core/generate/quantitative_comprehension.py

"""Arithmetic word-problem comprehension -> binding_graph (Phase 2b, domain 5).

The doctrine-aligned quantity reader, and the binding-graph's FIRST comprehension
consumer. Quantities live in the ``binding_graph`` substrate — CLAUDE.md: the
``MeaningGraph`` deliberately excludes quantities — so this reader lives OUTSIDE
``generate/meaning_graph`` (which stays a numeric-free interlingua, INV-28) and
targets the binding-graph instead.

It reads arithmetic prose ("Liam has 6 stickers. Mia has 4 more stickers than
Liam.") into ``SymbolBinding`` / ``BoundFact`` / ``BoundEquation`` and runs the
REAL ``check_admissibility`` — there is NO stamped "admitted": an equation is
admitted only if its operand units actually verify, and a dimensional mismatch
REFUSES the whole reading. ``to_relational_metric`` then projects the binding-graph
into the independent ``relational_metric`` oracle for scoring.

Templates (function-word + order; digits only — a non-digit quantity REFUSES):
  - ``<X> has <N> <unit>``                 -> BoundFact(X = N [unit])
  - ``<Y> has <N> more <unit> than <X>``   -> BoundEquation(Y = X + N)   op=add
  - ``<Y> has <N> fewer <unit> than <X>``  -> BoundEquation(Y = X - N)   op=subtract
  - query ``How many <unit> does <Y> have``       -> ask Y
  - query ``How many <unit> do <X> and <Y> have`` -> total = X + Y; ask total

Refusal-first: an unparseable clause, a non-digit quantity, a non-identifier name,
a missing/duplicated query, or an admissibility refusal all return a typed
``Refusal`` — never a fabricated quantity (wrong=0 at the comprehension layer).
"""

from __future__ import annotations

from dataclasses import dataclass
from typing import Any

from generate.binding_graph.admissibility import AdmissibilityError, check_admissibility
from generate.binding_graph.model import (
    BoundEquation,
    BoundFact,
    BoundUnknown,
    SemanticSymbolicBindingGraph,
    SourceSpanLink,
    SymbolBinding,
)
from generate.binding_graph.units import UnitAlgebraError, parse_unit
from generate.meaning_graph.reader import Refusal, _split_sentences

_INTRODUCED_BY = "comprehend_quantitative"

#: The generic count dimension for discrete sortal objects (an existing pack
#: lemma resolving to dimension ``count``). A noun the unit pack does not know is
#: read as a count of discrete objects, NOT faked into a physical unit.
_COUNT_UNIT = "item"


def _resolve_unit(noun: str) -> str:
    """Map a surface unit noun to a binding-graph unit the pack accepts.

    A KNOWN physical/currency/count unit (``dollars`` -> ``dollar``, ``meters``)
    is used verbatim (``parse_unit`` depluralizes). An UNKNOWN sortal noun
    (``stickers``, ``coins``) is a count of discrete objects -> ``item`` (dimension
    ``count``). This keeps admissibility a REAL check: ``count + count`` admits,
    ``count + length`` still refuses — nothing is stamped or faked.
    """
    try:
        parse_unit(noun)
    except UnitAlgebraError:
        return _COUNT_UNIT
    return noun


@dataclass(frozen=True, slots=True)
class QuantQuery:
    """The question over the comprehended quantities (which entity's count)."""

    entity: str
    unit: str
    span: SourceSpanLink


@dataclass(frozen=True, slots=True)
class QuantComprehension:
    """Successful arithmetic comprehension: a binding_graph + the asked entity."""

    binding_graph: SemanticSymbolicBindingGraph
    query: QuantQuery


class _QReject(Exception):
    """Internal: a clause matched a shape but is not honestly readable."""

    def __init__(self, reason: str, detail: str = "") -> None:
        super().__init__(reason)
        self.refusal = Refusal(reason, detail)


def _ident(tok: str, detail: str) -> str:
    w = tok.strip().lower()
    if not w.isidentifier():
        raise _QReject("non_identifier_name", detail)
    return w


def _int(tok: str, detail: str) -> int:
    if not tok.isdigit():
        raise _QReject("non_digit_quantity", detail)
    return int(tok)


@dataclass(frozen=True, slots=True)
class _Fact:
    entity: str
    value: int
    unit: str


