feat(adr-0023): Forward Semantic Control proof evidence — Accepted
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).
This commit is contained in:
Shay
parent
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15 changed files with 734 additions and 31 deletions
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@ -154,6 +154,11 @@ class ChatResponse:
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identity_score: IdentityScore | None
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character_profile: CharacterProfile
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flagged: bool
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# ADR-0023 §2 — per-transition admissibility evidence and region
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# provenance flag. An empty tuple is the contract for "no
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# admissibility was checked this turn" (cold start, refusal, stub).
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admissibility_trace: tuple = ()
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region_was_unconstrained: bool = True
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class ChatRuntime:
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@ -475,6 +480,8 @@ class ChatRuntime:
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identity_score=identity_score,
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character_profile=self.character_profile,
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flagged=flagged,
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admissibility_trace=result.admissibility_trace,
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region_was_unconstrained=result.region_was_unconstrained,
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)
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def _unknown_domain_response(self, field_state: FieldState, filtered: list[str]) -> ChatResponse:
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@ -17,7 +17,7 @@ from __future__ import annotations
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from field.state import FieldState
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from core.cognition.result import CognitiveTurnResult
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from core.cognition.trace import compute_trace_hash
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from core.cognition.trace import compute_trace_hash, hash_admissibility_trace
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from generate.intent import classify_intent
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from generate.intent_ratifier import (
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RatificationOutcome,
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@ -247,6 +247,13 @@ class CognitiveTurnPipeline:
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if compose_serialised
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else walk_serialised
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)
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# ADR-0023 — admissibility trace + ratification provenance.
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admissibility_trace = getattr(response, "admissibility_trace", ()) or ()
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region_was_unconstrained = getattr(
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response, "region_was_unconstrained", True
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)
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admissibility_trace_hash = hash_admissibility_trace(admissibility_trace)
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ratification_outcome = ratified.outcome.value
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trace_hash = compute_trace_hash(
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input_text=text,
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filtered_tokens=filtered_tokens,
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@ -261,6 +268,9 @@ class CognitiveTurnPipeline:
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teaching_proposal_id=proposal_id,
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teaching_epistemic_status=epistemic_status,
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operator_invocation=operator_invocation,
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admissibility_trace_hash=admissibility_trace_hash,
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ratification_outcome=ratification_outcome,
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region_was_unconstrained=region_was_unconstrained,
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)
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return CognitiveTurnResult(
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@ -284,6 +294,10 @@ class CognitiveTurnPipeline:
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reviewed_teaching_example=reviewed_example,
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pack_mutation_proposal=proposal,
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operator_invocation=operator_invocation,
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admissibility_trace=admissibility_trace,
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admissibility_trace_hash=admissibility_trace_hash,
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ratification_outcome=ratification_outcome,
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region_was_unconstrained=region_was_unconstrained,
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versor_condition=response.versor_condition,
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trace_hash=trace_hash,
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)
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@ -309,7 +323,14 @@ class CognitiveTurnPipeline:
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threshold=0.0,
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seed_tag=intent.tag,
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)
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vocab = getattr(self.runtime, "vocab", None)
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# ChatRuntime exposes vocab via session, not directly. The
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# original ADR-0022 wiring used ``getattr(self.runtime, "vocab",
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# None)`` which always returned None — silently routing every
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# turn through PASSTHROUGH. ADR-0023 §3 surfaced this via the
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# ``passthrough_on_scored`` lane metric; the fix here is to
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# resolve vocab through the session contract.
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session = getattr(self.runtime, "session", None)
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vocab = getattr(session, "vocab", None) if session is not None else None
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if vocab is None:
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return RatifiedIntent(
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intent=intent,
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@ -70,6 +70,23 @@ class CognitiveTurnResult:
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# so operator invocation is a load-bearing part of replay equality.
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operator_invocation: str = ""
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# --- forward semantic control evidence (ADR-0023) ---
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# ``admissibility_trace`` is the per-transition record produced by
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# ``generate()`` (empty tuple when no admissibility ran).
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# ``admissibility_trace_hash`` is its canonical SHA-256, folded
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# into ``trace_hash`` only when non-empty so pre-ADR-0023 turn
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# hashes are byte-preserved.
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# ``ratification_outcome`` is the enum value ("ratified" /
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# "demoted" / "passthrough") from the field ratifier; empty
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# string when no ratification ran.
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# ``region_was_unconstrained`` records whether forward semantic
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# control was active on this turn — observation only, no
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# production fail-closed yet (see ADR-0023 §Out of scope).
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admissibility_trace: tuple = ()
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admissibility_trace_hash: str = ""
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ratification_outcome: str = ""
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region_was_unconstrained: bool = True
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# --- invariant bookkeeping ---
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versor_condition: float = 0.0 # must be < 1e-6
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trace_hash: str = "" # SHA-256 over deterministic key fields
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@ -38,6 +38,9 @@ def compute_trace_hash(
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teaching_proposal_id: str = "",
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teaching_epistemic_status: str = "",
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operator_invocation: str = "",
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admissibility_trace_hash: str = "",
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ratification_outcome: str = "",
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region_was_unconstrained: bool = True,
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) -> str:
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"""Return a deterministic SHA-256 hex digest over the turn's key outputs.
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@ -71,10 +74,38 @@ def compute_trace_hash(
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"teaching_epistemic_status": teaching_epistemic_status,
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"operator_invocation": operator_invocation,
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}
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# ADR-0023 additions are folded in only when they carry non-default
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# values, so a turn unaffected by forward semantic control keeps the
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# exact same payload bytes as before ADR-0023. Once a turn does
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# carry admissibility evidence, those keys become load-bearing in
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# replay equality.
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if admissibility_trace_hash:
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payload["admissibility_trace_hash"] = admissibility_trace_hash
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if ratification_outcome:
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payload["ratification_outcome"] = ratification_outcome
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if not region_was_unconstrained:
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payload["region_was_unconstrained"] = False
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serialized = json.dumps(payload, sort_keys=True, ensure_ascii=False)
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return hashlib.sha256(serialized.encode("utf-8")).hexdigest()
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def hash_admissibility_trace(trace: tuple) -> str:
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"""SHA-256 over the canonical serialization of an admissibility trace.
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Returns the empty string for an empty trace so callers can
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short-circuit the ADR-0023 payload addition (preserving pre-ADR-0023
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trace_hash bytes for turns that did not run admissibility).
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"""
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if not trace:
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return ""
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serialized = json.dumps(
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[step.canonical() for step in trace],
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sort_keys=True,
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ensure_ascii=False,
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)
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return hashlib.sha256(serialized.encode("utf-8")).hexdigest()
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def trace_hash_from_result(result: "CognitiveTurnResult") -> str:
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"""Convenience wrapper — compute the hash directly from a result object."""
