teaching/math_inference_proposal.py
- MathReaderInferenceProposal frozen dataclass + ArmResult record
- build_inference_proposal() enforces all 9 invariants:
≥3 evidence rows, ≥6 trace steps including {abstraction,
test_design, test_application, test_result}, both-REJECT guard,
arm2 PASS requires cases_changed_answer==0,
ratification_effect_kind Literal=="canonicalization_bridge",
JSON-serializable payload, wrong_zero ≥40 chars
- canonical_bytes() for content-addressable inference_id
- to_jsonl_record() / from_jsonl_record() self-contained JSONL
persistence — mirrors post-#386 pattern from W1
tests/test_adr_0172_w5_inference_proposal.py — 21 tests across 11 obligations
core/cli.py — teaching suite tuple updated to include W5 test file
570 lines
20 KiB
Python
570 lines
20 KiB
Python
"""ADR-0172 Tier 2 / W5 — MathReaderInferenceProposal schema.
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Tier 2 intensional-contemplation proposal. Records a proposed structural
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equivalence (canonicalization bridge) derived from the refusal corpus.
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Each proposal carries:
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- ≥3 :class:`~teaching.math_evidence.MathReaderRefusalEvidence` pointers
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(tighter than Tier 1's ≥2);
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- a ``structural_claim`` naming the proposed equivalence class;
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- two :class:`ArmResult` records (arm1 = held-out, arm2 = known-good)
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from the two-arm self-test (W7);
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- ``ratification_effect_kind`` pinned to ``"canonicalization_bridge"``;
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- a ``wrong_zero_assertion`` (≥40 chars);
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- a :class:`~teaching.math_reasoning_trace.ReasoningTrace` carrying ≥6
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steps including ``{abstraction, test_design, test_application, test_result}``.
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Invariants enforced by :func:`build_inference_proposal`:
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1. ``domain == "math"``.
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2. ``len(evidence_pointers) >= 3``.
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3. ``reasoning_trace`` carries ≥6 steps.
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4. ``reasoning_trace`` steps include every kind in ``_REQUIRED_STEP_KINDS``.
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5. Both arms cannot simultaneously be ``"REJECT"``.
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6. Arm 2 ``"PASS"`` requires ``cases_changed_answer == 0``.
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7. ``ratification_effect_kind == "canonicalization_bridge"``.
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8. ``ratification_effect_payload`` is JSON-serializable.
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9. ``wrong_zero_assertion`` ≥ 40 chars (stripped).
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JSONL self-containment via :func:`to_jsonl_record` / :func:`from_jsonl_record`
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mirrors the post-#386 pattern from ``math_contemplation_proposal.py``.
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Trust boundary: schema-only module. No filesystem I/O, no teaching-store
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writes, no runtime pipeline hooks.
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"""
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from __future__ import annotations
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import hashlib
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import json
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from dataclasses import dataclass
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from typing import Any, Literal
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from generate.comprehension.audit import AuditRow
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from teaching.math_evidence import MathReaderRefusalEvidence
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from teaching.math_reasoning_trace import ReasoningStep, ReasoningTrace, build_trace
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# ---------------------------------------------------------------------------
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# Constants
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# ---------------------------------------------------------------------------
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ArmOutcome = Literal["PASS", "NEUTRAL", "REJECT"]
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ArmName = Literal["arm1_held_out", "arm2_known_good"]
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_ARM_OUTCOMES: frozenset[str] = frozenset({"PASS", "NEUTRAL", "REJECT"})
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_ARM_NAMES: frozenset[str] = frozenset({"arm1_held_out", "arm2_known_good"})
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_EVIDENCE_FLOOR: int = 3
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_REQUIRED_STEP_KINDS: frozenset[str] = frozenset({
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"abstraction",
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"test_design",
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"test_application",
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"test_result",
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})
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_MIN_TRACE_STEPS: int = 6
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_WRONG_ZERO_MIN_LEN: int = 40
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# ---------------------------------------------------------------------------
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# ArmResult
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# ---------------------------------------------------------------------------
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@dataclass(frozen=True)
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class ArmResult:
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"""Outcome record for one self-test arm.
