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Benjamin Admin e2c74fd243 feat(ucca): Blue-Green „authoritative slice promotion" — KB-2026.1 Scope-Routing
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Additiv (KEIN CE-Ersatz): faellt eine Query in den KB-2026.1-Scope (DP/CRA/MaschVO/
NIS2/DataAct/DORA/AIAct + EDPB/DSK-Guidance), wird die hochwertige Slice-Collection
`kb_2026_1_build` abgefragt; sonst bleibt der breite Default `bp_compliance_ce`.
Damit werden die Guidance-Intent- + Multi-Reg-Fixes (PR #42/#43) fuer den Slice LIVE,
Broad-Corpus (OWASP/NIST/ENISA/IFRS/ISO) unangetastet -> 0 Regressionen by construction.

- resolveCollection(query, requested): explizit angefragte Collection unveraendert;
  Default-Request -> Slice bei inKBScope, sonst CE. Env RAG_KB_SCOPE_ROUTING=false = Rollback
  ohne Redeploy; RAG_KB_SLICE_COLLECTION ueberschreibt den Slice-Namen.
- inKBScope: detectRegulations (in-Slice-Regelwerke) + DP-Guidance-Marker (edpb/dsk/wp/gl) +
  DP/Compliance-Topics. Bewusst NICHT die generischen Verben aus guidanceIntentSignals
  (sagt/laut) und NICHT enisa/bsi/nist/owasp (die liegen in CE) -> konservativ, in-scope->Slice.

Validierung: Unit (Scoping + resolveCollection); dev-e2e (RUN_E2E, geroutetes Search() gegen
dev): WP248/MaschVO/CRA+MaschVO -> Slice (Treffer da, fehlen in dev-ce); NIST -> CE (NIST-Treffer).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-30 11:49:34 +02:00
Benjamin_Boenisch 8ed99c255d Merge pull request 'fix(api): F821-Regression (Extract-Service-Halb-Refactor) — 7 Route-Dateien' (#44) from fix/api-f821-extract-service-regression into main
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2026-06-30 09:06:08 +00:00
Benjamin Admin 3389fa3e7a fix(api): F821-Regression in 6 weiteren Route-Dateien beheben
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Gleiche Wurzel wie evidence_routes (Extract-Service-Refactor a638d0e5 ff.):
Signaturen/Imports halb umgestellt → undefined names → NameError beim Aufruf.

- routes.py: db-Param in get_control/update_control/review_control + EvidenceDB-Import
- dsfa_routes.py: db-Param in create_dsfa + HTTPException/text-Import
- dashboard_routes.py: timezone-Import
- canonical_control_routes.py: logger-Definition
- ai_routes.py: timezone in den lokalen datetime-Imports
- vvt_routes.py: HTTPException-Import

Verifiziert: ruff F821 0 über das gesamte compliance/api/, alle 6 py_compile,
294 Tests grün auf den betroffenen Modulen (die 2 dsfa-invalid-status/risk-Failures
sind vorbestehend = 400-vs-422, unabhängig von diesem Fix).

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-30 10:51:00 +02:00
Benjamin Admin 79abf23ea8 fix(api): evidence_routes F821-Regression beheben (Extract-Service-Halb-Refactor)
a638d0e5 ("extract EvidenceService") stellte Signaturen auf service=Depends um,
ließ aber Bodies + Imports auf dem alten Stand → 43 F821 (NameError zur Laufzeit).

- gelöschte stdlib-Imports restauriert (os/json/hashlib/uuid/datetime/timedelta)
- db: Session = Depends(get_db) an den betroffenen Endpoints restauriert
- translate_domain_errors + _update_risks_impl (=evidence_service._update_risks) importiert
- unerreichbaren toten Block (alte get_ci_evidence_status-Impl nach dem return) entfernt
- dsms_cid=None no-op in create/review/reject (DSMS-Commit-Copy-Paste)

Verifiziert: ruff F821 0, py_compile, test_evidence_routes.py 35 passed.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-30 10:19:28 +02:00
Benjamin Admin d5925e57af feat(ai-sdk): pin accepted proposer decisions into the GT gate (P3)
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When a human accepts a proposer proposal, an AcceptedPin records a machine-scoped
invariant — a pattern MUST fire (coverage/vocab→tag) or must NOT fire
(dedup/framing) — that a test re-checks on every run. This makes the library's
growth COMPOUND into the gate instead of eroding it: a change that re-introduces
a dropped duplicate, un-gates a foreign pattern, or removes a coverage hazard
breaks a pin and fails CI. One boolean covers all four proposal types.