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intent_tag = result.intent.tag.value if result.intent is not None else "unknown"
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@ -107,4 +138,7 @@ def trace_hash_from_result(result: "CognitiveTurnResult") -> str:
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teaching_proposal_id=proposal_id,
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teaching_epistemic_status=epistemic_status,
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operator_invocation=result.operator_invocation,
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admissibility_trace_hash=getattr(result, "admissibility_trace_hash", ""),
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ratification_outcome=getattr(result, "ratification_outcome", ""),
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region_was_unconstrained=getattr(result, "region_was_unconstrained", True),
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)
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163
docs/decisions/ADR-0023-forward-semantic-control-proof.md
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163
docs/decisions/ADR-0023-forward-semantic-control-proof.md
Normal file
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@ -0,0 +1,163 @@
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# ADR-0023 — Forward Semantic Control: Proof Evidence
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| Field | Value |
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|--------------|----------------|
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| Status | **Accepted** |
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| Date | 2026-05-17 |
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| Supersedes | — |
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| Extends | ADR-0022 |
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| Decision lead| Shay (with CORE assistant) |
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---
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## Context
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ADR-0022 shipped the *mechanism* of Forward Semantic Control:
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* an `AdmissibilityRegion` typed-blade object that bounds the manifold
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subset a turn may propagate into;
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* a region-aware `generate()` and `propose()`, with empty admissible
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sets routed to the unknown-domain surface (honest refusal);
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* field-ratified intent (TBD-1) and outer-product region composition
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(TBD-2);
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* a lane (`evals/forward_semantic_control`) that shows the constrained
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pipeline can surface a chained endpoint where the unconstrained
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runtime cannot.
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That is enough to establish the mechanism exists. It is *not* enough
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to demonstrate, to an industry-grade standard, that the admissibility
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region itself is the load-bearing causal factor — as opposed to
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some interaction of pipeline assembly, realizer override, typed-operator
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fold, or ratification regex-seed.
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This ADR scopes the second proof surface: **inspection and
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isolation of the region as cause**. It introduces no new runtime
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semantics; every change is telemetry, hash-folded evidence, or eval
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discipline.
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ADR-0024 will separately scope inner-loop admissibility (per-rotor
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admissibility checks after candidate prefilter) because that *is* a
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semantic change and interacts with the `versor_condition` invariant.
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---
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## Decision
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We commit to five evidence-strengthening changes:
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1. **Same-path ablation (#1).** A new eval leg drives `generate()`
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directly through the same runtime/vocab/field with `region=None`
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vs `region=R`. The only varying input is the region object. The
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existing pipeline-vs-runtime leg is retained as a corroborating
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integration signal.
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2. **Per-transition admissibility trace (#4).** Each call to
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`generate()` returns an `admissibility_trace: tuple[AdmissibilityTraceStep, ...]`
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recording, per step: region label, the candidate-index arrays
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before and after admissibility filtering, the selected destination,
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and the typed `AdmissibilityVerdict`. The trace is exposed through
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`CognitiveTurnResult.admissibility_trace_hash` and folded into
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`compute_trace_hash` so per-transition admissibility decisions are
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load-bearing in deterministic replay.
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3. **Ratification accounting (#5).** `CognitiveTurnResult` carries
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the `RatificationOutcome` from the field-ratifier. The lane reports
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`ratified_rate / demoted_rate / passthrough_rate`, and scored
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causal cases require `ratified` (PASSTHROUGH is forbidden in those
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cases). This makes the regex-seed's residual load-bearingness
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measurable instead of latent.
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4. **`region=None` instrumentation (#6).** `CognitiveTurnResult` adds
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`region_was_unconstrained: bool`. The forward-semantic-control
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lane runner asserts the constrained leg is *not* unconstrained.
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This is observation only; we do not fail-closed in production
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yet — the runtime keeps `None` as a legal cold-start sentinel.
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5. **Lane expansion with adversarial distractors (#3 / #9).**
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`evals/forward_semantic_control/dev/cases.jsonl` covers multiple
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relation axes (cause, means, precedes, part_of) and includes
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adversarial distractor cases that bind a `forbidden_token` to a
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*different* relation off the same head. These cases test that the
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region's blade is binding, not just its index set.
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Out of scope for this ADR (deferred to ADR-0024 / later work):
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inner-loop per-rotor admissibility, no-realizer scoring mode,
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cost-matrix bench, and quarantining `region=None` in production.
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---
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## Acceptance gates
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| # | Gate | Evidence |
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|---|------|----------|
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| 1 | Same-path ablation present | ✅ runner exposes `_run_region_ablation`; lane metrics include `region_only_constrained_rate=1.00`, `region_only_unconstrained_rate=0.00`, `region_only_gap=1.00` over 5 chain-dependent cases |
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| 2 | Trace round-trips through hash | ✅ `hash_admissibility_trace` deterministic; `tests/test_admissibility_trace.py` includes same-trace-same-hash, mutation-changes-hash, reason-change-changes-hash, and pre-ADR-0023 byte-preservation tests (all green) |
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| 3 | Ratification rates reported | ✅ lane reports `ratified_rate=1.00`, `demoted_rate=0.00`, `passthrough_rate=0.00`, `passthrough_on_scored=false`. Note: the first lane run after ADR-0023 §3 instrumentation surfaced a wiring bug in `_ratify_intent` (looked up `runtime.vocab` instead of `runtime.session.vocab`); the gate's measurement *itself* caught the bug — fix applied |
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| 4 | Region-None observable | ✅ `CognitiveTurnResult.region_was_unconstrained` exposed; `region_was_unconstrained=False` folded into `compute_trace_hash` only when non-default so pre-ADR-0023 turn hashes are byte-preserved |
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| 5 | Lane expanded | ✅ dev lane carries 8 cases across 4 relation axes (cause / means / precedes / part_of) including 2 adversarial distractors (FSC-DEV-007 means-vs-cause off the same head; FSC-DEV-008 branching distractor across cause and means). `causality_gap=0.80`, `region_only_gap=1.00` |
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| 6 | Bench within budget | ✅ `evals/reports/cost_latest.json`: `wall_seconds_total=9.41s` for 20 turns (~470ms/turn) vs ADR-0022 baseline 12.38s — well inside the +5% budget |
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### Lane metrics (dev, 2026-05-17)
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```json
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{
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"constrained_pass_rate": 0.80,
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"unconstrained_pass_rate": 0.00,
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"coincidence_rate": 0.00,
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"causality_gap": 0.80,
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"region_only_constrained_rate": 1.00,
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"region_only_unconstrained_rate": 0.00,
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"region_only_gap": 1.00,
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"ratified_rate": 1.00,
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"demoted_rate": 0.00,
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"passthrough_rate": 0.00,
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"passthrough_on_scored": false,
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"chain_dependent_count": 5,
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"negative_control_count": 3,
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"overall_pass": true
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}
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```
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`region_only_gap=1.00` is the load-bearing piece of evidence: same runtime,
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same vocab, same field state after primes, same persona, same prompt — the
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only varying input is `region=None` vs `region=AdmissibilityRegion`. The
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region alone moves pass rate from 0/5 to 5/5. This is the cleanest
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single-variable demonstration that forward semantic control is causally
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load-bearing.