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Fields
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------
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arm:
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``"arm1_held_out"`` — 30% held-out refusal subset, or
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``"arm2_known_good"`` — prior admitted-with-correct-answer set.
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outcome:
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``"PASS"`` | ``"NEUTRAL"`` | ``"REJECT"``.
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cases_tested:
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Total cases evaluated in this arm.
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cases_admitted:
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Cases where the bridge produced an admission result.
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cases_changed_answer:
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Cases where a previously-correct answer changed under the bridge.
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Must be 0 when arm is ``"arm2_known_good"`` and outcome is ``"PASS"``.
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"""
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arm: ArmName
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outcome: ArmOutcome
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cases_tested: int
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cases_admitted: int
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cases_changed_answer: int
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def build_arm_result(
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*,
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arm: str,
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outcome: str,
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cases_tested: int,
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cases_admitted: int,
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cases_changed_answer: int,
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) -> ArmResult:
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"""Build an :class:`ArmResult` with basic field validation."""
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if arm not in _ARM_NAMES:
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raise ValueError(
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f"arm must be one of {sorted(_ARM_NAMES)}; got {arm!r}"
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)
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if outcome not in _ARM_OUTCOMES:
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raise ValueError(
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f"outcome must be one of {sorted(_ARM_OUTCOMES)}; got {outcome!r}"
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)
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if cases_tested < 0:
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raise ValueError(f"cases_tested must be ≥0; got {cases_tested}")
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if cases_admitted < 0:
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raise ValueError(f"cases_admitted must be ≥0; got {cases_admitted}")
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if cases_changed_answer < 0:
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raise ValueError(f"cases_changed_answer must be ≥0; got {cases_changed_answer}")
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return ArmResult(
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arm=arm, # type: ignore[arg-type]
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outcome=outcome, # type: ignore[arg-type]
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cases_tested=cases_tested,
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cases_admitted=cases_admitted,
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cases_changed_answer=cases_changed_answer,
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)
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# ---------------------------------------------------------------------------
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# Schema
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# ---------------------------------------------------------------------------
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@dataclass(frozen=True)
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class MathReaderInferenceProposal:
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"""One proposed canonicalization bridge for the math domain (Tier 2).
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Construct via :func:`build_inference_proposal` — do not instantiate
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directly (``inference_id`` is content-derived).
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Fields
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------
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inference_id:
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``sha256(canonical_bytes(...)).hexdigest()`` over all other fields.
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domain:
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Always ``"math"``.
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structural_claim:
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Human-readable description of the proposed equivalence class.
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evidence_pointers:
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≥3 :class:`MathReaderRefusalEvidence` records.
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arm1_result:
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Two-arm self-test result for the held-out subset.
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arm2_result:
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Two-arm self-test result for the known-good set.
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ratification_effect_kind:
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Always ``"canonicalization_bridge"`` for Tier 2 proposals.
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ratification_effect_payload:
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JSON-serializable payload describing the bridge implementation.
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wrong_zero_assertion:
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≥40-char statement pinning the wrong=0 invariant.
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replay_equivalence_hash:
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``sha256`` digest of the replay-equivalence gate output.
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reasoning_trace:
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:class:`~teaching.math_reasoning_trace.ReasoningTrace` carrying ≥6
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steps, including ``{abstraction, test_design, test_application,
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test_result}``.
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"""
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inference_id: str
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domain: Literal["math"]
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structural_claim: str
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evidence_pointers: tuple[MathReaderRefusalEvidence, ...]
