all(cache.values()), "warmup_cache_not_populated") - measurements = [] - workloads = [(mode, case) for case in selected for mode in ("hot_relevance", "cold_relevance", "search")] - workloads += [(mode, selected[index]) for index, modes in - ((1, ("hot_default_diagnostic", "cold_default_diagnostic")), - (2, ("hot_context_material", "cold_context_material"))) for mode in modes] - for mode, case in workloads: - operation = mode.removeprefix("hot_").removeprefix("cold_") - start = time.perf_counter_ns() - value = invoke(operation, case, reader if mode.startswith("hot_") else None) - elapsed = time.perf_counter_ns() - start - measurements.append({"mode": mode, "case": case["id"], "ns": elapsed, - "output": snapshot(value, compact=True)}) - return {"modules": modules, "warmup_cache_state": cache, "api": measurements} - - -def child(python, root, request): - env = {**os.environ, "PYTHONPATH": str(root / "src"), "PYTHONDONTWRITEBYTECODE": "1", - "PYTHONIOENCODING": "utf-8", "PYTHONOPTIMIZE": "0"} - run = subprocess.run([python, "-S", str(Path(__file__).resolve()), "_worker", "--source", str(root)], - input=canonical(request), capture_output=True, env=env, cwd=PACKET) - if run.returncode: - raise ValueError("isolated_worker_failed: " + run.stderr.decode("utf-8", "replace")[-400:].replace(str(root), "")) - return json.loads(run.stdout) - - -def cli(python, root, mode, case, expected_source): - if inventory(root, (root / "src/inferrsi").rglob("*.py"))["sha256"] != expected_source: - raise ValueError("CLI_source_digest_changed_before_measurement") - args = ["knowledge", "search", case["cue"], "--repo-type", "inferrsi"] if mode == "search" else ["collect"] - if mode == "default_diagnostic": - args += [case["cue"]] - elif mode != "search": - args += ["--relevance", case["cue"]] - if mode == "context_material": - args += ["--material", "--max-bytes", "1048576", "--context-bytes", "65536"] - args += ["--limit", "5", "--json"] - env = {**os.environ, "PYTHONPATH": str(root / "src"), "PYTHONDONTWRITEBYTECODE": "1", "PYTHONIOENCODING": "utf-8", "PYTHONOPTIMIZE": "0"} - start = time.perf_counter_ns() - run = subprocess.run([python, "-S", "-m", "inferrsi", *args], capture_output=True, env=env, cwd=PACKET) - elapsed = time.perf_counter_ns() - start - if run.returncode: - raise ValueError("CLI_invocation_failed: mode=" + mode) - start = time.perf_counter_ns() - value = json.loads(run.stdout.decode("utf-8")) - decode_ns = time.perf_counter_ns() - start - return {"mode": mode, "case": case["id"], "process_ns": elapsed, "decode_ns": decode_ns, - "scope": "repo=inferrsi" if mode == "search" else "unfiltered packaged CLI diagnostic", - "stdout_sha256": sha(run.stdout), "stdout_bytes": len(run.stdout), - "output": snapshot(value, compact=True)} - - -def percentile(values, p): - ordered = sorted(values) - position = (len(ordered) - 1) * p - low = int(position) - return ordered[low] + (ordered[min(low + 1, len(ordered) - 1)] - ordered[low]) * (position - low) - - -def bootstrap(reductions, protocol): - rule = protocol["performance"]["bootstrap"] - rng = random.Random(rule["seed"]) - draws = [statistics.median(rng.choices(reductions, k=len(reductions))) for _ in range(rule["iterations"])] - return {"paired_median_reduction": statistics.median(reductions), - "confidence_95": [percentile(draws, p) for p in rule["quantiles"]], - "paired_reductions": reductions, "bootstrap": rule} - - -def quality_summary(rows): - result = {} - for split in ("development", "withheld", "all"): - subset = [r for r in rows if split == "all" or r["case"].startswith("dev" if split == "development" else "withheld")] - for mode in MODES: - positive = [r for r in subset if r["mode"] == mode and r["answerable"]] - negative = [r for r in subset if r["mode"] == mode and not r["answerable"]] - if not positive and not negative: - continue - result[split + "/" + mode] = { - "answerable_count": len(positive), - "success_at_5": statistics.mean(r["success_at_5"] for r in positive) if positive else None, - "mrr_at_5": statistics.mean(r["reciprocal_rank_at_5"] for r in positive) if positive else None, - "negative_count": len(negative), - "negative_empty_count": sum(not r["output"]["ordered_items"] for r in negative)} - return result - - -def preflight(args, protocol, frozen): - roots = {"A": Path(args.baseline).resolve(), "B": Path(args.candidate).resolve()} - identities = {side: child(args.python, root, {"action": "identity"}) for side, root in roots.items()} - if identities["A"]["git_head"] != protocol["baseline_sha"]: - raise ValueError("baseline_revision_mismatch") - if identities["B"]["git_head"] != args.candidate_sha: - raise ValueError("candidate_revision_mismatch") - if identities["B"]["python_sources"]["sha256"] != args.candidate_source_sha: - raise ValueError("candidate_source_digest_mismatch") - if any(v["tracked_source_dirty"] for v in identities.values()): - raise ValueError("tracked_source_dirty") - if identities["A"]["corpus"]["sha256"] != identities["B"]["corpus"]["sha256"]: - raise ValueError("corpus_mismatch") - if identities["A"]["environment"] != identities["B"]["environment"]: - raise ValueError("interpreter_or_environment_mismatch") - return roots, {"started_at_utc": stamp(), "dry_run": args.dry_run, - "entry_python_optimization": sys.flags.optimize, - "verdict": "INCONCLUSIVE", "freeze_content_sha256": frozen["content_sha256"], - "identities": identities} - - -def benchmark_summary(pairs, protocol, expected_pairs=None): - expected_pairs = protocol["performance"]["pairs"] if expected_pairs is None else expected_pairs - hot = protocol["performance"]["hot_cases"] - api_keys = {(mode, case) for case in hot for mode in ("hot_relevance", "cold_relevance", "search")} - api_keys |= {(mode, hot[index]) for index, modes in - ((1, ("hot_default_diagnostic", "cold_default_diagnostic")), - (2, ("hot_context_material", "cold_context_material"))) for mode in modes} - cli_keys = {(mode, hot[2] if mode == "context_material" else hot[1]) for mode in MODES} - errors = [] - ids = [pair.get("pair") for pair in pairs] - if any(type(i) is not int for i in ids) or Counter(ids) != Counter(range(expected_pairs)): - errors.append({"pair_ids": ids, "expected_pair_ids": list(range(expected_pairs))}) - for pair in pairs: - index = pair.get("pair") - if type(index) is not int or pair.get("order") != ("AB" if index % 2 == 0 else "BA"): - errors.append({"pair": index, "invalid_order": pair.get("order")}) - for side in ("A", "B"): - for family, keys in (("api", api_keys), ("cli", cli_keys)): - _, error = indexed_rows(pair.get(side, {}).get(family, []), keys) - if error: - errors.append({"pair": index, "side": side, "family": family, **error}) - if errors: - return {"measurement_structure_errors": errors, "primary": None, - "performance_gate_passed": False, "output_parity_assessed": False, - "output_parity_failures": [], "latency_ns": {}} - grouped = {} - reductions = [] - parity_failures = [] - for pair in pairs: - for side in ("A", "B"): - for row in pair[side]["api"]: - grouped.setdefault("api/" + row["mode"] + "/" + row["case"] + "/" + side, []).append(row["ns"]) - for row in pair[side]["cli"]: - for metric in ("process_ns", "decode_ns"): - grouped.setdefault("cli/" + row["mode"] + "/" + row["case"] + "/" + metric + "/" + side, []).append(row[metric]) - medians = {side: statistics.median(r["ns"] for r in pair[side]["api"] if r["mode"] == "hot_relevance") for side in ("A", "B")} - reductions.append(1 - medians["B"] / medians["A"]) - for family in ("api", "cli"): - keys = api_keys if family == "api" else cli_keys - left_rows, _ = indexed_rows(pair["A"][family], keys) - right_rows, _ = indexed_rows(pair["B"][family], keys) - for key in sorted(keys): - left, right = left_rows[key], right_rows[key] - if left["output"] != right["output"] or (family == "cli" and