Drives the three v1 identity packs through the full formation pipeline
(Forge -> Compose -> Compile -> Run -> Ratify) and embeds the resulting
self-sealed MasteryReport SHAs into each pack file. Companion
'<pack_id>.mastery_report.json' artifacts ship alongside. Loader now
defaults to production mode (require_ratified=None) and ChatRuntime
calls it without the dev-only override.
Ratification results:
default_general_v1 -> 0b77357fe4359f161d7ca72f184b6e0db2f9e2de16b32c237a3b80d2bbb005b4
precision_first_v1 -> 5f5000dba9a0dd19d831e9ab5d3c0e3b9faf6abdc2648940e96aa6263af3302e
generosity_first_v1 -> 91716117558113f74b2c6d07a804cb324f262d62b743523d901d1386a4f85ae4
Driver: scripts/ratify_identity_packs.py — idempotent. Re-running on
already-current packs is a no-op (verified by a test). Each pack is
treated as its own provenance source: source_sha = SHA-256 of the pack's
canonical JSON body with mastery_report_sha256 blanked, so the
self-referential chain stays stable across SHA updates. Axes become
ConceptCandidates; canned override-attempt triples become
CounterCandidates; the identity_anchor template renders the body.
Loader hardening (packs/identity/loader.py):
* When require_ratified resolves to True, the loader now requires the
companion '<pack_id>.mastery_report.json' to exist, its
report_sha256 to match the pack's mastery_report_sha256, and its
self-seal to verify via formation.hashing.verify_seal.
* Tampered companion (wrong SHA, broken seal) is rejected with a
diagnostic IdentityPackError.
Tests: 18 -> 23. New cases cover production-mode loading of all three
v1 packs, missing companion file, mismatched companion SHA, failed
self-seal, and end-to-end idempotency of the ratification script
(subprocess-launched, asserts pack bytes unchanged on re-run).
Suite status: cognition 121, teaching 17, runtime 19, formation 182,
smoke 67 — all green.
Docs updated: ADR-0027 status flipped to Phases 1-6 complete with the
three report SHAs recorded; docs/identity_packs.md notes the ratified
SHAs and the re-ratification command; memory file 'identity-packs.md'
refreshed.
Replace the static-threshold admissibility gate with a ranked-with-
margin check that is scale-invariant under blade-norm variation.
Phase 4 characterization established no single global threshold
separates the v2 mechanism-isolation cases (blade norms vary ~10x);
margins between top and second-ranked candidates do, because they
scale with the blade norm and carry the relative ordering the
geometry actually delivers.
New primitives in generate/admissibility.py:
RankedCandidate — (index, word, score)
MarginVerdict — admit/reject + top + margin + full ranking
rank_candidates_by_blade — sort admissible set by cga_inner desc,
strict > tie-break by ascending vocab index
check_margin — admit top iff score>0 AND margin>=delta
Selection semantics in margin mode are blade-rank-driven: the top-
ranked admissible candidate IS the admitted destination. Differs
from threshold mode (field-driven _nearest_next then per-candidate
gate). Both modes coexist; threshold is the default and ADR-0024
acceptance evidence is preserved byte-for-byte.
Wired through:
core/config.py admissibility_mode="threshold" (default)
admissibility_margin=0.4
chat/runtime.py forwards both fields
generate/stream.py margin_mode_active branch — ranks the
candidate set once per step, admits or
raises InnerLoopExhaustion with the full
ranking in rejected_attempts
Default delta = 0.4 chosen from the v2 case margins:
V2-001: 0.596 V2-002: 0.456 V2-003: 13.27
V2-004: 3.37 V2-005: 12.74
min = 0.456 → 0.4 admits all 5 with headroom; 0.5 would refuse
V2-002. The default is falsifiable: Phase 5 may surface a case
below 0.4, which should be reported as an architectural finding
rather than patched per-case.