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arm1_result: ArmResult
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arm2_result: ArmResult
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ratification_effect_kind: Literal["canonicalization_bridge"]
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ratification_effect_payload: object
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wrong_zero_assertion: str
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replay_equivalence_hash: str
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reasoning_trace: ReasoningTrace
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# ---------------------------------------------------------------------------
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# Canonical-bytes serialization (content-hash; not round-trip)
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# ---------------------------------------------------------------------------
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def _arm_result_to_canonical(arm: ArmResult) -> dict[str, Any]:
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return {
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"arm": arm.arm,
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"cases_admitted": arm.cases_admitted,
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"cases_changed_answer": arm.cases_changed_answer,
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"cases_tested": arm.cases_tested,
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"outcome": arm.outcome,
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}
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def canonical_bytes(proposal: MathReaderInferenceProposal) -> bytes:
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"""Return deterministic canonical bytes over all fields except inference_id.
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Evidence pointers are reduced to their ``evidence_hash`` digests;
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``reasoning_trace`` is reduced to its ``trace_id``. Stable across
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processes and dict insertion order.
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"""
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payload: dict[str, Any] = {
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"arm1_result": _arm_result_to_canonical(proposal.arm1_result),
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"arm2_result": _arm_result_to_canonical(proposal.arm2_result),
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"domain": proposal.domain,
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"evidence_pointers": sorted(
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ev.evidence_hash for ev in proposal.evidence_pointers
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),
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"ratification_effect_kind": proposal.ratification_effect_kind,
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"ratification_effect_payload": proposal.ratification_effect_payload,
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"reasoning_trace_id": proposal.reasoning_trace.trace_id,
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"replay_equivalence_hash": proposal.replay_equivalence_hash,
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"structural_claim": proposal.structural_claim,
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"wrong_zero_assertion": proposal.wrong_zero_assertion,
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}
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return json.dumps(
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payload,
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ensure_ascii=False,
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sort_keys=True,
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separators=(",", ":"),
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).encode("utf-8")
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def compute_inference_id(
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*,
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domain: Literal["math"],
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structural_claim: str,
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evidence_pointers: tuple[MathReaderRefusalEvidence, ...],
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arm1_result: ArmResult,
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arm2_result: ArmResult,
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ratification_effect_kind: Literal["canonicalization_bridge"],
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ratification_effect_payload: object,
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wrong_zero_assertion: str,
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replay_equivalence_hash: str,
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reasoning_trace: ReasoningTrace,
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) -> str:
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"""Hash all content fields to produce a stable ``inference_id``."""
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placeholder = MathReaderInferenceProposal(
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inference_id="",
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domain=domain,
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structural_claim=structural_claim,
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evidence_pointers=evidence_pointers,
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arm1_result=arm1_result,
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arm2_result=arm2_result,
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ratification_effect_kind=ratification_effect_kind,
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ratification_effect_payload=ratification_effect_payload,
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wrong_zero_assertion=wrong_zero_assertion,
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replay_equivalence_hash=replay_equivalence_hash,
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reasoning_trace=reasoning_trace,
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)
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return hashlib.sha256(canonical_bytes(placeholder)).hexdigest()
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# ---------------------------------------------------------------------------
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# Factory
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# ---------------------------------------------------------------------------
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def build_inference_proposal(
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*,
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domain: Literal["math"] = "math",
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structural_claim: str,
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evidence_pointers: tuple[MathReaderRefusalEvidence, ...],
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arm1_result: ArmResult,
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arm2_result: ArmResult,
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ratification_effect_kind: str,
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ratification_effect_payload: object,
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wrong_zero_assertion: str,
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replay_equivalence_hash: str,
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reasoning_trace: ReasoningTrace,
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) -> MathReaderInferenceProposal:
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"""Build a :class:`MathReaderInferenceProposal` with all invariants enforced.
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Raises ``ValueError`` on any violation; the caller must fix the inputs.