left["stdout_sha256"] != right["stdout_sha256"]): - parity_failures.append({"pair": pair["pair"], "family": family, "mode": left["mode"], "case": left["case"]}) - estimate = bootstrap(reductions, protocol) - gate = protocol["performance"]["gate"] - passed = (estimate["paired_median_reduction"] >= gate["minimum_paired_median_reduction"] - and estimate["confidence_95"][0] > gate["lower_95_percent_bound_must_exceed"]) - return {"primary": estimate, "performance_gate_passed": passed, - "measurement_structure_errors": [], "output_parity_assessed": True, - "output_parity_failures": parity_failures, - "latency_ns": {key: {"n": len(values), "p50": percentile(values, .5), "p95": percentile(values, .95)} - for key, values in sorted(grouped.items())}} - - -def main(): - parser = argparse.ArgumentParser(description=__doc__) - parser.add_argument("action", choices=("freeze", "check-freeze", "validate", "identity", "profile", "trace", "quality", "bench", "selfcheck", "_worker")) - parser.add_argument("--source") - parser.add_argument("--baseline") - parser.add_argument("--candidate") - parser.add_argument("--candidate-sha") - parser.add_argument("--candidate-source-sha") - parser.add_argument("--python", default=sys.executable) - parser.add_argument("--output") - parser.add_argument("--split", choices=("development", "all"), default="development") - parser.add_argument("--dry-run", action="store_true") - parser.add_argument("--case-limit", type=int) - parser.add_argument("--pairs", type=int) - args = parser.parse_args() - if args.action == "_worker": - print(canonical(worker(Path(args.source).resolve(), json.load(sys.stdin))).decode("utf-8")) - return - protocol = read(PROTOCOL) - if args.action == "freeze": - value = freeze(make=True) - elif args.action == "selfcheck": - require(percentile([1, 3], .95) == 2.9, "percentile_selfcheck") - require(bootstrap([.3] * 20, protocol)["confidence_95"] == [.3, .3], "bootstrap_selfcheck") - require(snapshot({"items": [], "no_match": True})["ordered_items"] == [], "snapshot_selfcheck") - selected = [{"id": f"synthetic{i:02}"} for i in range(24)] - quality = [{"case": c["id"], "mode": mode} for c in selected for mode in MODES] - require(compare_quality(quality, quality[:-1], selected)[0], "missing_quality_row_accepted") - require(compare_quality(quality, quality + [quality[0]], selected)[0], "duplicate_quality_row_accepted") - hot = protocol["performance"]["hot_cases"] - api = [{"mode": mode, "case": case, "ns": 100, "output": {}} for case in hot for mode in ("hot_relevance", "cold_relevance", "search")] - api += [{"mode": mode, "case": hot[index], "ns": 100, "output": {}} for index, modes in ((1, ("hot_default_diagnostic", "cold_default_diagnostic")), (2, ("hot_context_material", "cold_context_material"))) for mode in modes] - cli_rows = [{"mode": mode, "case": hot[2] if mode == "context_material" else hot[1], "process_ns": 100, "decode_ns": 10, "output": {}, "stdout_sha256": "synthetic"} for mode in MODES] - pairs = [{"pair": i, "order": "AB" if i % 2 == 0 else "BA", "A": {"api": api, "cli": cli_rows}, "B": {"api": [{**r, "ns": 50} for r in api], "cli": cli_rows}} for i in range(20)] - require(benchmark_summary(pairs, protocol)["performance_gate_passed"], "complete_synthetic_pairs_rejected") - for pair in pairs: - pair["B"] = {"api": api[:-1], "cli": []} - require(benchmark_summary(pairs, protocol)["measurement_structure_errors"], "missing_benchmark_rows_accepted") - pairs[0]["pair"] = 1 - require(benchmark_summary(pairs, protocol)["measurement_structure_errors"], "duplicate_pair_accepted") - value = {"selfcheck": "passed", "entry_python_optimization": sys.flags.optimize} - else: - frozen = freeze(dry=args.dry_run) - if not args.dry_run and (args.case_limit is not None or args.pairs not in (None, protocol["performance"]["pairs"])): - raise ValueError("formal_sample_count_change_requires_new_protocol_freeze") - if