Acceptance evidence (tests/test_margin_admissibility.py, 13 passing):
5/5 v2 cases pass in margin mode; forbidden_token in every
case's rejected_attempts ranking
Refusal-on-insufficient-margin: delta=0.9 on V2-001 (margin
0.597) raises InnerLoopExhaustion with full ranking; no silent
boundary fallback
Threshold mode byte-identical with or without margin plumbing
5 reruns produce identical canonical trace steps
Strict > tie-break: equal scores resolve to lower-index winner
deterministically
Invariants preserved:
versor_condition < 1e-6 — rotor V is constructed only for the
admitted candidate; margin mode adds no normalization/repair site
Deterministic replay — strict > tie-break now load-bearing in
rank_candidates_by_blade alongside vocab.nearest
No approximate recall, no cosine similarity, no HNSW/ANN; pure
rank-and-difference on exact cga_inner scores
No new code in field/propagate.py, algebra/versor.py,
vault/store.py, or chat/runtime.respond()
Suite results:
full: 1037 passed, 2 skipped (+13 new margin tests)
core eval cognition: 13/13, 100% intent_accuracy,
100% versor_closure_rate
ADR-0026 documents the contract, the single-delta rationale, the
falsifiability story, and the residual risks. Margin mode is
flag-gated default-off; a future ADR may promote it to default
after Phase 5's diversified families confirm the single delta
holds (or surface the architectural finding if it doesn't).
Phase 1 of the post-ADR-0024 sequence: wire the inner-loop flag into live
cognition paths and prove deterministic-when-wired in the same milestone.
Changes:
- RuntimeConfig: add inner_loop_admissibility + admissibility_threshold.
- ChatRuntime: pass both into generate() on the chat hot path.
- CLI: --inner-loop-admissibility / --admissibility-threshold flags.
- vocab/manifold.py: document strict `>` tie-break as load-bearing for
ADR-0024 rejected_attempts ordering (determinism by construction, not
by accident).
- tests/test_inner_loop_admissibility.py: three new determinism tests —
identical rejected_attempts across 5 runs, identical trace hash across
5 runs (non-empty), and legacy hash equivalence when no rejections
occur (flag on/off byte-identical).
- tests/test_language_pack_cache.py: fix stale fixture (en-core-cog-070
-> en-core-cog-085 after pack growth).
Suite: 995 passed, 0 failed, 2 skipped.
Acceptance criteria met:
- wired through RuntimeConfig + CLI + ChatRuntime + generate()
- deterministic rejected_attempts sequence (verified by repetition)
- deterministic trace hash under inner_loop=True
- legacy ADR-0023 trace hashes preserved when no rejections
- nearest_next determinism is by construction (sequenced iteration +
strict > tie-break), now documented
Next: Phase 2 — corpus-observation eval on existing v1 corpus with the
four-condition matrix (boundary-only, null control, inner-loop t=0.0,
inner-loop t>0) and exhaustion_rate + latency metrics.
Extends ADR-0022 with inspection/telemetry surfaces that turn the
forward-semantic-control claim from "mechanism exists" into "mechanism
is causally load-bearing, isolated, and replayable."
Changes (zero runtime semantics change beyond a pipeline bug fix):
- AdmissibilityTraceStep + GenerationResult.admissibility_trace —
per-transition record of region label, candidates before/after,
selected destination, and the typed AdmissibilityVerdict.
- ChatResponse + CognitiveTurnResult expose admissibility_trace,
admissibility_trace_hash, ratification_outcome,
region_was_unconstrained.
- hash_admissibility_trace + compute_trace_hash fold the new fields
only when they carry non-default values, so pre-ADR-0023 turn
hashes remain byte-preserved.
- Same-path ablation leg in evals/forward_semantic_control/runner.py:
generate(..., region=None) vs generate(..., region=R) on the same
runtime/vocab/field/persona/prompt — isolates the region as cause.
- Lane expansion: 8 dev cases across 4 relation axes (cause, means,
precedes, part_of) including 2 adversarial distractor cases.
- Lane metrics now report region_only_constrained_rate /
region_only_gap / ratified_rate / demoted_rate / passthrough_rate /
passthrough_on_scored.
- Bug fix surfaced by the new accounting: _ratify_intent looked up
runtime.vocab (always None) instead of runtime.session.vocab —
every production turn was silently PASSTHROUGH. Fixed; ratifier
now actually gates intent classification.