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"""
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if domain != "math":
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raise ValueError(f"domain must be 'math'; got {domain!r}")
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if len(evidence_pointers) < _EVIDENCE_FLOOR:
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raise ValueError(
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f"evidence_pointers requires ≥{_EVIDENCE_FLOOR} entries; "
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f"got {len(evidence_pointers)}"
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)
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if not isinstance(reasoning_trace, ReasoningTrace):
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raise ValueError(
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f"reasoning_trace must be a ReasoningTrace instance; "
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f"got {type(reasoning_trace).__name__}"
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)
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if len(reasoning_trace.steps) < _MIN_TRACE_STEPS:
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raise ValueError(
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f"reasoning_trace must carry ≥{_MIN_TRACE_STEPS} steps; "
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f"got {len(reasoning_trace.steps)}"
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)
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present_kinds = {step.step_kind for step in reasoning_trace.steps}
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missing_kinds = _REQUIRED_STEP_KINDS - present_kinds
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if missing_kinds:
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raise ValueError(
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f"reasoning_trace is missing required step kind(s): "
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f"{sorted(missing_kinds)}; found kinds: {sorted(present_kinds)}"
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)
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if arm1_result.outcome == "REJECT" and arm2_result.outcome == "REJECT":
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raise ValueError(
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"both arms cannot simultaneously be REJECT at construction; "
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"proposals with two REJECT arms must not surface to the schema layer"
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)
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if arm2_result.outcome == "PASS" and arm2_result.cases_changed_answer != 0:
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raise ValueError(
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f"arm2 PASS requires cases_changed_answer == 0; "
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f"got {arm2_result.cases_changed_answer}"
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)
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if ratification_effect_kind != "canonicalization_bridge":
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raise ValueError(
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f"ratification_effect_kind must be 'canonicalization_bridge'; "
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f"got {ratification_effect_kind!r}"
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)
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try:
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json.dumps(
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ratification_effect_payload,
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ensure_ascii=False,
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separators=(",", ":"),
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)
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except (TypeError, ValueError) as exc:
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raise ValueError(
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f"ratification_effect_payload is not JSON-serializable: {exc}"
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) from exc
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if not wrong_zero_assertion or len(wrong_zero_assertion.strip()) < _WRONG_ZERO_MIN_LEN:
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raise ValueError(
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f"wrong_zero_assertion must be ≥{_WRONG_ZERO_MIN_LEN} chars (non-empty); "
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f"got {len(wrong_zero_assertion)!r}"
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)
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iid = compute_inference_id(
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domain=domain,
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structural_claim=structural_claim,
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evidence_pointers=evidence_pointers,
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arm1_result=arm1_result,
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arm2_result=arm2_result,
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ratification_effect_kind="canonicalization_bridge",
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ratification_effect_payload=ratification_effect_payload,
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wrong_zero_assertion=wrong_zero_assertion,
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replay_equivalence_hash=replay_equivalence_hash,
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reasoning_trace=reasoning_trace,
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)
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return MathReaderInferenceProposal(
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inference_id=iid,
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domain=domain,
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structural_claim=structural_claim,
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evidence_pointers=tuple(evidence_pointers),
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arm1_result=arm1_result,
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arm2_result=arm2_result,
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ratification_effect_kind="canonicalization_bridge",
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ratification_effect_payload=ratification_effect_payload,
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wrong_zero_assertion=wrong_zero_assertion,
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replay_equivalence_hash=replay_equivalence_hash,
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reasoning_trace=reasoning_trace,
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)
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# ---------------------------------------------------------------------------
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# Self-contained JSONL persistence serializer
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# ---------------------------------------------------------------------------
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#
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# canonical_bytes() is the content-hash function; it reduces evidence_pointers
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# to evidence_hashes and reasoning_trace to its trace_id. That is correct
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# for inference_id derivation but not for round-tripping through disk.
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#
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# to_jsonl_record() / from_jsonl_record() emit a self-contained record so the
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# workbench and HITL queue can read proposals.jsonl without re-running the
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# two-arm loop (W7).
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#
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# Determinism contract: sort_keys=True, compact separators, no floats.