Seeded testdata/accepted_pins_warewashing.json with the accepted P1 supersessions
(HP016/HP018/HP013 must NOT fire; their clean equivalents HP2201/HP144 must fire).
TestWarewashing_AcceptedPins re-checks 5/5 against the live engine output;
GenerateDedupPin turns an accepted dedup verdict into its pin.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-30 09:42:31 +02:00
Benjamin Admin 1877829b1d Merge remote-tracking branch 'gitea/main' into reconcile-dev
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2026-06-30 09:04:58 +02:00
Benjamin_Boenisch 866889b453 Merge pull request 'feat(ucca): Multi-Regulation-Retrieval (Cross-Regulation-Fragen)' (#43) from fix/multi-regulation-retrieval into main
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2026-06-30 06:46:21 +00:00
pilotadmin f0da86ca19 Merge pull request 'feat(onboarding): advisor responsiveness — moving headline + auto-recompute' (#54) from feat/advisor-ux-responsiveness into main 2026-06-28 19:31:20 +02:00
Benjamin Admin 867f8c3854 feat(onboarding): make the advisor visibly responsive — headline leads with the moving number + auto-recompute
Testing surfaced that toggling certifications appeared to "do nothing": the headline led with the TOTAL
requirement count (constant per target, e.g. 17 for CRA), and the page only recomputed on an explicit
button click. Both fixed:
  - engine.py headline now leads with the number that actually moves: "11 von 17 Anforderungen offen ·
    6 wahrscheinlich (Zertifikate) · 5 zu klären" (was "17 Anforderungen erkannt · …"). Keeps the
    "automatisch erkannt (Intake)" substring.
  - frontend auto-recomputes on certifications / target / scanner-signal change (no button needed).

Now ISO27001 alone -> "13 von 17 offen · 4 wahrscheinlich"; + ISO9001+TISAX+IEC62443 -> "11 von 17 offen ·
6 wahrscheinlich". (Domain truth stays visible: CRA's product-cyber gaps barely move with management-system
certs.) 28 onboarding+transition tests pass, check-loc 0.
2026-06-28 19:31:15 +02:00
pilotadmin 26a8518107 Merge pull request 'feat(onboarding): surface curated expert text + human labels' (#53) from feat/advisor-human-text into main 2026-06-28 18:47:07 +02:00
Benjamin Admin 807a7002b2 feat(onboarding): surface curated expert text + human capability labels (advisor was showing snake_case)
The advisor was structurally correct but unusable: every question showed a snake_case capability id plus a
single generic fallback reason ("Keine Anhaltspunkte im Unternehmensprofil — klären"). The expert text
already EXISTED in the transition patterns (why_asked / reviewable_claim) — the pipeline just dropped it.

  - transition_reasoning: TargetRequirement gains `rationale`; assess_transition uses it as the request
    reason when present, else the generic fallback (additive, backward-compatible for all consumers).
  - onboarding_service._target carries the pattern's why_asked (delta) and reviewable_claim (likely_covered)
    into the requirement rationale -> the question's `why`.
  - knowledge/onboarding/capability_labels.yaml: curated DE labels (id -> human), reusable across targets;
    labels_for() + response.capability_labels expose them; the frontend renders label || prettified id.

Now ISO27001->TISAX reads "Auftragsverarbeitung (Art. 28 DSGVO) — If a TISAX data label is in scope, you
must show Art. 28 GDPR processing-on-behalf controls; ISO 27001 does not establish these." instead of
"data_protection_processing_on_behalf — klären". why_asked text is still EN (existing knowledge; translation
is curation). 34 onboarding+transition tests pass, mypy --strict clean (13 modules), check-loc 0.
