core/teaching/curriculum_premises.py

"""Curriculum → premise compiler (generalization arc Phase 2, ADR-0262).

The load-bearing half of the curriculum-entailment gold contract
(docs/plans/generalization-arc-2026-07-24.md §4): an exam question supplies
only the QUERY; its premises are compiled here, from the RATIFIED domain-chain
corpus of the subject being examined, and from nowhere else. Gold is therefore
a function of *(curriculum, question)* — never of case-local hidden text, and
never of what a model happens to know about the world. That is the
decoding-not-generating line in mechanical form: a fact absent from the
curriculum is UNKNOWN, however true it is.

**Ratification** (§4.3) is the same predicate the capability reporter applies
to these corpora, restated here rather than imported: a chain counts iff its
``review_status`` is ``reviewed`` AND both its subject and object lemmas are
resident in the packs the chain itself declares. The duplication is
deliberate and narrow — a serving path must not take a dependency on the
reporting subsystem, and this module must be able to state its own admission
rule in the terms the serve-time refusals name.

**Compilation is family-scoped.** A question about a `causes` relation is
answered from the `causes` chains. Restricting cannot lose an entailment (a
chain's family is fixed by its connective, so an edge that would answer the
question is always in the question's own family), and it keeps the compiled
premise set inside the reader's honesty caps as corpora grow.

The compiler emits plain English sentences — ``"force causes acceleration"`` —
because the argument bands are the decider (ADR-0256…0261). There is no
subject-specific decision code anywhere in this path: physics differs from
philosophy only in which rows load.
"""

from __future__ import annotations

import json
from dataclasses import dataclass
from functools import lru_cache
from pathlib import Path

from core.capability.domains import (
    DOMAIN_CAPABILITY_CORPORA,
    DOMAIN_CORPORA,
    DOMAIN_PACKS,
)
from generate.proof_chain.verb import MAX_PREMISE_SENTENCES

_REPO_ROOT = Path(__file__).resolve().parents[1]

#: Connective → relation family. The closed set this path serves; a chain
#: whose connective is absent is not compiled (and cannot be questioned about
#: either, so the two ends stay consistent).
#:
#: The CONNECTIVE is the sole family authority here, deliberately — not the
#: row's own ``operator_family`` field. An exam question carries a relation
#: word and nothing else, so a family derived from anything the question does
#: not carry would let premise compilation and question routing disagree, and
#: a taught edge could then be missing from the premises compiled to decide
#: it — a wrong answer built from a correct curriculum. Two corpus rows
#: currently declare a family their connective does not imply
#: (``physics-causal-008`` and one systems_software row, both
#: ``requires``/``causal``); under this rule they are read as modal, which is
#: what their connective says.
CONNECTIVE_FAMILY: dict[str, str] = {
    "causes": "causal",
    "reveals": "causal",
    "grounds": "causal",
    "requires": "modal",
    "enables": "modal",
    "precedes": "sequence",
    "opposes": "contrast",
    "supports": "evidential",
}

#: Relation families, in a stable order (the band-key axis — ADR-0262 §4).
FAMILIES: tuple[str, ...] = ("causal", "modal", "sequence", "contrast", "evidential")

#: The two row polarities (ADR-0264 R1). ``polarity`` is a ROW-LEVEL field, not
#: an ``intent`` value and not a new ``operator_family``: bands key on
#: *(domain, connective-derived family)*, so a ``modal_negative`` family would
#: create a fresh band at n=0 instead of adding refuted volume to the band it
#: belongs to. An ABSENT field reads as affirmative, which is what makes the
#: existing corpora valid unchanged.
AFFIRMATIVE = "affirmative"
NEGATIVE = "negative"
POLARITIES: tuple[str, str] = (AFFIRMATIVE, NEGATIVE)

#: ADR-0264 R2 — the sentential-negation prefix the argument reader already
#: parses (``generate/proof_chain/english.py``). Stated once here so the
#: compiled form cannot drift from the form the reader accepts.
NEGATION_PREFIX = "it is not the case that "


@dataclass(frozen=True, slots=True)
class CurriculumChain:
    """One ratified curriculum edge, as the exam path reads it."""

    chain_id: str
    subject: str
    connective: str
    obj: str
    family: str
    #: ADR-0264 R1. Defaulted, so every existing construction site stays valid
    #: and an un-migrated corpus row reads as the affirmative it always was.
    polarity: str = AFFIRMATIVE

    @property
    def negated(self) -> bool:
        return self.polarity == NEGATIVE

    @property
    def atom_sentence(self) -> str:
        """The affirmative core, independent of polarity — the ATOM this chain
        is about.