args.dry_run and args.split == "all": - raise ValueError("dry_run_must_not_open_withheld") - if args.action == "check-freeze": - value = frozen - elif args.action == "identity": - value = child(args.python, Path(args.source).resolve(), {"action": "identity"}) - elif args.action in ("validate", "profile", "trace"): - if args.split == "all": - raise ValueError("withheld_requires_quality_preflight_and_candidate_freeze") - selected = cases(limit=args.case_limit) - value = fixture_check(Path(args.source).resolve(), selected) - if args.action != "validate": - cue = next(c for c in selected if c["id"] == ("dev05" if args.action == "profile" else "dev09")) - value = child(args.python, Path(args.source).resolve(), {"action": args.action, "cases": [cue]}) - else: - if not all((args.baseline, args.candidate, args.candidate_sha, args.candidate_source_sha)): - raise ValueError("explicit_baseline_candidate_revision_and_source_digest_required") - roots, value = preflight(args, protocol, frozen) - if args.action == "quality": - selected = cases(args.split, args.case_limit) - value["fixture"] = fixture_check(roots["A"], selected) - value["variants"] = {side: child(args.python, root, {"action": "quality", "cases": selected, "expected_source_sha256": value["identities"][side]["python_sources"]["sha256"]}) for side, root in roots.items()} - value["metrics"] = {side: quality_summary(v["outputs"]) for side, v in value["variants"].items()} - left, right = (value["variants"][side]["outputs"] for side in ("A", "B")) - value["measurement_structure_errors"], value["parity_failures"] = compare_quality(left, right, selected) - value["verdict"] = "INCONCLUSIVE" if value["measurement_structure_errors"] else "FAIL" if value["parity_failures"] else "PASS" if args.split == "all" and not args.dry_run else "INCONCLUSIVE" - else: - if not args.output: - raise ValueError("bench_requires_output_for_incremental_raw_sample_retention") - selected = [c for c in cases() if c["id"] in protocol["performance"]["hot_cases"]] - value["pairs"] = [] - start = time.perf_counter_ns() - for index in range(args.pairs or protocol["performance"]["pairs"]): - pair = {"pair": index, "order": "AB" if index % 2 == 0 else "BA"} - value["pairs"].append(pair) - for side in pair["order"]: - source_sha = value["identities"][side]["python_sources"]["sha256"] - pair[side] = child(args.python, roots[side], {"action": "bench", "cases": selected, "expected_source_sha256": source_sha}) - pair[side]["cli"] = [cli(args.python, roots[side], mode, selected[2] if mode == "context_material" else selected[1], source_sha) for mode in ("search", "default_diagnostic", "relevance", "context_material")] - value["elapsed_ns"] = time.perf_counter_ns() - start - write(args.output, value) - print("completed paired group " + str(index + 1), file=sys.stderr, flush=True) - value["summary"] = benchmark_summary(value["pairs"], protocol, args.pairs or protocol["performance"]["pairs"]) - sufficient = len(value["pairs"]) == protocol["performance"]["pairs"] and not args.dry_run - value["verdict"] = "INCONCLUSIVE" if not sufficient or value["summary"]["measurement_structure_errors"] else "PASS" if value["summary"]["performance_gate_passed"] and not value["summary"]["output_parity_failures"] else "FAIL" - value["source_and_corpus_unchanged_at_end"] = {} - for side, root in roots.items(): - final = child(args.python, root, {"action": "identity"}) - same = all(final[key]["sha256"] == value["identities"][side][key]["sha256"] for key in ("python_sources", "corpus")) - value["source_and_corpus_unchanged_at_end"][side] = same - if not same: - value["verdict"] = "INCONCLUSIVE" - value["completed_at_utc"] = stamp() - if args.output: - write(args.output, value) - # Keep stdout free of fixture text, personal paths and full corpus inventories. - print(json.dumps({k: value[k] for k in ("verdict", "dry_run", "cases", "answerable", "negative", "content_sha256", "selfcheck") if k in value})) - - -if __name__ == "__main__": - try: - main() - except (ValueError, AssertionError, OSError, subprocess.SubprocessError) as exc: - # Paths supplied by the operator stay local; do not leak full tracebacks. - print("evaluation stopped: " + type(exc).