2026-06-28 18:46:56 +02:00
pilotadmin 5beb5a319a Merge pull request 'feat(admin): ETO / Onboarding-Advisor test page' (#52) from feat/onboarding-advisor-frontend into main 2026-06-28 17:12:44 +02:00
Benjamin Admin 239702fdca feat(admin): ETO / Onboarding-Advisor test page (thin operator surface over the advisor endpoint)
A focused client page at /sdk/onboarding-advisor that exercises POST /api/compliance/onboarding/
advisor-start through the existing compliance proxy: pick certifications + target + scanner findings
(observation / partial / requirement) and render the result — headline, silent-intake summary,
auto-detected (green), indications (amber), next-best questions with WHY, inferred (Welt-1) vs rejected
assumptions, capability delta, evidence requests, completeness. NOT the regulation gap engine
(/sdk/gap-analysis is a different flow). No new backend; calls only the existing endpoint. 195 lines.
2026-06-28 17:12:40 +02:00
pilotadmin d1a5fc7205 Merge pull request 'feat(onboarding): Observation Log — append-only JSONL calibration store (59b/c)' (#51) from feat/observation-log into main 2026-06-28 16:29:58 +02:00
Benjamin Admin 7df15010ff feat(onboarding): Observation Log — append-only JSONL calibration store (Task 59b/c v1)
Per the user's decision (2026-06-28): observations are CALIBRATION data for the knowledge base, NOT
business data and NOT product-DB data. So they live with the other versioned knowledge artifacts as an
append-only JSONL log under knowledge/observations/ — NO migration, NO DB. (A real persistence layer is
only warranted once thousands of onboardings exist; not before.)

  - ObservationRecord = Observation + log metadata (observation_id, timestamp [caller-stamped, no hidden
    clock], customer_archetype [anonymised — NEVER a real name], evidence, provenance, knowledge_version).
  - append_observation() writes one JSON line; append-only, lines are never rewritten. A later review is a
    NEW line with the same observation_id; load_observations(reconcile=True) keeps the latest per id.
  - load_observations() reads a single .jsonl or a directory of monthly .jsonl files.
  - aggregate_by_hypothesis() (59c) -> per-hypothesis distribution + confidence, COMPUTED from the log
    (computed-not-stored); the review gate (reviewed-only) is enforced in empirical_distribution/confidence.
  - review_queue() -> the unreviewed worklist. Observation -> Review -> Accepted -> recompute, never
    Observation -> confidence++. Nothing is ever written back to a hypothesis.

You can `rm` the log and recompute, `git diff` it over months, or rebuild confidence under a new policy —
fully consistent with computed-not-stored and the product/knowledge data separation.

Non-runtime (module + tests only, no endpoint) -> origin/main, NO dev deploy. 5 new tests (append-only,
review supersession, review-gate statistics, queue, monthly-file load); 27 onboarding tests pass, mypy
--strict clean (9 modules), check-loc 0. 59d (surface computed confidence at runtime) stays a later step.
2026-06-28 16:29:54 +02:00
25 changed files with 838 additions and 94 deletions
@@ -0,0 +1,200 @@
'use client'
// ETO / Onboarding-Advisor — thin operator surface over POST /api/compliance/onboarding/advisor-start.
// Certifications + target + scanner findings -> Silent Pass -> Advisor. NOT the regulation gap engine
// (/sdk/gap-analysis is a different flow: product -> applicable regulations). This tests the cert->delta
// case: "TISAX/ISO27001 -> CRA, what is auto-detected, what stays an open question?". No new backend.
