Key issues fixed: - `CORE_BACKEND=numpy` was ignored, so tests mixed Python CGA embedding with Rust metric behavior. - Dense construction seeds were being rejected by strict `unitize_versor()`, while sparse dirty inputs still needed to fail closed. - Holonomy needed a construction-boundary path for raw/dense vocab fixtures and rare null final accumulators. - Proposition storage polluted vault recall by storing the live field instead of the proposition’s subject versor. - Dialogue qualitative frames rendered the same surface as assertive copular frames. - Repeated session prompts could collapse into the same deterministic response path. - Two proof fixtures were stale: one hand-built a non-null “null” vector, and one alignment proof omitted the English “with” anchor used by the resonance proof. Verification: `CORE_BACKEND=numpy CORE_STRICT_MLX_ON_APPLE=0 uv run core test -- -q` Result: `277 passed in 59.52s`
119 lines
4.1 KiB
Python
119 lines
4.1 KiB
Python
"""
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Dialogue move selection from proposition relation blades.
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The proposition layer constructs X_prompt ^ X_field. Dialogue reads that
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grade-2 relation against the prior relation blade and chooses the next move
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kind: assertion, elaboration, question/contrast, or refutation.
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"""
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from __future__ import annotations
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from dataclasses import dataclass, field
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from typing import Literal
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import numpy as np
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from algebra.cga import cga_inner, outer_product
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from field.state import FieldState
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from generate.proposition import FrameRegistry, Proposition, propose
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DialogueRole = Literal["assert", "elaborate", "question", "refute"]
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_PARALLEL_THRESHOLD = 0.35
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_ANTI_PARALLEL_THRESHOLD = -0.35
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_ORTHOGONAL_THRESHOLD = 0.20
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@dataclass(frozen=True, slots=True)
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class DialogueTurn:
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proposition: Proposition
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outer_product_blade: np.ndarray = field(repr=False)
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def __post_init__(self) -> None:
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blade = np.asarray(self.outer_product_blade, dtype=np.float32).copy()
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object.__setattr__(self, "outer_product_blade", blade)
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def blade_alignment(blade: np.ndarray, reference: np.ndarray) -> float:
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"""
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Return signed orientation of two relation blades.
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Positive values mean same plane orientation, near-zero values mean
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orthogonal relation, and negative values mean the same relation reversed.
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The scalar is derived from CORE's algebraic inner product, not an external
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approximate metric.
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"""
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blade = np.asarray(blade, dtype=np.float32)
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reference = np.asarray(reference, dtype=np.float32)
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blade_norm = abs(cga_inner(blade, blade)) ** 0.5
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reference_norm = abs(cga_inner(reference, reference)) ** 0.5
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if blade_norm < 1e-8 or reference_norm < 1e-8:
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return 0.0
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return float(-cga_inner(blade, reference) / (blade_norm * reference_norm))
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def classify_dialogue_blade(
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blade: np.ndarray,
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reference_blade: np.ndarray | None = None,
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) -> DialogueRole:
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"""
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Classify a relation blade as the next dialogue move.
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With no prior relation the engine has no contrastive plane yet, so the
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first move is an assertion. After that:
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same orientation -> elaboration
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near-orthogonal -> question/contrast
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reversed orientation -> refutation
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"""
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if reference_blade is None:
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return "assert"
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alignment = blade_alignment(blade, reference_blade)
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if alignment >= _PARALLEL_THRESHOLD:
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return "elaborate"
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if alignment <= _ANTI_PARALLEL_THRESHOLD:
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return "refute"
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if abs(alignment) <= _ORTHOGONAL_THRESHOLD:
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return "question"
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return "question"
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def trajectory_blade(blades: tuple[np.ndarray, ...] | list[np.ndarray]) -> np.ndarray | None:
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"""Fold a dialogue path into the running outer product of its blades."""
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if not blades:
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return None
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running = np.asarray(blades[0], dtype=np.float32).copy()
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for blade in blades[1:]:
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running = outer_product(running, blade)
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return running
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def propose_dialogue(
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field_state: FieldState,
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vault,
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vocab,
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frame_registry: FrameRegistry,
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reference_blade: np.ndarray | None = None,
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output_lang: str | None = None,
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) -> Proposition:
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"""
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Generate a proposition through a dialogue-role constrained frame choice.
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"""
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base = propose(field_state, None, vocab, frame_registry, output_lang=output_lang)
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role = classify_dialogue_blade(base.relation, reference_blade)
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frame = frame_registry.select_dialogue(base.relation, role)
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role_registry = FrameRegistry((frame,))
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proposition = propose(field_state, vault, vocab, role_registry, output_lang=output_lang)
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if reference_blade is not None and blade_alignment(proposition.relation, reference_blade) < 0.0:
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proposition = Proposition(
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subject=proposition.subject,
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predicate=proposition.predicate,
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object_=proposition.object_,
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surface=proposition.surface,
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frame_id=proposition.frame_id,
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subject_versor=proposition.subject_versor,
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predicate_versor=proposition.predicate_versor,
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object_versor=proposition.object_versor,
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relation=-proposition.relation,
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)
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return proposition
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