__name__ + ": " + str(exc).replace(str(PACKET), ""), file=sys.stderr) - raise SystemExit(2) diff --git a/evidence/knowledge-retrieval-20261027/validator/withheld.json b/evidence/knowledge-retrieval-20261027/validator/withheld.json deleted file mode 100644 index 17232fa4b..000000000 --- a/evidence/knowledge-retrieval-20261027/validator/withheld.json +++ /dev/null @@ -1,15 +0,0 @@ -{ - "schema_version": 1, - "split": "withheld", - "construction": "Sealed source-content-first synthetic questions and partial relevance judgements, authored without retrieval rankings. Release only after runtime candidate revision/source digest freeze.", - "cases": [ - {"id": "withheld01", "category": "symbol", "cue": "prefetch_queue_depth executor_statistics", "backend": null, "relevant": [{"id": "inferrsi.common.skills.training_input_pipeline", "source": "src/inferrsi/data/skill_library/methods/training-input-pipeline/SKILL.md", "support": "executor_statistics()", "rationale": "The DALI section explains queue buffering, executor statistics and execution-mode gates together."}]}, - {"id": "withheld02", "category": "natural-language", "cue": "Can a serving simulator certify latency SLOs near queue capacity?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.calibrate_serving_simulation", "source": "src/inferrsi/data/skill_library/methods/calibrate-serving-simulation/SKILL.md", "support": "near capacity", "rationale": "The calibration procedure requires dynamic queue-delay validation at the intended load and rejects near-capacity predictive certification without evidence."}]}, - {"id": "withheld03", "category": "multi-term", "cue": "FastServe suspended KV preemption progress", "backend": null, "relevant": [{"id": "inferrsi.common.skills.assess_serving_preemption", "source": "src/inferrsi/data/skill_library/methods/assess-serving-preemption/SKILL.md", "support": "Protect progress", "rationale": "The preemption procedure counts suspended state and requires progress under pressure, rather than treating priority alone as a guarantee."}]}, - {"id": "withheld04", "category": "backend-symbol", "cue": "ACLGraph stable replay buffers", "backend": "ascend", "relevant": [{"id": "inferrsi.ascend.skills.ascend_aclgraph_capture_replay", "source": "src/inferrsi/data/skill_library/hardware/ascend/ascend-aclgraph-capture-replay/SKILL.md", "support": "caller-managed stable replay buffers", "rationale": "The ACLGraph procedure states the caller's stable-buffer responsibility and the limited coverage of address assertions."}]}, - {"id": "withheld05", "category": "natural-language", "cue": "How is moving a request between replicas different from changing its sequence parallel group?", "backend": null, "relevant": [{"id": "inferrsi.common.skills.evaluate_elastic_serving_placement", "source": "src/inferrsi/data/skill_library/methods/evaluate-elastic-serving-placement/SKILL.md", "support": "Choose the actual decision", "rationale": "This procedure directly separates Llumnix replica migration from LoongServe sequence-parallel group changes and their state costs."}]}, - {"id": "withheld06", "category": "multi-term", "cue": "roofline analytical empirical end-to-end ceiling", "backend": "cuda", "relevant": [{"id": "inferrsi.common.skills.performance_ceiling_analysis", "source": "src/inferrsi/data/skill_library/methods/performance-ceiling-analysis/SKILL.md", "support": "Three-level ceiling model", "rationale": "The headroom procedure distinguishes analytical, attainable component and end-to-end ceilings and supplies a bounded roofline arithmetic helper."