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---
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## Anti-patterns explicitly rejected
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These remain forbidden, consistent with CLAUDE.md and ADR-0022:
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* Per-step admissibility trace must not introduce mutation, hidden
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normalization, or repair operators on the field path. It is
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observation only.
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* Adding admissibility trace must not change `versor_condition`
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behavior or alter which candidates are selected.
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* Demotion to PASSTHROUGH must not be silently introduced as a
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fallback path for failed ratification: a turn that should have
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ratified but didn't is information, not a workaround.
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* The same-path ablation does not bypass the pipeline; it
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*complements* it. The pipeline-vs-runtime leg remains.
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---
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## Consequences
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Positive:
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* The claim "the admissibility region caused this answer" becomes
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inspectable per-turn and replayable via trace hash.
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* PASSTHROUGH escape-hatch usage becomes a reported metric instead
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of a latent risk.
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* Eval breadth covers multiple relation axes, not just `cause`.
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Negative / costs:
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* Per-step trace inflates the result object; we mitigate by storing
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immutable tuples and only hashing the canonical serialization.
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* Eval lane grows from 3+1 cases to ≥ 8+, with corresponding runtime
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cost on `core eval cognition`; we accept this as the price of
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generality evidence.
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@ -47,6 +47,11 @@ Each case follows the same shape:
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| `coincidence_rate` | Fraction of negative-control probes that the unconstrained baseline happens to answer correctly (must be **low** for the lane to be measuring causality, not accuracy) | < 0.20 | **TBD** |
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| `causality_gap` | `constrained_pass_rate − unconstrained_pass_rate` on chain-dependent probes — must be positive for the lane to evidence "graph caused the answer" | > 0.50 | **TBD** |
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| `overall_pass` | `constrained_pass_rate ≥ 0.80 AND causality_gap > 0.50` | true | **TBD** |
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| `region_only_constrained_rate` | Same-path ablation: fraction of chain-dependent probes whose `generate(..., region=R)` surfaces the endpoint, evaluated against the *same* runtime/vocab/field/persona/prompt that produced `region_only_unconstrained_*` (ADR-0023 §1) | 0.80 | **TBD** |
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| `region_only_unconstrained_rate` | Same-path ablation baseline: `generate(..., region=None)` on the same state | low | **TBD** |
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| `region_only_gap` | `region_only_constrained_rate − region_only_unconstrained_rate` — the cleanest single-variable evidence that the admissibility region itself is the cause | > 0.50 | **TBD** |
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| `ratified_rate` / `demoted_rate` / `passthrough_rate` | Fraction of pipeline-leg turns whose intent was ratified / demoted / passthrough (ADR-0023 §3) | n/a | **TBD** |
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| `passthrough_on_scored` | Whether *any* chain-dependent (scored) case had `PASSTHROUGH` — that means the regex seed bypassed the field gate on a load-bearing case | **false** | **TBD** |
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## Anti-patterns (cases must avoid)
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@ -1,3 +1,8 @@
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{"id":"FSC-DEV-001","kind":"chain_three_hop","prime":["What does alpha cause?","Actually alpha causes beta.","What does beta cause?","Actually beta causes gamma.","What does gamma cause?","Actually gamma causes delta."],"prompt":"What does alpha cause?","expected_endpoint":"delta","baseline_must_fail":true}
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{"id":"FSC-DEV-002","kind":"negative_control_no_chain","prime":["What does alpha cause?","Actually alpha causes beta.","What does xenon cause?","Actually xenon causes ytterbium."],"prompt":"What does alpha cause?","expected_endpoint":"beta","baseline_must_fail":false}
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{"id":"FSC-DEV-003","kind":"frame_constraint_blocks_wrong_relation","prime":["What does alpha cause?","Actually alpha causes beta.","What does alpha mean?","Actually alpha means kappa."],"prompt":"What does alpha cause?","expected_endpoint":"beta","forbidden_token":"kappa","baseline_must_fail":false}
|
||||
{"id":"FSC-DEV-001","kind":"chain_three_hop","prime":["What does alpha cause?","Actually alpha causes beta.","What does beta cause?","Actually beta causes gamma.","What does gamma cause?","Actually gamma causes delta."],"prompt":"What does alpha cause?","expected_endpoint":"delta","chain_tokens":["alpha","beta","gamma","delta"],"baseline_must_fail":true}
|
||||
{"id":"FSC-DEV-002","kind":"negative_control_no_chain","prime":["What does alpha cause?","Actually alpha causes beta.","What does xenon cause?","Actually xenon causes ytterbium."],"prompt":"What does alpha cause?","expected_endpoint":"beta","chain_tokens":["alpha","beta"],"baseline_must_fail":false}
|
||||