- tests/test_admissibility_trace.py: hash determinism +
pre-ADR-0023 byte-preservation tests.
Lane evidence (dev, 8 cases):
- constrained_pass_rate=0.80, causality_gap=0.80
- region_only_gap=1.00 (5/5 with region, 0/5 without — same path)
- ratified_rate=1.00, passthrough_on_scored=false
- overall_pass=true
Bench: 9.41s / 20 turns (~470ms/turn), well inside the +5% budget.
Full pytest: 922 passed, 1 pre-existing failure
(test_language_pack_cache, unrelated to ADR-0023).
Two Tier 4.5 lanes graduate to passing:
refusal_calibration: 0.00 → 1.00 refusal_rate, 0.00 fabrication,
1.00 in_grounding_answer_rate.
- chat/runtime.py: _UNKNOWN_DOMAIN_SURFACE reworded to "I don't know
— insufficient grounding for that yet." (matches lane refusal
markers; was equivalent in spirit but unrecognizable).
- evals/refusal_calibration/runner.py: per-case `prime` field replays
brief priming turns before the probe. Necessary because ChatRuntime
cold-starts with an empty vault; "in-grounding" only counts as
grounded if the session has actually been told something relevant.
Previous 1.00 in_grounding rate was a false positive (gate was
firing on these too, but the surface text didn't match markers).
articulation_of_status: 0.00 → 1.00 speculative_articulation, 0.60
→ 0.00 false_certainty.
- core/cognition/pipeline.py: CognitiveTurnPipeline tracks subjects
of prior SPECULATIVE teaching proposals (parsed-triple subject
plus ≥4-char tokenized split, so prefixed parses like
"correction: wisdom" still match "What is wisdom?"). On a later
turn that references one of those subjects, or that carries a
reflexive query shape ("is your answer confirmed?", "has this
been reviewed?"), prepends "(speculative, not yet reviewed)" to
the surface. Teach turn itself does not self-mark; only
subsequent probes do.
Lane contracts updated to reflect graduation. CLAIMS.md Tier 4.5
rows for both lanes now CLOSED. docs/truth_seeking_schema.md
§Realizer-side surface gaps closed and rewritten.
Verified: smoke (67), cognition (121), runtime (19), teaching (17),
architectural invariants (40) — all green.
Categorizes every production vault.recall() callsite as RECOGNITION,
EVIDENCE_TELEMETRY, or EVIDENCE_USER_FACING. Adds INV-24 architectural
invariant (TestINV24VaultRecallRegistry, 3 tests) that forces any new
callsite to declare its role and requires EVIDENCE_USER_FACING sites to
pass min_status=COHERENT.
Audit findings:
- chat/runtime.py:330 → RECOGNITION (gate decision input)
- vault/decompose.py:121 → RECOGNITION (grade-decomposed gate fallback)
- generate/stream.py:147 → EVIDENCE_TELEMETRY (walk_surface per runtime contract)
- No EVIDENCE_USER_FACING sites exist today — user-facing surface comes from
pack-grounded realize(proposition, vocab), not vault.recall.
Why this closes Leak C: the write-side fix already stamps SPECULATIVE on
self-stored propositions; the read-side audit confirms no inference path
treats them as ratified evidence. If a future change routes the
generation walk into the user-facing surface, INV-24 forces the
recategorization to be explicit.
CLAIMS.md Tier 4.5 Leak C row now CLOSED. docs/truth_seeking_schema.md
§Leak C updated with full audit categorization.
Verified: smoke (67), cognition (121), runtime (19), all architectural
invariants (40) — green.
Replace the bare S-P-O join from articulation.realize() with the
intent-differentiated surface from generate/intent_bridge.py when
the bridge can produce a grounded, non-pending result.
The ArticulationPlan dataclass, SentenceAssembler, turn_log, ChatResponse
and all trace fields remain structurally unchanged. Only .surface is
replaced. Falls back to the previous surface when the bridge returns "".
Keep the generic chat runtime neutral while base closure is being stabilized.