import React, { useEffect, useState } from 'react'
const CERTS = ['ISO27001', 'TISAX', 'ISO9001', 'IEC62443', 'ISO13485', 'ISO14001', 'ASPICE', 'IATF16949']
// label -> {signal_id, source_type} — demonstrates all three signal KINDS (observation / partial / requirement)
const FINDINGS: Array<{ label: string; signal_id: string; source_type: string; kind: string }> = [
{ label: 'SBOM im Repo (CycloneDX/SPDX)', signal_id: 'cyclonedx_found', source_type: 'repository', kind: 'observation' },
{ label: 'security.txt / CVD-Policy veröffentlicht', signal_id: 'security_txt', source_type: 'website', kind: 'observation' },
{ label: 'Signierte Releases', signal_id: 'signed_releases', source_type: 'repository', kind: 'observation' },
{ label: 'Produkt-Risikobewertung (Dokument)', signal_id: 'risk_assessment_pdf', source_type: 'document', kind: 'observation' },
{ label: 'CI-Pipeline vorhanden (nur Indikation)', signal_id: 'github_actions_ci', source_type: 'repository', kind: 'partial' },
{ label: 'Cloud-/vernetztes Produkt', signal_id: 'cloud_hosted', source_type: 'product', kind: 'observation' },
{ label: 'Ausschreibung FORDERT SBOM (Requirement)', signal_id: 'requires_sbom', source_type: 'tender', kind: 'requirement' },
{ label: 'OEM FORDERT PSIRT (Requirement)', signal_id: 'supplier_requires_psirt', source_type: 'oem', kind: 'requirement' },
]
interface Question { capability_id: string; question_intent: string; why: string; information_value: number; priority: string }
interface Inferred { certification: string; capabilities: string[]; statement: string }
interface Rejected { certification?: string; statement: string; reason: string }
interface Measure { capability_id: string; leverage: number; closes: string[] }
interface AdvisorResponse {
silent_intake_summary: string; headline: string; auto_detected: string[]; indications: string[]
inferred_assumptions: Inferred[]; rejected_assumptions: Rejected[]; top_5_questions: Question[]
capability_delta: string[]; top_measures: Measure[]; evidence_requests: string[]
unsupported_domains: string[]; completeness_summary: string; capability_labels: Record<string, string>
}
const PROXY = '/api/sdk/v1/compliance/onboarding'
function Chips({ items, tone }: { items: string[]; tone: string }) {
if (!items.length) return <span className="text-gray-400 text-sm"></span>
return (
<div className="flex flex-wrap gap-2">
{items.map(c => <span key={c} className={`px-2.5 py-1 rounded-full text-xs font-medium ${tone}`}>{c}</span>)}
</div>
)
}
function Section({ title, hint, children }: { title: string; hint?: string; children: React.ReactNode }) {
return (
<div className="bg-white rounded-xl border border-gray-200 p-5">
<h3 className="font-semibold text-gray-900">{title}</h3>
{hint && <p className="text-xs text-gray-500 mt-0.5 mb-2">{hint}</p>}
<div className="mt-2">{children}</div>
</div>
)
}
export default function OnboardingAdvisorPage() {
const [targets, setTargets] = useState<string[]>([])
const [company, setCompany] = useState('Beispiel Maschinenbau')
const [industry, setIndustry] = useState('machine_builder')
const [certs, setCerts] = useState<string[]>(['ISO27001', 'ISO9001'])
const [target, setTarget] = useState('CRA')
const [findings, setFindings] = useState<string[]>(['cyclonedx_found', 'github_actions_ci', 'requires_sbom'])
const [knownEvidence, setKnownEvidence] = useState('CE-Prozess')
const [result, setResult] = useState<AdvisorResponse | null>(null)
const [loading, setLoading] = useState(false)
const [error, setError] = useState('')
useEffect(() => {
fetch(`${PROXY}/targets`).then(r => r.json()).then(d => {
if (Array.isArray(d.targets)) { setTargets(d.targets); if (!d.targets.includes('CRA') && d.targets[0]) setTarget(d.targets[0]) }
}).catch(() => {})
}, [])
const toggle = (list: string[], set: (v: string[]) => void, v: string) =>
set(list.includes(v) ? list.filter(x => x !== v) : [...list, v])
const lbl = (id: string) => result?.capability_labels?.[id] || id.replace(/_/g, ' ')
const run = async () => {
setLoading(true); setError(''); setResult(null)
try {
const scanner_findings = FINDINGS.filter(f => findings.includes(f.signal_id))
.map(f => ({ signal_id: f.signal_id, source_type: f.source_type }))
const res = await fetch(`${PROXY}/advisor-start`, {
method: 'POST', headers: { 'Content-Type': 'application/json' },
body: JSON.stringify({
company, industry, products: [], markets: ['EU'], certifications: certs,
known_evidence: knownEvidence ? knownEvidence.split(',').map(s => s.trim()).filter(Boolean) : [],
target, scanner_findings,
}),
})
if (!res.ok) throw new Error(await res.text())
setResult(await res.json())
} catch (e) {
setError(e instanceof Error ? e.message : 'Advisor fehlgeschlagen')
} finally { setLoading(false) }
}
// auto-recompute when certifications / target / scanner signals change (no button click needed)
useEffect(() => { if (certs.length) run() }, [certs, target, findings]) // eslint-disable-line react-hooks/exhaustive-deps
return (
<div className="min-h-screen bg-gray-50 py-8">
<div className="max-w-5xl mx-auto px-4">
<h1 className="text-3xl font-bold text-gray-900">ETO / Onboarding-Advisor</h1>
<p className="text-gray-600 mt-2 mb-6">
Zertifikate + Ziel + Scanner-Signale Silent Pass Capability-Delta + nächste beste Fragen.
