feat(reasoning): Regulatory Reasoning Engine MVP (scope/obligations/implementation/interpretation)

Deterministic reasoning layer ON TOP of the Legal Knowledge Graph (obligation
registry) and the Compliance Execution Graph (control mapping/evidence). Answers
which regulations apply to a concrete product, which obligations follow, whether
the customer's implementation covers them, and whether a customer interpretation
is too narrow/broad/plausible.

- ProductProfile with tri-state facts (Optional[bool]=None => uncertain, never
  false security); safe predicate evaluator (no eval).
- 6 regulation triggers (CRA/MaschinenVO/RED/EMV/DataAct/NIS2) with missing-fact
  prompts; 24 obligation scope rules.
- CRA obligation_ids RE-USED verbatim from the registry (93 ids) — never re-minted
  (control_uuid trap); Machine/Data-Act flagged proposed=True.
- required_evidence constrained to the framework-agnostic shared evidence catalog;
  capabilities echo the planned Obligation->Capability layer.
- Overlap groups (CRA<->MaschinenVO cyber-safety) + evidence-for-multiple (USP).
- 4 endpoints POST /reasoning/{scope,obligations,implementation-assessment,
  interpretation-assessment}; thin handlers, registered in api/__init__.py.
- 22 tests (5 machine-builder scenarios + 10 acceptance questions). No DB
  migration, no RAG, no new controls.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>

backend-compliance/compliance/reasoning/predicates.py

@@ -0,0 +1,100 @@
+"""Safe, tri-state condition evaluator for applicability rules.
+
+Conditions are plain data (no `eval`): a *leaf* is a 3-tuple
+``(field, op, value)``; a *composite* is ``{"all": [...]}`` or
+``{"any": [...]}``. Evaluation is tri-state — ``True`` / ``False`` /
+``None`` (unknown) — so a missing product fact yields *uncertain*, never a
+false negative.
+"""
+
+from __future__ import annotations
+
+from enum import Enum
+from typing import Any, Dict, List, Optional, Tuple, Union
+
+Leaf = Tuple[str, str, Any]
+Condition = Union[Leaf, Dict[str, Any]]
+
+
+def _attr(profile: Any, field: str) -> Any:
+    value = getattr(profile, field, None)
+    if isinstance(value, Enum):
+        return value.value
+    return value
+
+
+def _eval_leaf(leaf: Leaf, profile: Any) -> Optional[bool]:
+    field, op, expected = leaf
+    actual = _attr(profile, field)
+
+    if op == "not_none":
+        return actual is not None
+    if op == "is_none":
+        return actual is None
+
+    if op == "contains_any":
+        # list-valued field (e.g. product_type); empty list = known-empty.
+        items = actual or []
+        hay = " ".join(str(x).lower() for x in items)
+        return any(str(k).lower() in hay for k in expected)
+
+    if actual is None:
+        return None  # unknown fact -> unknown result
+
+    if op == "eq":
+        return bool(actual == expected)
+    if op == "ne":
+        return bool(actual != expected)
+    if op == "truthy":
+        return bool(actual)
+    if op == "falsy":
+        return not bool(actual)
+    if op == "in":
+        return bool(actual in expected)
+    if op == "not_in":
+        return bool(actual not in expected)
+    if op == "date_after":
+        return bool(actual > expected)
+    raise ValueError("unknown predicate op: %r" % (op,))
+
+
+def evaluate(condition: Optional[Condition], profile: Any) -> Optional[bool]:
+    """Return True/False/None(unknown) for a condition tree."""
+    if condition is None:
+        return True
+    if isinstance(condition, tuple):
+        return _eval_leaf(condition, profile)
+
+    if "all" in condition:
+        results = [evaluate(c, profile) for c in condition["all"]]
+        if any(r is False for r in results):
+            return False
+        if any(r is None for r in results):
+            return None
+        return True
+    if "any" in condition:
+        results = [evaluate(c, profile) for c in condition["any"]]
+        if any(r is True for r in results):
+            return True
+        if any(r is None for r in results):
+            return None
+        return False
+    raise ValueError("malformed condition: %r" % (condition,))
+
+
+def true_leaves(condition: Optional[Condition], profile: Any) -> List[Leaf]:
+    """Collect the leaf conditions that evaluated True (for trigger_facts)."""
+    if condition is None:
+        return []
+    if isinstance(condition, tuple):
+        return [condition] if _eval_leaf(condition, profile) is True else []
+    members = condition.get("all") or condition.get("any") or []
+    out: List[Leaf] = []
+    for c in members:
+        out.extend(true_leaves(c, profile))
+    return out
+
+
+def unknown_fields(fields: List[str], profile: Any) -> List[str]:
+    """Subset of `fields` whose value on the profile is None (unknown)."""
+    return [f for f in fields if _attr(profile, f) is None]