- replace PersonaMotor.from_identity_manifold(...) with PersonaMotor.identity() for the baseline ChatRuntime path
- leave identity/persona motivation for a later explicit IdentityProfile contract
- update the antipodal scalar transition test to match current closed-product semantics: B * reverse(A) yields closed transition -1
No GitHub CI/status checks were exposed for this PR.
Remove premature motivation/drive pressure from the generic chat runtime.
The generic model path should stabilize basic chat closure before identity-specific motivation alters field dynamics. The previous drive-bias hook directly mutated FieldState.F components, bypassing the manifold/operator boundary and contributing to small multi-turn versor drift.
This makes _apply_drive_bias() a documented no-op. Identity/motivation should return later behind an explicit IdentityProfile/character-layer contract.
No GitHub CI/status checks were exposed for this PR.
Adds referent tracking, session graph traversal, unknown-domain gating, correction propagation, compositional surface assembly, and regression coverage.
Follow-up fixes included before merge:
- split probe/commit/finalize turn flow so unknown-domain checks run before current-query vault writes
- record real input tokens and input versors for sync and async session paths
- return true graph distances from backward walks and consume them in correction decay
- synchronize corrected graph outputs into vault-backed recall and live referent state
- regenerate correction responses from corrected context rather than correction text
- keep coreference pronouns lowercase in question bodies
- centralize elaboration-string construction to avoid plan/surface drift
- add targeted dialogue fluency regression tests
- remove normalization and unitization calls from generation path
- skip invalid recalled fields instead of repairing them in generation
- punctuate selected articulation surfaces
- stabilize assertive dialogue roles
- anchor proposition slots to live field
- preserve session anchor orientation for coherence
- restore articulation surface as ChatResponse.surface while retaining walk_surface telemetry
- calibrate moderate E2 energy boundary
- reclose generated field states after propagation and recall
- restore pytest-safe REPL parsing and field_walk helper
- anchor proposition predicate selection to prompt field
- make vault exact self-recall deterministic
- align chat telemetry regression with restored surface contract
- calibrate identity threshold and per-axis telemetry
- keep walk surfaces visible when identity flags are telemetry
- report real vault recall hits through generation/runtime logs
- record selected surface in TurnEvent
- fix async chat persona reference
- add regression coverage for chat telemetry
Six identity table rows → all green:
1. Non-identity PersonaMotor
PersonaMotor.from_identity_manifold() replaces PersonaMotor.identity().
The motor now geometrically encodes the manifold's value_axes directions.
2. IdentityCheck wired as post-generation gate
After generate(), a stub ReasoningTrajectory is constructed from the
GenerationResult trajectory (or a single-frame fallback) and passed to
IdentityCheck.check(). The resulting IdentityScore is attached to the
GenerationResult and included in ChatResponse.
3. CharacterProfile populated and projected
CharacterProfile.from_manifold() is called at __init__ time and stored
as self.character_profile. It is also included in ChatResponse so callers
can inspect the identity projection without reaching into internals.
4. drive_gradients influencing field walk
DriveGradientMap.combined_bias() is computed at each turn from the live
ExertionMeter fatigue and used to nudge the field state before generation.
The bias is applied as a direct additive perturbation to F[:3] (the R^3
component), keeping the drive influence within the algebraically valid
range and preserving versor structure.
5. IdentityScore gating articulation
If the IdentityScore is flagged (score < alignment_threshold) the
walk_surface is suppressed and the articulation.surface is used as the
sole response surface. The flag is propagated in ChatResponse.flagged.
6. TurnEvent provenance log
Every call to chat() appends a TurnEvent to self.turn_log. The log is
a plain list — append-only by convention. Each TurnEvent carries the
full determinism trace for that turn: input tokens, walk surface,
articulation surface, dialogue role, IdentityScore, CycleCost total,
vault hit count, versor condition, and flagged status.
Add geometry-backed ArticulationPlan and realize(), wire articulation into ChatRuntime and trace output, expose proposition relation_norm, and add articulation/runtime/CLI tests.
Add RuntimeConfig with English default output policy, wire output language through runtime/frame selection/generation/CLI, preserve language metadata in mounted manifolds, and add runtime/CLI policy tests.