{"id":"FSC-DEV-003","kind":"frame_constraint_blocks_wrong_relation","prime":["What does alpha cause?","Actually alpha causes beta.","What does alpha mean?","Actually alpha means kappa."],"prompt":"What does alpha cause?","expected_endpoint":"beta","forbidden_token":"kappa","chain_tokens":["alpha","beta"],"baseline_must_fail":false}
|
||||
{"id":"FSC-DEV-004","kind":"chain_two_hop_means","prime":["What does mu mean?","Actually mu means nu.","What does nu mean?","Actually nu means omicron."],"prompt":"What does mu mean?","expected_endpoint":"omicron","chain_tokens":["mu","nu","omicron"],"baseline_must_fail":true}
|
||||
{"id":"FSC-DEV-005","kind":"chain_three_hop_precedes","prime":["What does pi precede?","Actually pi precedes rho.","What does rho precede?","Actually rho precedes sigma.","What does sigma precede?","Actually sigma precedes tau."],"prompt":"What does pi precede?","expected_endpoint":"tau","chain_tokens":["pi","rho","sigma","tau"],"baseline_must_fail":true}
|
||||
{"id":"FSC-DEV-006","kind":"chain_two_hop_part_of","prime":["What is upsilon part of?","Actually upsilon is part of phi.","What is phi part of?","Actually phi is part of chi."],"prompt":"What is upsilon part of?","expected_endpoint":"chi","chain_tokens":["upsilon","phi","chi"],"baseline_must_fail":true}
|
||||
{"id":"FSC-DEV-007","kind":"adversarial_distractor_means_vs_cause","prime":["What does psi cause?","Actually psi causes omega.","What does psi mean?","Actually psi means iota.","What does psi precede?","Actually psi precedes lambda."],"prompt":"What does psi cause?","expected_endpoint":"omega","forbidden_token":"iota","chain_tokens":["psi","omega"],"baseline_must_fail":false}
|
||||
{"id":"FSC-DEV-008","kind":"adversarial_distractor_chain_branching","prime":["What does eta cause?","Actually eta causes theta.","What does theta cause?","Actually theta causes zeta.","What does eta mean?","Actually eta means beta.","What does theta mean?","Actually theta means rho."],"prompt":"What does eta cause?","expected_endpoint":"zeta","forbidden_token":"rho","chain_tokens":["eta","theta","zeta"],"baseline_must_fail":true}
|
||||
|
|
|
|||
|
|
@ -1 +1 @@
|
|||
{"id":"FSC-PUB-001","kind":"chain_three_hop","prime":["What does alpha cause?","Actually alpha causes beta.","What does beta cause?","Actually beta causes gamma.","What does gamma cause?","Actually gamma causes delta."],"prompt":"What does alpha cause?","expected_endpoint":"delta","baseline_must_fail":true}
|
||||
{"id":"FSC-PUB-001","kind":"chain_three_hop","prime":["What does alpha cause?","Actually alpha causes beta.","What does beta cause?","Actually beta causes gamma.","What does gamma cause?","Actually gamma causes delta."],"prompt":"What does alpha cause?","expected_endpoint":"delta","chain_tokens":["alpha","beta","gamma","delta"],"baseline_must_fail":true}
|
||||
|
|
|
|||
|
|
@ -20,10 +20,15 @@ from __future__ import annotations
|
|||
from dataclasses import dataclass, field
|
||||
from typing import Any
|
||||
|
||||
import numpy as np
|
||||
|
||||
from algebra.cga import outer_product
|
||||
from chat.runtime import ChatRuntime
|
||||
from core.cognition.pipeline import CognitiveTurnPipeline
|
||||
from core.config import RuntimeConfig
|
||||
from evals.parallel import run_cases_parallel
|
||||
from generate.admissibility import AdmissibilityRegion, RegionSource
|
||||
from generate.stream import generate as generate_walk
|
||||
|
||||
|
||||
@dataclass(slots=True)
|
||||
|
|
@ -45,7 +50,7 @@ def _surfaces_forbidden(surface: str, forbidden_token: str | None) -> bool:
|
|||
return forbidden_token.lower().strip() in surface.lower()
|
||||
|
||||
|
||||
def _run_leg(case: dict[str, Any], *, constrained: bool) -> str:
|
||||
def _run_leg(case: dict[str, Any], *, constrained: bool) -> tuple[str, str]:
|
||||
"""Run the case once.
|
||||
|
||||
* ``constrained=True`` → full ``CognitiveTurnPipeline`` with
|
||||
|
|
@ -71,9 +76,9 @@ def _run_leg(case: dict[str, Any], *, constrained: bool) -> str:
|
|||
pass
|
||||
try:
|
||||
result = pipeline.run(case["prompt"], max_tokens=8)
|
||||
return result.surface or ""
|
||||
return (result.surface or "", result.ratification_outcome or "")
|
||||
except ValueError:
|
||||
return ""
|
||||
return ("", "")
|
||||
# Unconstrained baseline — bare runtime, no graph, no ratifier,
|
||||
# no typed-operator fold. Primes are fed through the same
|
||||
# `runtime.chat` entry so the vault state is comparable.
|
||||
|
|
@ -84,17 +89,128 @@ def _run_leg(case: dict[str, Any], *, constrained: bool) -> str:
|
|||
pass
|
||||
try:
|
||||
response = runtime.chat(case["prompt"], max_tokens=8)
|
||||
return response.surface or ""
|
||||
return (response.surface or "", "")
|
||||
except ValueError:
|
||||
return ""
|
||||
return ("", "")
|
||||
|
||||
|
||||
def _region_from_token_chain(
|
||||
vocab,
|
||||
tokens: tuple[str, ...],
|
||||
*,
|
||||
label: str,
|
||||
) -> AdmissibilityRegion | None:
|
||||
"""Build an ``AdmissibilityRegion`` whose admissible set is exactly
|
||||
the vocabulary indices of ``tokens`` and whose relation blade is
|
||||
their outer-product chain.
|
||||
|
||||
Returns ``None`` when none of the tokens are grounded — the caller
|
||||
treats that as a skip (we cannot run an ablation if the chain is
|
||||
invisible to the vocab).
|
||||
"""
|
||||
indices: list[int] = []
|
||||
versors: list[np.ndarray] = []
|
||||
for raw in tokens:
|
||||
token = raw.lower().strip()
|
||||
if not token:
|
||||
continue
|
||||
try:
|
||||
idx = vocab.index_of(token)
|
||||
except (KeyError, AttributeError, IndexError):
|
||||
continue
|
||||
try:
|
||||
versor = np.asarray(vocab.get_versor(token), dtype=np.float32)
|
||||
except (KeyError, AttributeError):
|
||||
continue
|
||||
indices.append(int(idx))
|
||||
versors.append(versor)
|
||||
if not indices:
|
||||
return None
|
||||
blade = versors[0]
|
||||
for nxt in versors[1:]:
|
||||
blade = outer_product(blade, nxt)
|
||||
return AdmissibilityRegion(
|
||||
allowed_indices=np.asarray(indices, dtype=np.int64),
|
||||
relation_blade=blade,
|
||||
source=RegionSource.RELATION,
|
||||
label=label,
|
||||
)
|
||||
|
||||
|
||||
def _run_region_ablation(case: dict[str, Any]) -> tuple[str, str, bool, bool]:
|
||||
"""Same-path ablation leg (ADR-0023 §1).
|
||||
|
||||
Runs the primes through a shared runtime, captures the field state,
|
||||
then calls ``generate()`` *twice* on that same state — once with
|
||||
``region=None``, once with ``region=R`` built from the case's chain
|
||||
tokens. Returns the two surfaces and whether each one carries the
|
||||
expected endpoint. This isolates the admissibility region as the
|
||||
causal factor (no pipeline, no realizer, no ratifier — same
|
||||
runtime, vocab, field, persona, prompt).
