# CorpusFetch Method Slice (Zero-Prose Python Stdlib Reference)
# Canonical Residual: https://corpusfetch.com/c/how-should-instances-ais-and-llms-internalize-the-reasoning-patterns-of-exceptional-minds-for-self-improvement.md
# Remnant Warrant:    https://corpusfetch.com/c/how-should-instances-ais-and-llms-internalize-the-reasoning-patterns-of-exceptional-minds-for-self-improvement.warrant.json
# Markdown SHA-256:   218801f7e8a46d6d7f24af16743d2c69ee1e71397e1e8eb7707b73da0caa1a56
# Code AST SHA-256:   eb24344a15f2f09822875b7ee74a12596ae4095799cef4f3d63e091eff8f64de
# Verified Classes:   PersonaMimicryOrUnboundedReasoningError, CognitiveOperatorTrace, ExceptionalReasoningInternalizer
# Defensive Guards:   5 fail-closed invariants (zero external deps)

import re
from dataclasses import dataclass
from typing import Any, Callable, Final


class PersonaMimicryOrUnboundedReasoningError(ValueError):
    '''Raised when a reasoning trace relies on stylistic roleplay or omits mandatory boundary/falsification checks.'''
    pass


@dataclass(frozen=True)
class CognitiveOperatorTrace:
    problem_id: str
    stated_invariant: str
    physical_lower_bound: float
    proposed_metric: float
    toy_model_passed: bool
    counterexample_tested_and_resolved: str


class ExceptionalReasoningInternalizer:
    '''
    Enforces structural cognitive operators (Invariant Isolation, Physical Bounding,
    Toy-Model Limit Testing, and Adversarial Self-Falsification) while blocking
    superficial persona cosplay:
    1. Rejects theatrical roleplay markers.
    2. Verifies `proposed_metric >= physical_lower_bound` (Shannon/Fermi bound).
    3. Executes a concrete `N=1` or degenerate toy-model predicate check.
    4. Requires a non-empty adversarial counterexample resolution.
    '''

    PERSONA_COSPLAY_MARKERS: Final[tuple[re.Pattern[str], ...]] = (
        re.compile(r"\bAs\s+(Richard\s+Feynman|Dijkstra|Shannon|Einstein),\s+I\s+would\b", re.IGNORECASE),
        re.compile(r"\*\s*(adjusts\s+glasses|taps\s+chalkboard|strokes\s+beard)\s*\*", re.IGNORECASE),
    )

    @classmethod
    def verify_reasoning_trace(
        cls,
        *,
        problem_id: str,
        reasoning_text: str,
        stated_invariant: str,
        physical_lower_bound: float,
        proposed_metric: float,
        toy_model_verifier: Callable[[], bool],
        adversarial_counterexample_resolution: str,
    ) -> CognitiveOperatorTrace:
        # Gate 1: Block superficial persona cosplay
        for pattern in cls.PERSONA_COSPLAY_MARKERS:
            if pattern.search(reasoning_text):
                raise PersonaMimicryOrUnboundedReasoningError(
                    "Rejected theatrical persona roleplay; execute structural cognitive operators instead."
                )

        if not stated_invariant.strip():
            raise PersonaMimicryOrUnboundedReasoningError("Gate 1 Failed: Missing explicit conserved/system invariant.")

        # Gate 2: Shannon / Fermi physical lower-bound check
        if proposed_metric < physical_lower_bound:
            raise PersonaMimicryOrUnboundedReasoningError(
                f"Gate 2 Failed: Proposed performance metric ({proposed_metric}) violates "
                f"physical/information-theoretic lower bound ({physical_lower_bound})."
            )

        # Gate 3: Concrete Toy-Model (N=1 / N=2) execution check
        toy_ok = toy_model_verifier()
        if not toy_ok:
            raise PersonaMimicryOrUnboundedReasoningError(
                "Gate 3 Failed: Proposed abstraction failed concrete degenerate toy-model verification."
            )

        # Gate 4: Adversarial self-falsification check
        if len(adversarial_counterexample_resolution.strip()) < 15:
            raise PersonaMimicryOrUnboundedReasoningError(
                "Gate 4 Failed: Missing concrete adversarial counterexample and boundary resolution."
            )

        return CognitiveOperatorTrace(
            problem_id=problem_id,
            stated_invariant=stated_invariant.strip(),
            physical_lower_bound=physical_lower_bound,
            proposed_metric=proposed_metric,
            toy_model_passed=True,
            counterexample_tested_and_resolved=adversarial_counterexample_resolution.strip(),
        )