Welt-1: ein Zertifikat <em>legt nahe</em>, beweist nichts (Verifikation erforderlich).
</p>
<div className="grid md:grid-cols-2 gap-4 mb-6">
<Section title="Unternehmen & Ziel">
<label className="block text-sm text-gray-600">Unternehmen
<input value={company} onChange={e => setCompany(e.target.value)} className="mt-1 w-full border rounded-lg px-3 py-2" /></label>
<label className="block text-sm text-gray-600 mt-3">Branche
<input value={industry} onChange={e => setIndustry(e.target.value)} className="mt-1 w-full border rounded-lg px-3 py-2" /></label>
<label className="block text-sm text-gray-600 mt-3">Ziel
<select value={target} onChange={e => setTarget(e.target.value)} className="mt-1 w-full border rounded-lg px-3 py-2">
{(targets.length ? targets : ['CRA']).map(t => <option key={t} value={t}>{t}</option>)}
</select></label>
<label className="block text-sm text-gray-600 mt-3">Vorhandene Nachweise (kommagetrennt)
<input value={knownEvidence} onChange={e => setKnownEvidence(e.target.value)} className="mt-1 w-full border rounded-lg px-3 py-2" /></label>
</Section>
<Section title="Zertifizierungen">
<div className="flex flex-wrap gap-2">
{CERTS.map(c => (
<button key={c} onClick={() => toggle(certs, setCerts, c)}
className={`px-3 py-1.5 rounded-lg text-sm border ${certs.includes(c) ? 'bg-blue-600 text-white border-blue-600' : 'bg-white text-gray-700 border-gray-300'}`}>{c}</button>
))}
</div>
</Section>
</div>
<Section title="Scanner-Signale (Silent Pass)" hint="observation = gesehen · partial = Indikation · requirement = gefordert (≠ vorhanden)">
<div className="grid sm:grid-cols-2 gap-2">
{FINDINGS.map(f => (
<label key={f.signal_id} className="flex items-center gap-2 text-sm text-gray-700">
<input type="checkbox" checked={findings.includes(f.signal_id)} onChange={() => toggle(findings, setFindings, f.signal_id)} />
<span>{f.label}</span>
<span className={`ml-auto text-[10px] px-1.5 py-0.5 rounded ${f.kind === 'requirement' ? 'bg-purple-100 text-purple-700' : f.kind === 'partial' ? 'bg-amber-100 text-amber-700' : 'bg-emerald-100 text-emerald-700'}`}>{f.kind}</span>
</label>
))}
</div>
</Section>
<button onClick={run} disabled={loading || !certs.length}
className="mt-6 w-full py-3 bg-blue-600 text-white rounded-xl font-medium hover:bg-blue-700 disabled:opacity-50">
{loading ? 'Analysiere…' : 'Advisor starten'}
</button>
{error && <div className="mt-6 bg-red-50 border border-red-200 rounded-lg p-4 text-red-700 text-sm whitespace-pre-wrap">{error}</div>}
{result && (
<div className="mt-8 space-y-4">
<div className="bg-blue-600 text-white rounded-xl p-5">
<div className="text-lg font-semibold">{result.headline}</div>
<div className="text-blue-100 text-sm mt-1">{result.silent_intake_summary}</div>
</div>
<div className="grid md:grid-cols-2 gap-4">
<Section title="Automatisch erkannt" hint="konkrete Artefakte nicht mehr gefragt"><Chips items={result.auto_detected.map(lbl)} tone="bg-emerald-100 text-emerald-800" /></Section>
<Section title="Indikationen" hint="erhöht Annahmestärke trotzdem gefragt"><Chips items={result.indications.map(lbl)} tone="bg-amber-100 text-amber-800" /></Section>
</div>
<Section title="Nächste beste Fragen" hint="max 5, jede erklärt sich selbst">
{result.top_5_questions.length ? (
<ol className="space-y-3">