        ADR-0264 R3 in one property: a negative row must mint the *same*
        propositional atom as its affirmative counterpart, or it cannot refute
        anything. A negative row that reworded the relation would produce a
        second, unrelated atom and the query would come back UNKNOWN instead of
        REFUTED — a taught refutation silently failing to refute, which is the
        worst available outcome here because nothing goes red.
        """
        return f"{self.subject} {self.connective} {self.obj}"

    @property
    def sentence(self) -> str:
        """The English premise this chain compiles to.

        The connective is already a third-person-singular verb form, so the
        affirmative sentence lands in the verb-predicate grammar (ADR-0260)
        exactly as written. A negative row is the same sentence under the
        sentential-negation prefix (ADR-0264 R2), which the verb band reads as
        a negation OF THAT ATOM — so `(¬p, therefore p)` is a tautological
        refutation and the query decides REFUTED.
        """
        if self.negated:
            return f"{NEGATION_PREFIX}{self.atom_sentence}"
        return self.atom_sentence


@dataclass(frozen=True, slots=True)
class Curriculum:
    """The ratified curriculum of one subject — the ONLY premise source."""

    domain: str
    chains: tuple[CurriculumChain, ...]
    vocabulary: frozenset[str]

    def family(self, family: str) -> tuple[CurriculumChain, ...]:
        return tuple(c for c in self.chains if c.family == family)

    def chain_by_id(self, chain_id: str) -> CurriculumChain | None:
        return next((c for c in self.chains if c.chain_id == chain_id), None)


@lru_cache(maxsize=None)
def _pack_lemmas(pack_id: str) -> frozenset[str]:
    path = _REPO_ROOT / "packs" / "data" / pack_id / "lexicon.jsonl"
    if not path.exists():
        return frozenset()
    lemmas: set[str] = set()
    for line in path.read_text(encoding="utf-8").splitlines():
        if not line.strip():
            continue
        try:
            row = json.loads(line)
        except json.JSONDecodeError:
            continue
        lemma = row.get("lemma") if isinstance(row, dict) else None
        if isinstance(lemma, str):
            lemmas.add(lemma)
    return frozenset(lemmas)


def _domain_vocabulary(domain: str) -> frozenset[str]:
    """Every lemma the subject's mounted packs teach — the vocabulary boundary
    an exam question may not cross (§4.6 ``untaught_vocabulary``)."""
    lemmas: set[str] = set()
    for pack_id in DOMAIN_PACKS.get(domain, ()):
        lemmas |= _pack_lemmas(pack_id)
    return frozenset(lemmas)


def _ratified_rows(corpus_id: str, domain: str) -> list[dict]:
    rel = DOMAIN_CAPABILITY_CORPORA.get(corpus_id)
    if rel is None:
        return []
    path = _REPO_ROOT / rel
    if not path.exists():
        return []
    rows: list[dict] = []
    for line in path.read_text(encoding="utf-8").splitlines():
        if not line.strip():
            continue
        try:
            row = json.loads(line)
        except json.JSONDecodeError:
            continue
        if not isinstance(row, dict):
            continue
        if row.get("review_status") != "reviewed":
            continue
        if str(row.get("domain") or "").strip() != domain:
            continue
        subject = str(row.get("subject") or "").strip()
        obj = str(row.get("object") or "").strip()
        subject_pack = str(row.get("subject_pack_id") or "").strip()
        object_pack = str(row.get("object_pack_id") or "").strip()
        if not subject or not obj:
            continue
        if subject_pack and subject not in _pack_lemmas(subject_pack):
            continue
        if object_pack and obj not in _pack_lemmas(object_pack):
            continue
        rows.append(row)
    return rows


@lru_cache(maxsize=None)
def load_curriculum(domain: str) -> Curriculum:
    """The ratified curriculum for *domain* — deterministic, corpus order.

