Commit graph

3 commits

Author SHA1 Message Date
Shay
b5d6ad6510 feat(compositionality): compose_relations operator lifts lane 68.8% → 100%
Closes the residual `novel_pair_under_seen_relation` pattern that
neither `transitive_walk` nor `multi_relation_walk` could synthesise.

- new `compose_relations(triples, head, frame, relation)` operator —
  pure lookup, returns both `R(head, ?)` and `R(frame, ?)` tails
- new `FRAME_TRANSFER` intent + `_FRAME_TRANSFER_RE` regex tried
  before generic TRANSITIVE_QUERY so "in Y" isn't truncated; handles
  "X belong to in Y" → belongs_to normalisation
- pipeline wiring: `_maybe_compose_relations`, `_fold_compose_into_surface`,
  `_serialize_compose` (folded into operator_invocation so trace_hash
  stays bit-identical across replay)
- regression: inference_closure, multi_step_reasoning,
  cross_domain_transfer all still 100% on public + holdouts

discourse_paragraph v2:
- per-sentence grammar rubric (length, capitalization, subject
  alignment) gated on `require_per_sentence_grammar`
- scaling cases at 10 / 20 / 50 sentences — 3/3 pass, 100% per-sentence
- 3 runtime round-trip cases (`mode: runtime_roundtrip`) that prime
  vault, ask question, verify bit-identical across two fresh runtimes
- new `per_sentence_grammar_pass_rate` lane metric

Long-form replay benchmark (benchmarks/replay_vs_llm.py):
- `replay_determinism_report(prompts, runs, priming)` — CORE-only
- `compare_to_llm(prompts, llm_callable)` — BYO API client, no
  provider lock-in; reports per-prompt determinism on both sides
- ships with default cognition-pack prompts; 100% bit-identical at runs=3

Lanes green: cognition 121/121, runtime 19/19, teaching 17/17,
packs 6/6, compositionality 16/16 + 10/10, inference_closure 20/20 +
12/12, multi_step_reasoning 15/15 + 10/10, cross_domain_transfer
10/10 + 8/8, discourse_paragraph v1 12/12 + v2 6/6.
2026-05-16 22:44:06 -07:00
Shay
694754ab46 feat(algebra): null-preserving versor_apply path + un-skip 2 invariant tests
Closes the two skipped null-preservation tests and the architectural
gap behind them.  In CGA, null vectors represent Euclidean points;
under a conformal transformation a point must map to a point —
applying a versor sandwich to a null vector must preserve null
property.  The previous implementation forced everything onto the
unit-versor shell, which is correct for field-state propagation but
wrong for geometric point input.

Implementation
- algebra/versor.py: new `_input_is_null(F)` checks `cga_inner(F,F) ≈ 0`;
  `versor_apply` routes null inputs around `_close_applied_versor`
  and returns the raw sandwich V·F·rev(V), which algebraically
  preserves null property.  Non-null inputs unchanged.
- core-rs/src/versor.rs: `versor_apply_closed_f64` gains the same
  null-check branch via `input_is_null_f64`.  ADR-0020 parity
  preserved (8/8 versor_apply bit-identity tests still pass).

Test changes
- tests/test_architectural_invariants.py::TestINV06NullConePreservation::
  test_versor_apply_preserves_null_property — un-skipped, passes.
- tests/test_rust_backend.py::test_rust_versor_apply_preserves_null_vectors
  — un-skipped, passes.
- tests/test_versor_closure.py::test_versor_apply_closes_null_like_field_
  results_for_runtime_contract — renamed to
  test_versor_apply_preserves_null_property_for_null_inputs and
  rewritten to assert the now-correct semantics (null in → null out).
  The old contract over-specified closure for null inputs and
  contradicted the architectural invariant; that's what kept the
  invariant test skipped.

Stale gap docs updated
- inference_closure / cross_domain_transfer / multi_step_reasoning
  gaps.md now lead with a resolution block: lanes pass at 100% on
  both splits after the typed operators (transitive_walk,
  multi_relation_walk, path_recall in generate/operators.py) +
  pipeline wiring (_maybe_transitive_walk + _fold_walk_into_surface)
  landed.  The historic findings are preserved below for traceability.
- compositionality gaps.md: partial resolution — recall up from
  6.25% to 68.75%; overall_pass True; residual ~30% miss requires
  a relation-aware `compose_relations` operator (v2 follow-on).

Lane health unchanged: algebra 132, smoke 55, runtime 19, teaching 17,
packs 6, cognition 103.  Cognition eval 100%.  Four formerly-"blocked"
reasoning lanes confirmed 100% / overall_pass=True end-to-end.
2026-05-16 21:40:37 -07:00
Shay
819c8b81ac feat(phase3): compositionality, multi-step-reasoning, introspection, cross-domain-transfer v1
Spreads the four remaining Phase 3 lanes to map the full reasoning-
depth surface alongside inference-closure (already landed at e509e0d).
Each lane is a v1 honest probe per the roadmap; engineering work
follows once the full surface is visible.

Results across all five Phase 3 lanes:

  lane                      split        primary signal  foundation
  inference-closure         public/v1    0.0             1.0 / 1.0
  inference-closure         holdouts/v1  0.0             1.0 / 1.0
  compositionality          public/v1   0.0625 (1/16)   1.0 / 1.0
  compositionality          holdouts/v1  0.0             1.0 / 1.0
  multi-step-reasoning      public/v1    0.0             1.0 / 1.0
  multi-step-reasoning      holdouts/v1  0.0             1.0 / 1.0
  introspection             public/v1    0.0 (no api)    n/a
  introspection             holdouts/v1  0.0             n/a
  cross-domain-transfer     public/v1    0.0             1.0 / 1.0
  cross-domain-transfer     holdouts/v1  0.0             1.0 / 1.0

Foundation guarantees (storage + replay) intact across every lane
that has them. The reasoning-depth signal is uniformly zero. The
five lanes triangulate four architectural gaps:

  Gap 1. generate/graph_planner.py has no transitive composition.
  Gap 2. field/propagate.py has no derivable-but-not-asserted recall.
  Gap 3. core/cognition/explain.py module does not exist.
  Gap 4. no structural-pattern recogniser (cross-subdomain transfer).

Gaps 1, 2, 4 cluster on the same code surface and may close together
as a single bounded PR. Gap 3 is independent module-creation work.

Lane scaffolding mirrors inference-closure (contract.md, runner.py,
dev + public/v1 + holdouts/v1 cases.jsonl, baselines/v1_structural_zero.json,
gaps.md). All runners are parallel-safe and use the standard
run_lane(cases, *, config, workers) interface.

Per-lane gaps.md records the engineering shape for v2 plus future
directions worth not forgetting:
  - compositionality/gaps.md: metaphor is compositionality with
    selective property transfer; building it is correctly downstream
    of closing this lane.
  - cross-domain-transfer/gaps.md: metaphor + narrative as
    cross-domain operators; narrative requires the Agency open-scope
    decision to pin first.
  - introspection/gaps.md: explain API is also the substrate for
    first-person narrative self-account.

Recommended v2 sequence in docs/PROGRESS.md:
  1. Pin Agency + Tool-use open-scope decisions (deadline: before
     Phase 3 engineering).
  2. Engineer Gaps 1 + 2 as one bounded PR.
  3. Engineer Gap 3 independently.
  4. Re-author cross-domain-transfer v2 with matched-control
     contract refinement.

Phase 3 v1 exit: 0/5 lanes passing, which is the expected v1 floor.
CLI suites smoke / cognition / teaching pass; no regression on
Phase 2.
2026-05-16 14:48:36 -07:00