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def _audit_row_to_dict(row: AuditRow) -> dict[str, Any]:
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return {
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"case_id": row.case_id,
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"sentence_index": row.sentence_index,
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"token_index": row.token_index,
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"token_text": row.token_text,
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"recognized_terms": list(row.recognized_terms),
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"skipped_frame": row.skipped_frame,
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"missing_operator": row.missing_operator,
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"refusal_reason": row.refusal_reason,
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"refusal_detail": row.refusal_detail,
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}
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def _audit_row_from_dict(data: dict[str, Any]) -> AuditRow:
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return AuditRow(
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case_id=str(data["case_id"]),
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sentence_index=int(data["sentence_index"]),
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token_index=int(data["token_index"]),
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token_text=str(data["token_text"]),
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recognized_terms=tuple(data.get("recognized_terms") or ()),
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skipped_frame=data.get("skipped_frame"),
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missing_operator=data.get("missing_operator"),
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refusal_reason=str(data.get("refusal_reason", "")),
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refusal_detail=str(data.get("refusal_detail", "")),
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)
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def _evidence_to_dict(ev: MathReaderRefusalEvidence) -> dict[str, Any]:
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return {
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"case_id": ev.case_id,
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"sentence_index": ev.sentence_index,
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"token_index": ev.token_index,
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"refusal_reason": ev.refusal_reason,
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"missing_operator": ev.missing_operator,
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"claim_signature": ev.claim_signature,
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"evidence_hash": ev.evidence_hash,
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"sub_type": ev.sub_type,
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"audit_row": _audit_row_to_dict(ev.audit_row),
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}
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def _evidence_from_dict(data: dict[str, Any]) -> MathReaderRefusalEvidence:
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return MathReaderRefusalEvidence(
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case_id=str(data["case_id"]),
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sentence_index=int(data["sentence_index"]),
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token_index=int(data["token_index"]),
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refusal_reason=str(data["refusal_reason"]),
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missing_operator=data.get("missing_operator"),
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claim_signature=str(data.get("claim_signature", "")),
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evidence_hash=str(data["evidence_hash"]),
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audit_row=_audit_row_from_dict(data["audit_row"]),
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sub_type=data["sub_type"],
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)
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def _arm_result_to_dict(arm: ArmResult) -> dict[str, Any]:
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return {
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"arm": arm.arm,
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"outcome": arm.outcome,
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"cases_tested": arm.cases_tested,
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"cases_admitted": arm.cases_admitted,
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"cases_changed_answer": arm.cases_changed_answer,
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}
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def _arm_result_from_dict(data: dict[str, Any]) -> ArmResult:
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return ArmResult(
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arm=data["arm"],
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outcome=data["outcome"],
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cases_tested=int(data["cases_tested"]),
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cases_admitted=int(data["cases_admitted"]),
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cases_changed_answer=int(data["cases_changed_answer"]),
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)
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def _step_to_dict(step: ReasoningStep) -> dict[str, Any]:
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return {
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"step_index": step.step_index,
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"step_kind": step.step_kind,
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"input_pointers": list(step.input_pointers),
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"claim": step.claim,
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"justification": step.justification,
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"output_payload": step.output_payload,
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}
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def _step_from_dict(data: dict[str, Any]) -> ReasoningStep:
|
|
return ReasoningStep(
|
|
step_index=int(data["step_index"]),
|
|
step_kind=data["step_kind"],
|
|
input_pointers=tuple(str(p) for p in data.get("input_pointers", ())),
|
|
claim=str(data.get("claim", "")),
|
|
justification=str(data.get("justification", "")),
|
|
output_payload=data.get("output_payload"),
|
|
)
|
|
|
|
|
|
def to_jsonl_record(proposal: MathReaderInferenceProposal) -> dict[str, Any]:
|
|
"""Return a self-contained dict representation suitable for JSONL persistence.