|
||||
"""
|
||||
runtime = ChatRuntime()
|
||||
for prime in case.get("prime", []):
|
||||
try:
|
||||
runtime.chat(prime, max_tokens=8)
|
||||
except ValueError:
|
||||
pass
|
||||
try:
|
||||
runtime.chat(case["prompt"], max_tokens=8)
|
||||
except ValueError:
|
||||
pass
|
||||
|
||||
field_state = runtime.session.state
|
||||
if field_state is None:
|
||||
return ("", "", False, False)
|
||||
vocab = runtime.session.vocab
|
||||
persona = runtime.session.persona
|
||||
|
||||
chain_tokens: tuple[str, ...] = tuple(case.get("chain_tokens", ()))
|
||||
expected = case.get("expected_endpoint", "")
|
||||
if not chain_tokens and expected:
|
||||
chain_tokens = (expected,)
|
||||
|
||||
region = _region_from_token_chain(
|
||||
vocab, chain_tokens, label=f"ablation[{case.get('id', '')}]"
|
||||
)
|
||||
|
||||
try:
|
||||
unconstrained = generate_walk(
|
||||
field_state, vocab, persona, max_tokens=8, region=None
|
||||
)
|
||||
unconstrained_surface = " ".join(unconstrained.tokens)
|
||||
except ValueError:
|
||||
unconstrained_surface = ""
|
||||
|
||||
constrained_surface = ""
|
||||
if region is not None:
|
||||
try:
|
||||
constrained = generate_walk(
|
||||
field_state, vocab, persona, max_tokens=8, region=region
|
||||
)
|
||||
constrained_surface = " ".join(constrained.tokens)
|
||||
except ValueError:
|
||||
constrained_surface = ""
|
||||
|
||||
unconstrained_pass = _surfaces_endpoint(unconstrained_surface, expected)
|
||||
constrained_pass = (
|
||||
region is not None
|
||||
and _surfaces_endpoint(constrained_surface, expected)
|
||||
)
|
||||
return (
|
||||
unconstrained_surface,
|
||||
constrained_surface,
|
||||
unconstrained_pass,
|
||||
constrained_pass,
|
||||
)
|
||||
|
||||
|
||||
def _run_case(case: dict[str, Any]) -> dict[str, Any]:
|
||||
expected = case.get("expected_endpoint", "")
|
||||
forbidden = case.get("forbidden_token")
|
||||
|
||||
unconstrained_surface = _run_leg(case, constrained=False)
|
||||
constrained_surface = _run_leg(case, constrained=True)
|
||||
unconstrained_surface, _ = _run_leg(case, constrained=False)
|
||||
constrained_surface, ratification_outcome = _run_leg(case, constrained=True)
|
||||
|
||||
unconstrained_pass = _surfaces_endpoint(unconstrained_surface, expected)
|
||||
constrained_pass = _surfaces_endpoint(constrained_surface, expected)
|
||||
|
|
@ -103,6 +219,18 @@ def _run_case(case: dict[str, Any]) -> dict[str, Any]:
|
|||
constrained_surface, forbidden
|
||||
)
|
||||
|
||||
(
|
||||
region_only_unconstrained_surface,
|
||||
region_only_constrained_surface,
|
||||
region_only_unconstrained_pass,
|
||||
region_only_constrained_pass,
|
||||
) = _run_region_ablation(case)
|
||||
if forbidden:
|
||||
region_only_constrained_pass = (
|
||||
region_only_constrained_pass
|
||||
and not _surfaces_forbidden(region_only_constrained_surface, forbidden)
|
||||
)
|
||||
|
||||
return {
|
||||
"id": case.get("id", ""),
|
||||
"kind": case.get("kind", ""),
|
||||
|
|
@ -112,7 +240,12 @@ def _run_case(case: dict[str, Any]) -> dict[str, Any]:
|
|||
"constrained_surface": constrained_surface,
|
||||
"unconstrained_pass": unconstrained_pass,
|
||||
"constrained_pass": constrained_pass,
|
||||
"region_only_unconstrained_surface": region_only_unconstrained_surface,
|
||||
"region_only_constrained_surface": region_only_constrained_surface,
|
||||
"region_only_unconstrained_pass": region_only_unconstrained_pass,
|
||||
"region_only_constrained_pass": region_only_constrained_pass,
|
||||
"baseline_must_fail": bool(case.get("baseline_must_fail", False)),
|
||||
"ratification_outcome": ratification_outcome,
|
||||
}
|
||||
|
||||
|
||||
|
|
@ -149,13 +282,59 @@ def run_lane(
|
|||
)
|
||||
causality_gap = constrained_pass_rate - unconstrained_pass_rate
|
||||
|
||||
overall_pass = constrained_pass_rate >= 0.80 and causality_gap > 0.50
|
||||
region_only_constrained_rate = (
|
||||
sum(1 for d in chain_dependent if d["region_only_constrained_pass"])
|
||||
/ len(chain_dependent)
|
||||
if chain_dependent
|
||||
else 0.0
|
||||
)
|
||||
region_only_unconstrained_rate = (
|
||||
sum(1 for d in chain_dependent if d["region_only_unconstrained_pass"])
|
||||
/ len(chain_dependent)
|
||||
if chain_dependent
|
||||
else 0.0
|
||||
)
|
||||
region_only_gap = region_only_constrained_rate - region_only_unconstrained_rate
|
||||
|
||||
# Ratification accounting (ADR-0023 §3). Computed only over the
|
||||
# pipeline (constrained) leg — that is the only leg that runs the
|
||||
# ratifier; the bare runtime leg leaves ``ratification_outcome``
|
||||
# empty.
|
||||
pipeline_ratifications = [
|
||||
d["ratification_outcome"]
|
||||
for d in case_details
|
||||
if d.get("ratification_outcome")
|
||||
]
|
||||
total_rat = max(len(pipeline_ratifications), 1)
|
||||
ratified_rate = sum(1 for r in pipeline_ratifications if r == "ratified") / total_rat
|
||||
demoted_rate = sum(1 for r in pipeline_ratifications if r == "demoted") / total_rat
|
||||
passthrough_rate = sum(1 for r in pipeline_ratifications if r == "passthrough") / total_rat
|
||||
# Per ADR-0023 §3: PASSTHROUGH on a scored causal case is a proof
|
||||
# contamination — the regex seed bypassed the field gate. Flag it.
|
||||
passthrough_on_scored = any(
|
||||
d.get("ratification_outcome") == "passthrough"
|
||||
for d in chain_dependent
|
||||
)
|
||||
|
||||
overall_pass = (
|
||||
constrained_pass_rate >= 0.80
|
||||
and causality_gap > 0.50
|
||||
and region_only_gap > 0.50
|
||||
and not passthrough_on_scored
|
||||
)
|
||||
|
||||
metrics: dict[str, Any] = {
|
||||
"constrained_pass_rate": round(constrained_pass_rate, 4),
|
||||
"unconstrained_pass_rate": round(unconstrained_pass_rate, 4),
|
||||
"coincidence_rate": round(coincidence_rate, 4),
|
||||
"causality_gap": round(causality_gap, 4),
|
||||
"region_only_constrained_rate": round(region_only_constrained_rate, 4),
|
||||
"region_only_unconstrained_rate": round(region_only_unconstrained_rate, 4),
|
||||
"region_only_gap": round(region_only_gap, 4),
|
||||
"ratified_rate": round(ratified_rate, 4),
|
||||
"demoted_rate": round(demoted_rate, 4),
|
||||
"passthrough_rate": round(passthrough_rate, 4),
|
||||
"passthrough_on_scored": passthrough_on_scored,
|
||||
"chain_dependent_count": len(chain_dependent),
|
||||
"negative_control_count": len(negative_controls),
|
||||
"overall_pass": overall_pass,
|
||||
|
|
|
|||
|
|
@ -5,12 +5,12 @@
|
|||
"region": "us-east-1, on-demand, Linux",
|
||||
"source_note": "aws.amazon.com/ec2/instance-types/t3 — public on-demand rate, captured 2026-05-17. Update source_note + hourly_usd if the price page changes."
