feat(controls): shared get_controls_for_use_case retrieval API

Read-only layer (service + thin route + tests) that returns the controls
mapped to a use-case/topic, ranked by a deterministic precision proxy
(is_primary + mapping confidence + registry keyword relevance) over the
existing mc_use_case_mappings seed. No schema change.

Shared handoff point: the document specialist agents AND the CRA
finding-mapper draw from this one controls index instead of separate
retrievals.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
This commit is contained in:
Benjamin Admin
2026-06-13 21:37:18 +02:00
parent 43ae33975d
commit a4b405077f
4 changed files with 268 additions and 0 deletions
@@ -58,6 +58,7 @@ _ROUTER_MODULES = [
"canonical_control_routes",
"control_generator_routes",
"crosswalk_routes",
"use_case_controls_routes",
"process_task_routes",
"evidence_check_routes",
"vvt_library_routes",
@@ -0,0 +1,49 @@
"""Use-Case → Controls API — the shared retrieval layer.
GET /v1/controls/use-cases — registry + mapped counts
GET /v1/controls/use-cases/{use_case}/controls — ranked controls of a topic
Consumed by the document specialist agents and the CRA finding-mapper so both
draw from ONE controls index instead of separate retrievals. Read-only.
"""
from __future__ import annotations
from typing import Any
from fastapi import APIRouter, Depends, Query
from sqlalchemy.orm import Session
from classroom_engine.database import get_db
from compliance.api._http_errors import translate_domain_errors
from compliance.services.use_case_controls import UseCaseControlsService
router = APIRouter(prefix="/v1/controls", tags=["use-case-controls"])
def get_use_case_controls_service(
db: Session = Depends(get_db),
) -> UseCaseControlsService:
return UseCaseControlsService(db)
@router.get("/use-cases")
async def list_use_cases(
svc: UseCaseControlsService = Depends(get_use_case_controls_service),
) -> list[dict[str, Any]]:
"""All enabled use-cases (topics) with their live mapped-control counts."""
with translate_domain_errors():
return svc.list_use_cases()
@router.get("/use-cases/{use_case}/controls")
async def controls_for_use_case(
use_case: str,
primary_only: bool = Query(False, description="Nur Primaerzweck-Mappings"),
limit: int = Query(50, ge=1, le=200),
offset: int = Query(0, ge=0),
svc: UseCaseControlsService = Depends(get_use_case_controls_service),
) -> dict[str, Any]:
"""Controls mapped to a topic, ranked by the deterministic precision proxy."""
with translate_domain_errors():
return svc.controls_for_use_case(use_case, primary_only, limit, offset)
@@ -0,0 +1,161 @@
# mypy: disable-error-code="no-any-return,arg-type"
"""Use-Case → Controls retrieval — the SHARED layer the document agents AND the
CRA finding-mapper query to pull the controls that belong to a topic.
Read-only over the existing ``mc_use_case_mappings`` seed (no schema change).
The seed is recall-oriented ("this MC comes from a law about the topic"); the
ranking here is a deterministic *precision proxy* — is_primary + mapping
confidence + cluster size, plus a keyword-relevance score derived from the
use-case registry. The LLM precision pass (Phase B) refines this later; the
ranking field stays the same so consumers do not change.
"""
from __future__ import annotations
from typing import Any, Optional
from sqlalchemy import text
from sqlalchemy.orm import Session
from compliance.data.use_case_registry import REGISTRY, is_valid_use_case
from compliance.domain import NotFoundError
def relevance_score(
title: Optional[str],
objective: Optional[str],
keyword_tokens: tuple[str, ...],
is_primary: Optional[bool],
confidence: Optional[float],
) -> float:
"""Deterministic precision proxy in [0, 1]. Pure → unit-testable.
Combines the recall signals already on the mapping (primary flag, mapping
confidence) with a content signal: how many of the use-case's registry
keyword tokens appear in the control's own representative text. The content
term is what separates "actually about this topic" from "merely from a
related law" — the core of the precision problem.
"""
haystack = f"{title or ''} {objective or ''}".lower()
hits = sum(1 for kw in keyword_tokens if kw and kw in haystack)
kw_score = min(hits / 3.0, 1.0) if keyword_tokens else 0.0
score = (0.5 if is_primary else 0.0) + 0.3 * float(confidence or 0.0) + 0.2 * kw_score
return round(min(score, 1.0), 3)
# Representative member (most severe, then lowest control_id) carries the
# human-readable title/objective — master_controls.canonical_name is only the
# merge token, so we surface a real member control per master.
_LIST_SQL = text("""
SELECT mc.id, mc.master_control_id, mc.canonical_name, mc.total_controls,
m.is_primary, m.confidence,
(SELECT r.source_regulation FROM mc_regulations r
WHERE r.master_control_uuid = mc.id AND r.is_primary LIMIT 1)
AS primary_regulation,
rep.title, rep.objective, rep.severity, rep.category
FROM master_controls mc
JOIN mc_use_case_mappings m
ON m.master_control_uuid = mc.id AND m.use_case = :uc
LEFT JOIN LATERAL (
SELECT cc.title, cc.objective, cc.severity, cc.category
FROM master_control_members mcm
JOIN canonical_controls cc ON cc.id = mcm.control_uuid
WHERE mcm.master_control_uuid = mc.id
ORDER BY CASE cc.severity WHEN 'critical' THEN 0 WHEN 'high' THEN 1
WHEN 'medium' THEN 2 ELSE 3 END, cc.control_id
LIMIT 1
) rep ON true
WHERE (:primary_only = false OR m.is_primary)
ORDER BY m.is_primary DESC, m.confidence DESC NULLS LAST,
mc.total_controls DESC
LIMIT :lim OFFSET :off
""")
class UseCaseControlsService:
"""Topic → controls retrieval over the seeded use-case mappings."""