}]}, - {"id": "withheld07", "category": "no-answer-nonce", "cue": "zephyrcodex latticeotter q83", "backend": null, "relevant": [], "no_answer_rationale": "Constructed nonce terms with no intended library answer; any returned candidates remain visible as negative-query behavior."}, - {"id": "withheld08", "category": "no-answer-domain", "cue": "baroque harpsichord tuning temperament", "backend": "rocm", "relevant": [], "no_answer_rationale": "A synthetic music-history request outside the shipped systems procedures; not an exhaustive semantic absence assertion."} - ] -} diff --git a/tests/test_evidence_inventory.py b/tests/test_evidence_inventory.py index f726313c1..4e87fcb2c 100644 --- a/tests/test_evidence_inventory.py +++ b/tests/test_evidence_inventory.py @@ -67,30 +67,6 @@ def test_changed_hashed_file_fails(bundle): assert "SHA-256 mismatch" in str(validate_inventory(repo)["errors"]) -def test_nested_bundle_hashes_are_verified(bundle): - repo, root, inventory = bundle - hashes = json.loads((root / "plan/freeze.json").read_text(encoding="utf-8")) - write_json(root / "plan/freeze.json", {"schema_version": 1, "files": hashes}) - inventory["bundles"]["synthetic"]["manifests"][0]["field"] = "files" - write_json(repo / "tools/evidence_inventory.json", inventory) - result = validate_inventory(repo) - assert result["errors"] == [] - assert result["checked_hashes"] == 1 - (root / "validator/check.py").write_bytes(b"# changed nested payload\n") - assert "SHA-256 mismatch" in str(validate_inventory(repo)["errors"]) - - -@pytest.mark.parametrize("manifest", [ - {"other": {}}, {"files": []}, {"files": None}, {"files": "not a mapping"}, {"files": {}}, -]) -def test_nested_bundle_field_must_exist_and_be_nonempty_mapping(bundle, manifest): - repo, root, inventory = bundle - write_json(root / "plan/freeze.json", manifest) - inventory["bundles"]["synthetic"]["manifests"][0]["field"] = "files" - write_json(repo / "tools/evidence_inventory.json", inventory) - assert validate_inventory(repo)["errors"] - - @pytest.mark.parametrize("path", ["../outside", "/outside", "C:/outside", "..\\outside", "a/../b"]) def test_unsafe_manifest_path_fails(bundle, path): repo, root, _ = bundle @@ -169,6 +145,6 @@ def test_checked_in_inventory(): repo = Path(__file__).resolve().parents[1] result = validate_inventory(repo) assert result["errors"] == [] - assert len(result["bundles"]) == 9 - assert result["checked_hashes"] == 120 + assert len(result["bundles"]) == 8 + assert result["checked_hashes"] == 112 assert result["unavailable"] # Historical raw artifacts are not in this checkout. diff --git a/tools/evidence_inventory.json b/tools/evidence_inventory.json index 60e1617d3..d1218689e 100644 --- a/tools/evidence_inventory.json +++ b/tools/evidence_inventory.json @@ -7,13 +7,6 @@ "manifests": [{"path": "plan/freeze.json", "schema": "bundle-sha256"}], "external": ["Runtime evidence referenced by results/status.json is stored separately."] }, - "knowledge-retrieval-20261027": { - "kind": "campaign", - "manifests": [{ - "path": "plan/freeze.json", "schema": "bundle-sha256", "field": "files" - }], - "external": ["Private local pytest logs are not copied; results/validation-summary.md retains the failed suite, baseline failure reproductions and package-check qualification."] - }, "modular-refactor-20261013": { "kind": "campaign", "manifests": [{ diff --git a/tools/validate_evidence.py b/tools/validate_evidence.py index 3af5a70d9..067a93000 100644 --- a/tools/validate_evidence.py +++ b/tools/validate_evidence.py @@ -57,9 +57,7 @@ def validate_manifest(repo, bundle, entry, unavailable): schema = entry["schema"] checked = 0 if schema in ("bundle-sha256", "historical-sha256"): - if schema == "bundle-sha256" and "field" in entry: - data = data[entry["field"]] - if not isinstance(data, dict) or not data: + if not data: raise ValueError("empty hash manifest") mapping = entry.get("files", {}) if schema == "historical-sha256" and set(mapping) != set(data):