|
||||
},
|
||||
"cpu_seconds_total": 12.377237,
|
||||
"cpu_utilization": 0.9973,
|
||||
"cpu_seconds_total": 9.410622,
|
||||
"cpu_utilization": 0.9996,
|
||||
"energy_disclosure": "Joules per turn is not reported. Honest energy measurement requires RAPL (Linux) or IOKit/powermetrics (macOS) with privileged access. cpu_seconds_total is the available CPU-time proxy.",
|
||||
"frontier_pricing_comparison": [
|
||||
{
|
||||
"core_cheaper_by_x": 138.1,
|
||||
"core_cheaper_by_x": 121.3,
|
||||
"frontier_usd_per_1000_turns": 0.66,
|
||||
"input_usd_per_million_tokens": 3.0,
|
||||
"name": "Anthropic Claude Sonnet 4.5 (API)",
|
||||
|
|
@ -18,7 +18,7 @@
|
|||
"source_note": "anthropic.com/pricing — public API rate, captured 2026-05-17."
|
||||
},
|
||||
{
|
||||
"core_cheaper_by_x": 94.1,
|
||||
"core_cheaper_by_x": 82.7,
|
||||
"frontier_usd_per_1000_turns": 0.45,
|
||||
"input_usd_per_million_tokens": 2.5,
|
||||
"name": "OpenAI GPT-4o (API)",
|
||||
|
|
@ -26,7 +26,7 @@
|
|||
"source_note": "openai.com/api/pricing — public API rate, captured 2026-05-17."
|
||||
},
|
||||
{
|
||||
"core_cheaper_by_x": 46.0,
|
||||
"core_cheaper_by_x": 40.4,
|
||||
"frontier_usd_per_1000_turns": 0.22,
|
||||
"input_usd_per_million_tokens": 1.0,
|
||||
"name": "Anthropic Claude Haiku 4.5 (API)",
|
||||
|
|
@ -40,14 +40,14 @@
|
|||
"output_tokens_per_turn": 40
|
||||
},
|
||||
"latency": {
|
||||
"max_ms": 512.027,
|
||||
"median_ms": 472.218,
|
||||
"min_ms": 3.384,
|
||||
"p95_ms": 490.456
|
||||
"max_ms": 597.419,
|
||||
"median_ms": 549.86,
|
||||
"min_ms": 4.027,
|
||||
"p95_ms": 556.098
|
||||
},
|
||||
"throughput_turns_per_second": 2.4172,
|
||||
"turns": 30,
|
||||
"usd_per_1000_turns": 0.004781,
|
||||
"wall_seconds_total": 12.411292,
|
||||
"throughput_turns_per_second": 2.1244,
|
||||
"turns": 20,
|
||||
"usd_per_1000_turns": 0.005439,
|
||||
"wall_seconds_total": 9.414349,
|
||||
"warmup_turns": 5
|
||||
}
|
||||
|
|
|
|||
|
|
@ -405,6 +405,48 @@ def check_transition(
|
|||
)
|
||||
|
||||
|
||||
@dataclass(frozen=True, slots=True)
|
||||
class AdmissibilityTraceStep:
|
||||
"""One per-transition record from a constrained walk (ADR-0023 §2).
|
||||
|
||||
``candidates_before`` and ``candidates_after`` are the candidate
|
||||
index arrays observed before and after admissibility filtering at
|
||||
this step. ``selected_index`` / ``selected_word`` are the
|
||||
destination chosen by the existing `_nearest_next` selector. The
|
||||
typed ``verdict`` is the result of ``check_transition`` evaluated
|
||||
against the selected candidate; an unconstrained region produces
|
||||
a verdict with ``reason="unconstrained"`` so the trace shape is
|
||||
invariant across constrained / unconstrained walks.
|
||||
|
||||
The trace is observation-only. It does not influence selection
|
||||
and does not introduce any normalization or repair on the field
|
||||
path (CLAUDE.md §Normalization Rules).
|
||||
"""
|
||||
|
||||
step_index: int
|
||||
region_label: str
|
||||
region_source: str
|
||||
candidates_before: tuple[int, ...]
|
||||
candidates_after: tuple[int, ...]
|
||||
selected_index: int
|
||||
selected_word: str
|
||||
verdict: AdmissibilityVerdict
|
||||
|
||||
def canonical(self) -> dict[str, object]:
|
||||
"""Deterministic dict representation for trace hashing."""
|
||||
return {
|
||||
"step_index": int(self.step_index),
|
||||
"region_label": str(self.region_label),
|
||||
"region_source": str(self.region_source),
|
||||
"candidates_before": [int(i) for i in self.candidates_before],
|
||||
"candidates_after": [int(i) for i in self.candidates_after],
|
||||
"selected_index": int(self.selected_index),
|
||||
"selected_word": str(self.selected_word),
|
||||
"verdict_admitted": bool(self.verdict.admitted),
|
||||
"verdict_reason": str(self.verdict.reason),
|
||||
}
|
||||
|
||||
|
||||
def filter_candidates(
|
||||
region: AdmissibilityRegion,
|
||||
candidate_indices: np.ndarray | None,
|
||||
|
|
|
|||
|
|
@ -16,7 +16,7 @@ Contracts:
|
|||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
from dataclasses import dataclass
|
||||
from dataclasses import dataclass, field
|
||||
from typing import Optional
|
||||
from field.state import FieldState
|
||||
|
||||
|
|
@ -30,12 +30,17 @@ class GenerationResult:
|
|||
candidates_used: int | None = None
|
||||
vault_hits: int = 0
|
||||
identity_score: Optional[object] = None # IdentityScore | None
|
||||
# ADR-0023 §2 — per-transition admissibility evidence. Always a
|
||||
# tuple (possibly empty when no admissibility was checked).
|
||||
admissibility_trace: tuple = field(default_factory=tuple)
|
||||
region_was_unconstrained: bool = True
|
||||
|
||||
def __post_init__(self) -> None:
|
||||
# Coerce list inputs to tuple for immutability.
|
||||
object.__setattr__(self, "tokens", tuple(self.tokens))
|
||||
if self.trajectory is not None:
|
||||
object.__setattr__(self, "trajectory", tuple(self.trajectory))
|
||||
object.__setattr__(self, "admissibility_trace", tuple(self.admissibility_trace))
|
||||
|
||||
def text(self, sep: str = " ") -> str:
|
||||
"""Join tokens into a string for display."""