|
|
|
|
Unlike :func:`canonical_bytes`, this record includes:
|
|
- ``inference_id`` (so consumers don't need to recompute it)
|
|
- full ``evidence_pointers`` (nested dicts — not just hashes)
|
|
- full ``arm1_result`` and ``arm2_result``
|
|
- full ``reasoning_trace.steps`` (inline — not just trace_id)
|
|
|
|
The output is JSON-serializable. Encoding via
|
|
``json.dumps(record, sort_keys=True, separators=(",", ":"),
|
|
ensure_ascii=False)`` produces deterministic byte-identical output.
|
|
"""
|
|
return {
|
|
"inference_id": proposal.inference_id,
|
|
"domain": proposal.domain,
|
|
"structural_claim": proposal.structural_claim,
|
|
"evidence_pointers": [
|
|
_evidence_to_dict(ev) for ev in proposal.evidence_pointers
|
|
],
|
|
"arm1_result": _arm_result_to_dict(proposal.arm1_result),
|
|
"arm2_result": _arm_result_to_dict(proposal.arm2_result),
|
|
"ratification_effect_kind": proposal.ratification_effect_kind,
|
|
"ratification_effect_payload": proposal.ratification_effect_payload,
|
|
"wrong_zero_assertion": proposal.wrong_zero_assertion,
|
|
"replay_equivalence_hash": proposal.replay_equivalence_hash,
|
|
"reasoning_trace": {
|
|
"trace_id": proposal.reasoning_trace.trace_id,
|
|
"steps": [_step_to_dict(s) for s in proposal.reasoning_trace.steps],
|
|
},
|
|
}
|
|
|
|
|
|
def from_jsonl_record(record: dict[str, Any]) -> MathReaderInferenceProposal:
|
|
"""Reconstruct a proposal from a :func:`to_jsonl_record` dict.
|
|
|
|
Goes through :func:`build_inference_proposal` so all invariants are
|
|
re-validated. The reconstructed ``inference_id`` must match the
|
|
persisted one — mismatch indicates tampering or schema drift and
|
|
raises :class:`ValueError`.
|
|
"""
|
|
evidence_records = tuple(
|
|
_evidence_from_dict(d) for d in record.get("evidence_pointers", ())
|
|
)
|
|
steps = tuple(_step_from_dict(d) for d in record["reasoning_trace"]["steps"])
|
|
trace = build_trace(steps)
|
|
|
|
arm1 = _arm_result_from_dict(record["arm1_result"])
|
|
arm2 = _arm_result_from_dict(record["arm2_result"])
|
|
|
|
proposal = build_inference_proposal(
|
|
domain=record.get("domain", "math"),
|
|
structural_claim=str(record["structural_claim"]),
|
|
evidence_pointers=evidence_records,
|
|
arm1_result=arm1,
|
|
arm2_result=arm2,
|
|
ratification_effect_kind=str(record["ratification_effect_kind"]),
|
|
ratification_effect_payload=record.get("ratification_effect_payload"),
|
|
wrong_zero_assertion=str(record["wrong_zero_assertion"]),
|
|
replay_equivalence_hash=str(record["replay_equivalence_hash"]),
|
|
reasoning_trace=trace,
|
|
)
|
|
|
|
persisted_id = str(record.get("inference_id", ""))
|
|
if persisted_id and persisted_id != proposal.inference_id:
|
|
raise ValueError(
|
|
"inference_id mismatch on JSONL round-trip: persisted "
|
|
f"{persisted_id!r} != recomputed {proposal.inference_id!r}"
|
|
)
|
|
return proposal
|
|
|
|
|
|
__all__ = [
|
|
"ArmName",
|
|
"ArmOutcome",
|
|
"ArmResult",
|
|
"MathReaderInferenceProposal",
|
|
"build_arm_result",
|
|
"build_inference_proposal",
|
|
"canonical_bytes",
|
|
"compute_inference_id",
|
|
"from_jsonl_record",
|
|
"to_jsonl_record",
|
|
]
|