@dataclass(frozen=True, slots=True)
class _Eq:
    entity: str
    ref: str
    delta: int
    op: str  # "add" | "subtract"
    unit: str


def _parse_sentence(body: str, detail: str):
    """Return a (_Fact | _Eq | ('query', entity, unit) | ('sumquery', parts, unit))
    spec, or None if the sentence matches no arithmetic template."""
    toks = body.strip().lower().rstrip("?.!").split()
    if not toks:
        return None

    if len(toks) >= 5 and toks[0] == "how" and toks[1] == "many" and toks[-1] == "have":
        unit = _resolve_unit(_ident(toks[2], detail))
        rest = toks[3:-1]  # between "<unit>" and "have"
        if rest and rest[0] == "does" and len(rest) == 2:
            return ("query", _ident(rest[1], detail), unit)
        if rest and rest[0] == "do":
            parts = [_ident(t, detail) for t in rest[1:] if t != "and"]
            if len(parts) >= 2:
                return ("sumquery", tuple(parts), unit)
        raise _QReject("unreadable_quantity_query", detail)

    if len(toks) >= 4 and toks[1] == "has":
        entity = _ident(toks[0], detail)
        value = _int(toks[2], detail)
        if len(toks) == 4:
            return _Fact(entity, value, _resolve_unit(_ident(toks[3], detail)))
        if len(toks) == 7 and toks[3] in ("more", "fewer") and toks[5] == "than":
            op = "add" if toks[3] == "more" else "subtract"
            return _Eq(
                entity, _ident(toks[6], detail), value, op, _resolve_unit(_ident(toks[4], detail))
            )
        raise _QReject("unreadable_quantity_clause", detail)

    return None


def _span(text: str) -> SourceSpanLink:
    return SourceSpanLink(source_id="input", start=0, end=max(1, len(text)), text=text or " ")


def _rhs(op: str, ref: str, delta: int) -> str:
    return f"{ref} + {delta}" if op == "add" else f"{ref} - {delta}"


def comprehend_quantitative(text: str, source_id: str = "input") -> QuantComprehension | Refusal:
    """Comprehend arithmetic prose into a binding_graph + asked entity, or refuse."""
    if not text or not text.strip():
        return Refusal("empty")
    sentences = _split_sentences(text)
    if not sentences:
        return Refusal("empty")

    facts: list[_Fact] = []
    eqs: list[_Eq] = []
    queries: list[tuple] = []

    try:
        for body, _terminator, _start, _end in sentences:
            spec = _parse_sentence(body, body)
            if spec is None:
                return Refusal("no_quantity_template", body)
            if isinstance(spec, _Fact):
                facts.append(spec)
            elif isinstance(spec, _Eq):
                eqs.append(spec)
            else:
                queries.append(spec)
    except _QReject as rej:
        return rej.refusal

    if len(queries) != 1 or not facts:
        return Refusal("no_single_quantity_query")

    unit_of: dict[str, str] = {}
    role_of: dict[str, str] = {}
    for f in facts:
        unit_of[f.entity], role_of[f.entity] = f.unit, "count"
    for e in eqs:
        unit_of[e.entity], role_of[e.entity] = e.unit, "count"

    query = queries[0]
    sum_eq: tuple[str, tuple[str, ...]] | None = None
    if query[0] == "query":
        ask_entity, ask_unit = query[1], query[2]
    else:  # sumquery -> synthesize a total symbol + sum equation
        parts, ask_unit = query[1], query[2]
        ask_entity = "total"
        unit_of.setdefault(ask_entity, ask_unit)
        role_of[ask_entity] = "total"
        sum_eq = (ask_entity, parts)

    referenced: set[str] = set()
    for f in facts:
        referenced.add(f.entity)
    for e in eqs:
        referenced.update((e.entity, e.ref))
    if sum_eq is not None:
        referenced.add(sum_eq[0])
        referenced.update(sum_eq[1])
    referenced.add(ask_entity)

    symbols = [
        SymbolBinding(
            symbol_id=sid,
            name=sid,
            semantic_role=role_of.get(sid, "count"),
            source_span=_span(sid),
            introduced_by=_INTRODUCED_BY,
            entity=sid,
            unit=unit_of.get(sid),
        )
        for sid in sorted(referenced)
    ]
    symbols_by_id = {s.symbol_id: s for s in symbols}

    bound_facts = tuple(
        BoundFact(symbol_id=f.entity, value=str(f.value), source_span=_span(f.entity), unit=f.unit)
        for f in facts
    )