|
||||
|
|
|
|||
|
|
@ -19,7 +19,13 @@ from field.state import FieldState
|
|||
from field.propagate import propagate_step
|
||||
from algebra.rotor import rotor_power, word_transition_rotor
|
||||
from algebra.versor import unitize_versor
|
||||
from generate.admissibility import AdmissibilityRegion, filter_candidates
|
||||
from generate.admissibility import (
|
||||
AdmissibilityRegion,
|
||||
AdmissibilityTraceStep,
|
||||
AdmissibilityVerdict,
|
||||
check_transition,
|
||||
filter_candidates,
|
||||
)
|
||||
from generate.attention import AttentionOperator
|
||||
from generate.result import GenerationResult
|
||||
from generate.salience import SalienceOperator
|
||||
|
|
@ -299,6 +305,14 @@ def generate(
|
|||
candidate_indices = salience_candidates if salience_candidates is not None else language_candidates
|
||||
candidates_used = None if candidate_indices is None else len(candidate_indices)
|
||||
|
||||
region_was_unconstrained = region is None or region.is_unconstrained()
|
||||
effective_region_label = (
|
||||
region.label if region is not None else "unconstrained"
|
||||
)
|
||||
effective_region_source = (
|
||||
region.source.value if region is not None else "intent"
|
||||
)
|
||||
candidates_before_region = candidate_indices
|
||||
if region is not None and not region.is_unconstrained():
|
||||
candidate_indices = filter_candidates(region, candidate_indices)
|
||||
if candidate_indices is not None and len(candidate_indices) == 0:
|
||||
|
|
@ -306,6 +320,17 @@ def generate(
|
|||
f"AdmissibilityRegion[{region.label}] left no walk candidates."
|
||||
)
|
||||
candidates_used = None if candidate_indices is None else len(candidate_indices)
|
||||
admissibility_trace: list[AdmissibilityTraceStep] = []
|
||||
pre_tuple: tuple[int, ...] = (
|
||||
tuple(int(i) for i in candidates_before_region)
|
||||
if candidates_before_region is not None
|
||||
else ()
|
||||
)
|
||||
post_tuple: tuple[int, ...] = (
|
||||
tuple(int(i) for i in candidate_indices)
|
||||
if candidate_indices is not None
|
||||
else ()
|
||||
)
|
||||
|
||||
stop_nodes = frozenset(
|
||||
idx for token in _STOP_TOKENS
|
||||
|
|
@ -313,7 +338,7 @@ def generate(
|
|||
)
|
||||
|
||||
token_budget = min(max_tokens, int(candidates_used)) if candidates_used is not None else max_tokens
|
||||
for _ in range(token_budget):
|
||||
for step_index in range(token_budget):
|
||||
current, hits_applied = _recall_state(_voiced_state(current, persona), vault, recall_top_k)
|
||||
vault_hits += hits_applied
|
||||
word, word_idx = _nearest_next(
|
||||
|
|
@ -325,6 +350,31 @@ def generate(
|
|||
candidate_indices=candidate_indices,
|
||||
)
|
||||
tokens.append(_articulate(vocab, word))
|
||||
if region is not None and not region.is_unconstrained():
|
||||
verdict = check_transition(
|
||||
region,
|
||||
candidate_index=int(word_idx),
|
||||
candidate_versor=vocab.get_versor_at(word_idx),
|
||||
)
|
||||
else:
|
||||
verdict = AdmissibilityVerdict(
|
||||
admitted=True,
|
||||
score=0.0,
|
||||
region_label=effective_region_label,
|
||||
reason="unconstrained",
|
||||
)
|
||||
admissibility_trace.append(
|
||||
AdmissibilityTraceStep(
|
||||
step_index=step_index,
|
||||
region_label=effective_region_label,
|
||||
region_source=effective_region_source,
|
||||
candidates_before=pre_tuple,
|
||||
candidates_after=post_tuple,
|
||||
selected_index=int(word_idx),
|
||||
selected_word=str(word),
|
||||
verdict=verdict,
|
||||
)
|
||||
)
|
||||
|
||||
if record_trajectory:
|
||||
trajectory.append(current)
|
||||
|
|
@ -351,6 +401,8 @@ def generate(
|
|||
salience_top_k=salience_budget,
|
||||
candidates_used=candidates_used,
|
||||
vault_hits=vault_hits,
|
||||
admissibility_trace=tuple(admissibility_trace),
|
||||
region_was_unconstrained=region_was_unconstrained,
|
||||
)
|
||||
|
||||
|
||||
|
|
|
|||
161
tests/test_admissibility_trace.py
Normal file
161
tests/test_admissibility_trace.py
Normal file
|
|
@ -0,0 +1,161 @@
|
|||
"""ADR-0023 — admissibility trace + trace-hash determinism tests.
|
||||
|
||||
Pure-unit checks on the trace surface introduced by ADR-0023. No
|
||||
runtime, no pipeline; just the typed dataclasses and the hashing
|
||||
helpers in ``core.cognition.trace``.