def __init__(self, db: Session) -> None:
self.db = db
def list_use_cases(self) -> list[dict[str, Any]]:
"""Registry use-cases with their live mapped-control counts."""
counts = {
row[0]: int(row[1])
for row in self.db.execute(text(
"SELECT use_case, count(*) FROM mc_use_case_mappings "
"GROUP BY use_case"
)).fetchall()
}
out = [
{
"key": uc.key,
"label": uc.label,
"group": uc.group,
"regulations": list(uc.regulations),
"verification_methods": list(uc.verification_methods),
"mapped_controls": counts.get(uc.key, 0),
}
for uc in REGISTRY.values() if uc.enabled
]
out.sort(key=lambda x: x["mapped_controls"], reverse=True)
return out
def controls_for_use_case(
self,
use_case: str,
primary_only: bool = False,
limit: int = 50,
offset: int = 0,
) -> dict[str, Any]:
"""Ranked controls mapped to ``use_case`` (deduplicated master grain)."""
if not is_valid_use_case(use_case):
raise NotFoundError(f"Unknown use_case '{use_case}'")
uc = REGISTRY[use_case]
lim = min(max(int(limit), 1), 200)
off = max(int(offset), 0)
count_sql = (
"SELECT count(*) FROM mc_use_case_mappings WHERE use_case = :uc"
+ (" AND is_primary" if primary_only else "")
)
total = self.db.execute(text(count_sql), {"uc": use_case}).scalar() or 0
rows = self.db.execute(_LIST_SQL, {
"uc": use_case,
"primary_only": bool(primary_only),
"lim": lim,
"off": off,
}).fetchall()
controls = [
{
"id": str(r.id),
"master_control_id": r.master_control_id,
"title": r.title or r.canonical_name,
"objective": r.objective,
"severity": r.severity,
"category": r.category,
"member_count": r.total_controls,
"is_primary": bool(r.is_primary),
"confidence": (
float(r.confidence) if r.confidence is not None else None
),
"primary_regulation": r.primary_regulation,
"relevance": relevance_score(
r.title, r.objective, uc.keyword_tokens,
r.is_primary, r.confidence,
),
}
for r in rows
]
return {
"use_case": uc.key,
"label": uc.label,
"group": uc.group,
"total": int(total),
"limit": lim,
"offset": off,
"primary_only": bool(primary_only),
"controls": controls,
}
@@ -0,0 +1,57 @@
"""Tests for the shared use-case → controls retrieval layer.
The SQL paths are verified e2e against the seeded DB; here we pin the pure,
deterministic ranking logic and the validation guard.
"""
import pytest
from compliance.domain import NotFoundError
from compliance.services.use_case_controls import (
UseCaseControlsService,
relevance_score,
)
_NET_KW = ("firewall", "tls", "port", "segmentation", "network", "header")
def test_relevance_primary_only_baseline():
# primary flag alone (no confidence, no keyword hit) → 0.5
assert relevance_score("x", "y", _NET_KW, True, None) == 0.5
def test_relevance_non_primary_baseline_is_zero():
assert relevance_score("x", "y", _NET_KW, False, None) == 0.0
def test_relevance_confidence_contributes():
# non-primary, no keyword: 0.3 * confidence
assert relevance_score("x", "y", _NET_KW, False, 1.0) == 0.3
assert relevance_score("x", "y", _NET_KW, False, 0.5) == 0.15
def test_relevance_keyword_hits_are_capped_at_three():
# three+ distinct keyword hits saturate the content term at +0.2
title = "Firewall and TLS on every port and network segmentation header"
assert relevance_score(title, "", _NET_KW, False, None) == 0.2
def test_relevance_keyword_match_is_case_insensitive_over_title_and_objective():
score = relevance_score("FIREWALL", "tls config", _NET_KW, False, None)
# two hits → 2/3 * 0.2 ≈ 0.133
assert score == pytest.approx(0.133, abs=0.001)
def test_relevance_is_clamped_to_one():
title = "firewall tls port" # 3 hits → +0.2
assert relevance_score(title, "", _NET_KW, True, 1.0) == 1.0
def test_relevance_no_keyword_tokens_yields_zero_content_term():
assert relevance_score("anything", "here", (), True, 1.0) == 0.8
def test_controls_for_unknown_use_case_raises_not_found():
svc = UseCaseControlsService(db=None) # guard runs before any DB access
with pytest.raises(NotFoundError):
svc.controls_for_use_case("does_not_exist")