    # equations: shell -> REAL admissibility -> rebuild (NEVER stamp "admitted").
    eq_specs: list[tuple[str, str, frozenset[str], str]] = [
        (e.entity, _rhs(e.op, e.ref, e.delta), frozenset({e.ref}), e.op) for e in eqs
    ]
    if sum_eq is not None:
        lhs, parts = sum_eq
        eq_specs.append((lhs, " + ".join(parts), frozenset(parts), "add"))

    equations: list[BoundEquation] = []
    for lhs, rhs, deps, op in eq_specs:
        shell = BoundEquation(
            lhs_symbol_id=lhs,
            rhs_canonical=rhs,
            dependencies=deps,
            operation_kind=op,
            unit_proof="pending",
            admissibility_status="pending",
            source_span=_span(lhs),
        )
        try:
            proof = check_admissibility(shell, symbols=symbols_by_id)
        except AdmissibilityError as exc:
            return Refusal("admissibility_refused", f"{lhs}: {exc.reason}")
        equations.append(
            BoundEquation(
                lhs_symbol_id=lhs,
                rhs_canonical=rhs,
                dependencies=deps,
                operation_kind=op,
                unit_proof=proof.to_canonical_string(),
                admissibility_status="admitted",
                source_span=_span(lhs),
            )
        )

    # The question target lives INSIDE the graph (ADR-0135): a BoundUnknown bound to
    # the asked symbol at the terminal state. The form is "total" for an aggregate
    # query ("how many do X and Y have"), else "count". ``query`` is retained as a
    # consistent-by-construction convenience for the existing relational_metric
    # projection + realize path; a follow-up collapses it onto graph.unknowns.
    unknown = BoundUnknown(
        symbol_id=ask_entity,
        question_span=_span(ask_entity),
        state_index="terminal",
        question_form="total" if sum_eq is not None else "count",
        expected_unit=ask_unit,
    )

    try:
        graph = SemanticSymbolicBindingGraph(
            symbols=tuple(symbols),
            facts=bound_facts,
            equations=tuple(equations),
            unknowns=(unknown,),
        )
    except Exception as exc:  # noqa: BLE001 — surface construction refusal
        return Refusal("invalid_binding_graph", repr(exc))

    return QuantComprehension(
        binding_graph=graph,
        query=QuantQuery(entity=ask_entity, unit=ask_unit, span=_span(ask_entity)),
    )


def to_relational_metric(
    comp: QuantComprehension,
) -> tuple[list[dict[str, Any]], dict[str, Any]] | None:
    """Project the comprehended binding_graph into ``(relations, query)`` for
    ``evals.relational_metric.oracle.oracle_answer``.

    Reads the binding-graph itself (facts + admitted equations) — the equation's
    own ``rhs_canonical`` is parsed back (a controlled round-trip of the format this
    module emits) and operands are classified as symbol (a known entity) vs literal.
    Facts are emitted before equations and equations in dependency order, so the
    oracle's forward substitution never hits an unresolved reference.
    """
    graph = comp.binding_graph
    symbol_ids = {s.symbol_id for s in graph.symbols}
    relations: list[dict[str, Any]] = [
        {"kind": "fact", "entity": f.symbol_id, "value": int(f.value)} for f in graph.facts
    ]
    for eq in graph.equations:
        rhs = eq.rhs_canonical
        if " + " in rhs:
            operands = rhs.split(" + ")
            if all(op in symbol_ids for op in operands):
                relations.append({"kind": "sum_of", "entity": eq.lhs_symbol_id, "parts": list(operands)})
                continue
            ref, literal = operands[0], operands[1]
            relations.append(
                {"kind": "more_than", "entity": eq.lhs_symbol_id, "ref": ref, "delta": int(literal)}
            )
        elif " - " in rhs:
            ref, literal = rhs.split(" - ")
            relations.append(
                {"kind": "fewer_than", "entity": eq.lhs_symbol_id, "ref": ref, "delta": int(literal)}
            )
        else:
            return None  # unrecognized equation shape -> refuse
    if not relations:
        return None
    return relations, {"entity": comp.query.entity, "unit": comp.query.unit}