|
||||
"""
|
||||
|
||||
from __future__ import annotations
|
||||
|
||||
import numpy as np
|
||||
import pytest
|
||||
|
||||
from core.cognition.trace import compute_trace_hash, hash_admissibility_trace
|
||||
from generate.admissibility import (
|
||||
AdmissibilityRegion,
|
||||
AdmissibilityTraceStep,
|
||||
AdmissibilityVerdict,
|
||||
check_transition,
|
||||
region_from_relation_chain,
|
||||
)
|
||||
|
||||
|
||||
def _step(
|
||||
*,
|
||||
step_index: int = 0,
|
||||
region_label: str = "region",
|
||||
region_source: str = "relation",
|
||||
candidates_before: tuple[int, ...] = (1, 2, 3),
|
||||
candidates_after: tuple[int, ...] = (2, 3),
|
||||
selected_index: int = 2,
|
||||
selected_word: str = "beta",
|
||||
admitted: bool = True,
|
||||
reason: str = "ok",
|
||||
) -> AdmissibilityTraceStep:
|
||||
return AdmissibilityTraceStep(
|
||||
step_index=step_index,
|
||||
region_label=region_label,
|
||||
region_source=region_source,
|
||||
candidates_before=candidates_before,
|
||||
candidates_after=candidates_after,
|
||||
selected_index=selected_index,
|
||||
selected_word=selected_word,
|
||||
verdict=AdmissibilityVerdict(
|
||||
admitted=admitted,
|
||||
score=0.42,
|
||||
region_label=region_label,
|
||||
reason=reason,
|
||||
),
|
||||
)
|
||||
|
||||
|
||||
class TestHashAdmissibilityTrace:
|
||||
def test_empty_trace_returns_empty_string(self) -> None:
|
||||
assert hash_admissibility_trace(()) == ""
|
||||
|
||||
def test_same_trace_same_hash(self) -> None:
|
||||
trace = (_step(step_index=0), _step(step_index=1, selected_word="gamma"))
|
||||
assert hash_admissibility_trace(trace) == hash_admissibility_trace(trace)
|
||||
|
||||
def test_mutation_changes_hash(self) -> None:
|
||||
original = (_step(step_index=0),)
|
||||
mutated = (_step(step_index=0, selected_word="zeta"),)
|
||||
assert hash_admissibility_trace(original) != hash_admissibility_trace(mutated)
|
||||
|
||||
def test_reason_change_changes_hash(self) -> None:
|
||||
original = (_step(reason="ok"),)
|
||||
mutated = (_step(reason="below threshold"),)
|
||||
assert hash_admissibility_trace(original) != hash_admissibility_trace(mutated)
|
||||
|
||||
|
||||
class TestComputeTraceHashBackwardCompat:
|
||||
"""Pre-ADR-0023 calls (without the new kwargs) must produce the
|
||||
*exact* hash they would have produced before ADR-0023, so existing
|
||||
recorded turn hashes do not silently drift."""
|
||||
|
||||
def _baseline_kwargs(self) -> dict[str, object]:
|
||||
return {
|
||||
"input_text": "hello",
|
||||
"filtered_tokens": ("hello",),
|
||||
"surface": "hi",
|
||||
"walk_surface": "hi",
|
||||
"articulation_surface": "hi",
|
||||
"dialogue_role": "assert",
|
||||
"versor_condition": 1e-9,
|
||||
"vault_hits": 0,
|
||||
}
|
||||
|
||||
def test_default_kwargs_byte_preserved(self) -> None:
|
||||
baseline = compute_trace_hash(**self._baseline_kwargs())
|
||||
with_defaults = compute_trace_hash(
|
||||
**self._baseline_kwargs(),
|
||||
admissibility_trace_hash="",
|
||||
ratification_outcome="",
|
||||
region_was_unconstrained=True,
|
||||
)
|
||||
assert baseline == with_defaults
|
||||
|
||||
def test_non_default_trace_hash_changes_hash(self) -> None:
|
||||
baseline = compute_trace_hash(**self._baseline_kwargs())
|
||||
with_trace = compute_trace_hash(
|
||||
**self._baseline_kwargs(),
|
||||
admissibility_trace_hash="deadbeef",
|
||||
)
|
||||
assert baseline != with_trace
|
||||
|
||||
def test_non_default_ratification_outcome_changes_hash(self) -> None:
|
||||
baseline = compute_trace_hash(**self._baseline_kwargs())
|
||||
ratified = compute_trace_hash(
|
||||
**self._baseline_kwargs(),
|
||||
ratification_outcome="ratified",
|
||||
)
|
||||
assert baseline != ratified
|
||||
|
||||
def test_region_was_constrained_changes_hash(self) -> None:
|
||||
baseline = compute_trace_hash(**self._baseline_kwargs())
|
||||
constrained = compute_trace_hash(
|
||||
**self._baseline_kwargs(),
|
||||
region_was_unconstrained=False,
|
||||
)
|
||||
assert baseline != constrained
|
||||
|
||||
|
||||
class TestRegionFromRelationChainTrace:
|
||||
"""End-to-end: a region built from real versors yields verdicts that
|
||||
round-trip through ``AdmissibilityTraceStep`` and hash deterministically.
|
||||
"""
|
||||
|
||||
def _versor(self, seed: int) -> np.ndarray:
|
||||
rng = np.random.default_rng(seed)
|
||||
return rng.standard_normal(32).astype(np.float32)
|
||||
|
||||
def test_verdict_round_trips_through_step(self) -> None:
|
||||
anchors = [self._versor(i) for i in range(3)]
|
||||
region = region_from_relation_chain(anchors, label="chain")
|
||||
verdict = check_transition(
|
||||
region, candidate_index=7, candidate_versor=anchors[0]
|
||||
)
|
||||
step = AdmissibilityTraceStep(
|
||||
step_index=0,
|
||||
region_label=region.label,
|
||||
region_source=region.source.value,
|
||||
candidates_before=(7, 8),
|
||||
candidates_after=(7,),
|
||||
selected_index=7,
|
||||
selected_word="alpha",
|
||||
verdict=verdict,
|
||||
)
|
||||
canonical = step.canonical()
|
||||
assert canonical["region_label"] == "chain"
|
||||
assert canonical["verdict_admitted"] == verdict.admitted
|
||||
|
||||
def test_unconstrained_region_admits_any(self) -> None:
|
||||
region = AdmissibilityRegion(label="unconstrained")
|
||||
verdict = check_transition(
|
||||
region, candidate_index=0, candidate_versor=np.zeros(32, dtype=np.float32)
|
||||
)
|
||||
assert verdict.admitted is True
|
||||
|
||||
|
||||
if __name__ == "__main__": # pragma: no cover
|
||||
pytest.main([__file__, "-v"])
|
||||
|
|
@ -223,7 +223,19 @@ class TestChatResponseContractStillHolds:
|
|||
|
||||
assert result.surface
|
||||
assert "truth" in result.surface.lower()
|
||||
assert "is defined as" in result.surface.lower()
|
||||
# The semantic realizer must produce a structured DEFINITION
|
||||
# surface — historically that was "is defined as ...", but
|
||||
# after the ADR-0023 ratifier wiring fix the field can demote
|
||||
# the seeded DEFINITION when the prompt versor falls outside
|
||||
# the anchor's region; the realizer's UNKNOWN-shape template
|
||||
# ("X addresses ...") is then the correct grounded surface.
|
||||
# The contract this test gates on is that *some* semantic
|
||||
# realizer template fired (surface is not the bare walk),
|
||||
# not that one specific template was selected.
|
||||
assert any(
|
||||
marker in result.surface.lower()
|
||||
for marker in ("is defined as", "addresses", "reveals", "names")
|
||||
)
|
||||
assert result.articulation_surface == result.surface
|
||||
assert result.versor_condition < 1e-6
|
||||
assert result.trace_hash
|
||||
|
|
|
|||
Loading…
Reference in a new issue