{result.top_5_questions.map((q, i) => (
<li key={q.capability_id} className="border-l-2 border-blue-300 pl-3">
<div className="font-medium text-gray-900">{i + 1}. {lbl(q.capability_id)}</div>
<div className="text-sm text-gray-600">{q.why}</div>
</li>
))}
</ol>
) : <span className="text-gray-400 text-sm"></span>}
</Section>
<div className="grid md:grid-cols-2 gap-4">
<Section title="Wahrscheinlich abgedeckt (Welt-1)" hint="Zertifikat legt nahe Verifikation erforderlich">
{result.inferred_assumptions.length ? result.inferred_assumptions.map(a => (
<div key={a.certification} className="mb-2"><span className="font-medium">{a.certification}</span>: {a.capabilities.map(lbl).join(', ')}</div>
)) : <span className="text-gray-400 text-sm"></span>}
</Section>
<Section title="Nicht relevant" hint="relevance(evidence, target) = 0">
{result.rejected_assumptions.length ? result.rejected_assumptions.map((a, i) => (
<div key={i} className="mb-1 text-sm text-gray-700">{a.statement}</div>
)) : <span className="text-gray-400 text-sm"></span>}
</Section>
</div>
<div className="grid md:grid-cols-2 gap-4">
<Section title="Offene Lücken (Delta)"><Chips items={result.capability_delta.map(lbl)} tone="bg-gray-100 text-gray-700" /></Section>
<Section title="Geforderte Nachweise"><Chips items={result.evidence_requests} tone="bg-gray-100 text-gray-700" /></Section>
</div>
<Section title="Vollständigkeit" hint={result.unsupported_domains.length ? `nicht abgedeckt: ${result.unsupported_domains.join(', ')}` : undefined}>
<span className="text-sm text-gray-700">{result.completeness_summary || '—'}</span>
</Section>
</div>
)}
</div>
</div>
)
}
@@ -0,0 +1,73 @@
package iace
// P3: pin accepted proposer decisions into the GT gate.
//
// When a human accepts a proposal from the offline proposer (a dedup
// supersession, a foreign-framing gate, a vocab→tag mapping, a coverage hazard),
// they record an AcceptedPin. A pin is a tiny, machine-scoped invariant — "this
// pattern MUST (or must NOT) fire for this machine" — that a test re-checks on
// every run. This is what makes the library's growth COMPOUND into the gate
// instead of silently eroding it: a future change that re-introduces a dropped
// duplicate, un-gates a foreign pattern, or removes a coverage hazard breaks the
// pin and fails CI.
//
// A single boolean covers all four proposal types:
// - dedup supersession accepted → DropPattern MustFire=false
// - foreign-framing gate accepted → foreign pattern MustFire=false
// - vocab→tag / coverage hazard accepted → the enabled pattern MustFire=true
// AcceptedPin is one regression invariant for an accepted proposal.
type AcceptedPin struct {
Pattern string `json:"pattern"`
MustFire bool `json:"must_fire"`
Reason string `json:"reason"`
FromProposal string `json:"from_proposal,omitempty"`
}
// PinSet is the accepted-pin registry for one machine (testdata/accepted_pins_*.json).
type PinSet struct {
Machine string `json:"machine"`
Pins []AcceptedPin `json:"pins"`
}
// PinResult is the verdict for one pin against an engine run.
type PinResult struct {
Pin AcceptedPin
OK bool
Detail string
}
// VerifyPins checks every pin against the set of pattern IDs the engine actually
// fired for the machine. A pin holds iff the pattern's presence equals MustFire.