    Unratified rows, rows whose terms have left their packs, and rows whose
    connective is outside :data:`CONNECTIVE_FAMILY` are DROPPED here, at the
    admission boundary, so that everything downstream can treat every chain it
    sees as licensed premise material. A dropped chain is not a silent
    weakening of an argument the way a dropped *premise* would be (ADR-0261
    §5.1): the exam path pins chain ids and fails loudly when a pinned chain
    did not survive admission — see ``resolve_pinned``.
    """
    chains: list[CurriculumChain] = []
    for corpus_id in DOMAIN_CORPORA.get(domain, ()):
        for row in _ratified_rows(corpus_id, domain):
            connective = str(row.get("connective") or "").strip()
            family = CONNECTIVE_FAMILY.get(connective)
            if family is None:
                continue
            # ADR-0264 R1 — absent polarity IS affirmative. An UNRECOGNIZED
            # polarity is dropped here rather than guessed: reading an
            # unknown token as affirmative would turn a row someone wrote to
            # refute into a row that asserts, which is the one direction of
            # error this whole rule exists to prevent.
            polarity = str(row.get("polarity") or AFFIRMATIVE).strip().lower()
            if polarity not in POLARITIES:
                continue
            chains.append(
                CurriculumChain(
                    chain_id=str(row.get("chain_id") or ""),
                    subject=str(row.get("subject") or "").strip(),
                    connective=connective,
                    obj=str(row.get("object") or "").strip(),
                    family=family,
                    polarity=polarity,
                )
            )
    return Curriculum(
        domain=domain,
        chains=tuple(chains),
        vocabulary=_domain_vocabulary(domain),
    )


def compile_premises(
    curriculum: Curriculum,
    family: str,
    query: tuple[str, str, str] | None = None,
) -> tuple[tuple[str, ...], tuple[str, ...]]:
    """``(premise_sentences, chain_ids)`` for *family*, in corpus order.

    Without *query*, the full family is compiled unscoped — the pre-ADR-0264
    behaviour, still correct where no query exists to scope by.

    With *query* — ``(subject, connective, obj)``, the query's own terms in
    the curriculum's connective spelling — compilation is QUERY-SCOPED
    (ADR-0264 R5). The default scope is **term incidence**: every chain whose
    subject or object is one of the query's two terms. This is a superset of
    the query's own atom, and since every compiled premise mints one
    independent propositional atom that no other atom in the argument can
    constrain, a term-incidence scope decides the query identically to the
    full family — verified over 8,520 routable questions with zero verdict
    mismatches (``docs/research/curriculum-premise-scope-2026-07-25.md``
    probe 3). If term incidence would still exceed the reader's
    :data:`MAX_PREMISE_SENTENCES` cap, narrow further to the **query-atom
    rows** — chains whose ``(subject, connective, obj)`` exactly match the
    query's — which stays verdict-identical for the same reason. Scope is
    never truncated arbitrarily and never refused for size.

    Deterministic: the same curriculum, family and query always compile to
    the same sentences in the same order, so a lane report over them is
    SHA-pinnable.
    """
    chains = curriculum.family(family)
    if query is None:
        scoped = chains
    else:
        q_subject, q_connective, q_obj = query
        scoped = tuple(
            c for c in chains if c.subject in (q_subject, q_obj) or c.obj in (q_subject, q_obj)
        )
        if len(scoped) > MAX_PREMISE_SENTENCES:
            scoped = tuple(
                c
                for c in chains
                if c.subject == q_subject and c.connective == q_connective and c.obj == q_obj
            )
    return tuple(c.sentence for c in scoped), tuple(c.chain_id for c in scoped)


class UnratifiedChain(LookupError):
    """A lane case pinned a chain that is absent or did not survive admission."""


def resolve_pinned(curriculum: Curriculum, chain_ids: tuple[str, ...]) -> tuple[CurriculumChain, ...]:
    """The pinned chains, or raise (§4.3).

    A case that pins a chain the curriculum no longer ratifies MUST fail — not
    quietly answer from whatever else is present. This is the provenance guard
    that keeps "gold is a function of the curriculum" true over time: if the
    curriculum changes under a case, the case breaks loudly.
    """
    resolved: list[CurriculumChain] = []
    for chain_id in chain_ids:
        chain = curriculum.chain_by_id(chain_id)
        if chain is None:
            raise UnratifiedChain(
                f"{curriculum.domain}: pinned chain {chain_id!r} is absent or unratified"
            )
        resolved.append(chain)
    return tuple(resolved)


__all__ = [
    "AFFIRMATIVE",
    "CONNECTIVE_FAMILY",
    "FAMILIES",
    "MAX_PREMISE_SENTENCES",
    "NEGATION_PREFIX",
    "NEGATIVE",
    "POLARITIES",
    "Curriculum",
    "CurriculumChain",
    "UnratifiedChain",
    "compile_premises",
    "load_curriculum",
    "resolve_pinned",
]