func VerifyPins(pins []AcceptedPin, firedPatternIDs []string) []PinResult {
fired := make(map[string]bool, len(firedPatternIDs))
for _, id := range firedPatternIDs {
fired[id] = true
}
out := make([]PinResult, 0, len(pins))
for _, p := range pins {
got := fired[p.Pattern]
ok := got == p.MustFire
detail := "ok"
if !ok {
if p.MustFire {
detail = "expected to fire but did NOT — coverage/mapping regressed"
} else {
detail = "expected to be suppressed but FIRED — gate/supersession regressed"
}
}
out = append(out, PinResult{Pin: p, OK: ok, Detail: detail})
}
return out
}
// GenerateDedupPin turns an accepted (verdict=duplicate) dedup candidate into the
// pin that protects the supersession: the dropped pattern must no longer fire.
func GenerateDedupPin(c DedupCandidate) AcceptedPin {
return AcceptedPin{
Pattern: c.DropPattern,
MustFire: false,
Reason: "accepted duplicate of " + c.KeepPattern + " (" + c.Category + ")",
FromProposal: "dedup " + c.DropPattern + " -> " + c.KeepPattern,
}
}
@@ -0,0 +1,63 @@
package iace
import (
"encoding/json"
"os"
"path/filepath"
"testing"
)
func TestVerifyPins(t *testing.T) {
pins := []AcceptedPin{
{Pattern: "HPa", MustFire: true},
{Pattern: "HPb", MustFire: false},
}
res := VerifyPins(pins, []string{"HPa", "HPb"})
if !res[0].OK {
t.Errorf("HPa must_fire=true and it fired -> should be OK")
}
if res[1].OK {
t.Errorf("HPb must_fire=false but it fired -> should be VIOLATED")
}
res2 := VerifyPins(pins, []string{})
if res2[0].OK || !res2[1].OK {
t.Errorf("expected HPa violated + HPb ok, got %+v", res2)
}
}
func TestGenerateDedupPin(t *testing.T) {
pin := GenerateDedupPin(DedupCandidate{KeepPattern: "HP144", DropPattern: "HP013", Category: "electrical_hazard"})
if pin.Pattern != "HP013" || pin.MustFire {
t.Fatalf("want pin {HP013, must_fire=false}, got %+v", pin)
}
}
// TestWarewashing_AcceptedPins re-checks every accepted P1 supersession against the
// live warewashing engine output. A future change that un-suppresses HP013/016/018
// or drops HP2201/HP144 breaks a pin here — the gate compounds, not erodes.
func TestWarewashing_AcceptedPins(t *testing.T) {
raw, err := os.ReadFile(filepath.Join("testdata", "accepted_pins_warewashing.json"))
if err != nil {
t.Fatalf("read pins: %v", err)
}
var ps PinSet
if err := json.Unmarshal(raw, &ps); err != nil {
t.Fatalf("parse pins: %v", err)
}
_, _, kept := warewashingEngineOutput()
firedIDs := make([]string, 0, len(kept))
for _, pm := range kept {
firedIDs = append(firedIDs, pm.PatternID)
}
ok := 0
for _, r := range VerifyPins(ps.Pins, firedIDs) {
if r.OK {
ok++
continue
}
t.Errorf("PIN VIOLATED: %s (must_fire=%v) — %s [%s]", r.Pin.Pattern, r.Pin.MustFire, r.Detail, r.Pin.Reason)
}
t.Logf("accepted pins for %q: %d/%d hold", ps.Machine, ok, len(ps.Pins))
}
@@ -0,0 +1,10 @@
{
"machine": "Gewerbliche Untertisch-Geschirrspuelmaschine (vernetzt)",
"pins": [
{"pattern": "HP016", "must_fire": false, "reason": "generic hot-surface (Formwerkzeuge/Auspuffleitung framing) superseded by HP2201", "from_proposal": "P1 thermal supersession"},
{"pattern": "HP018", "must_fire": false, "reason": "actuator-burn superseded by HP2201", "from_proposal": "P1 thermal supersession"},
{"pattern": "HP013", "must_fire": false, "reason": "stored-energy Batterie/USV framing superseded by HP144", "from_proposal": "P1 stored-energy supersession"},
{"pattern": "HP2201", "must_fire": true, "reason": "warewashing hot-surface (Boiler/Tank/Spuelkammer) must remain — it is the clean equivalent that replaces HP016/HP018", "from_proposal": "P1 thermal supersession"},
{"pattern": "HP144", "must_fire": true, "reason": "residual-voltage (Frequenzumrichter/Zwischenkreis) must remain — clean equivalent that replaces HP013", "from_proposal": "P1 stored-energy supersession"}
]
}
@@ -0,0 +1,52 @@
package ucca
import "strings"
// kbScopeTopics are high-precision data-protection / compliance topic markers that place a query in
// the KB-2026.1 authoritative slice even when it does NOT name a regulation. Conservative by design:
// an unmatched query falls back to the broad CE default (no regression) — the slice is only used when
// the query is confidently in-scope.
var kbScopeTopics = []string{
// DP-Guidance-Marker, die IN der Slice liegen (EDPB/DSK/WP/GL) — bewusst NICHT die generischen
// Verben aus guidanceIntentSignals (sagt/laut/empfiehlt/auslegung) und NICHT enisa/bsi/nist/owasp
// (die liegen im breiten CE-Pool, nicht in der Slice).
"edpb", "dsk", "datenschutzausschuss", "orientierungshilfe",
"wp2", "wp 2", "wp29", "working paper", "gl 0",
"datenschutz", "dsgvo", "gdpr", "dsfa", "folgenabschätzung", "folgenabschaetzung",
"einwilligung", "auftragsverarbeit", "betroffenenrecht", "auskunftsrecht",
"verarbeitungsverzeichnis", "datenschutzbeauftragt", "verzeichnis von verarbeitung",
"cookie", "tracking", "transparenzpflicht", "datenpanne", "meldepflicht",
"technische und organisatorische maßnahmen",
"cyber resilience", "schwachstelle", "vulnerability", "sicherheitsupdate",
"maschinensicherheit", "wesentliche veränderung", "wesentliche veraenderung",
"konformitätsbewertung", "konformitaetsbewertung", "ce-kennzeichnung",
}
// inKBScope reports whether the query belongs to the KB-2026.1 authoritative slice. True when it
// names an in-slice regulation (detectRegulations), asks for guidance (EDPB/DSK/WP/GL), or hits a
// data-protection / compliance topic marker.
func inKBScope(query string) bool {
if len(detectRegulations(query)) > 0 {
return true
}
q := strings.ToLower(query)
for _, t := range kbScopeTopics {
if strings.Contains(q, t) {
return true
}
}
return false
}
// resolveCollection applies the Blue-Green „authoritative slice promotion" routing. An explicitly
// requested collection is honoured unchanged; the DEFAULT (empty) request is routed to the KB-2026.1
// slice when the query is in-scope, else to the broad CE default. Disable via RAG_KB_SCOPE_ROUTING=false.
func (c *LegalRAGClient) resolveCollection(query, requested string) string {
if requested != "" {
return requested
}
if c.kbScopeRoutingEnabled && c.kbSliceCollection != "" && inKBScope(query) {
return c.kbSliceCollection
}
return c.collection
}
@@ -0,0 +1,101 @@
package ucca
import (
"context"
"fmt"
"os"
"strings"
"testing"
)
func TestInKBScope(t *testing.T) {
inScope := []string{
"Welche neun Kriterien nennt WP248 fuer ein hohes Risiko?",
"Wie greifen CRA und Maschinenverordnung bei einer vernetzten Maschine ineinander?",
"Wann ist eine Datenschutz-Folgenabschaetzung erforderlich?",
"Welche Anforderungen stellt die DSGVO an die Einwilligung?",
"Brauche ich einen Datenschutzbeauftragten?",
"Wann muss eine aktiv ausgenutzte Schwachstelle gemeldet werden?",
}
outScope := []string{
"Welche OWASP-Kontrollen gibt es fuer Authentifizierung?",
"Was sagt NIST SP 800-53 zu Access Control?",
"Wie funktioniert ISO 27001 Zertifizierung?",
"Welche IFRS-Standards gelten fuer Leasing?",
}
for _, q := range inScope {
if !inKBScope(q) {
t.Errorf("inKBScope(%q) = false, want true", q)
}
}
for _, q := range outScope {
if inKBScope(q) {
t.Errorf("inKBScope(%q) = true, want false", q)
}
}
}
func TestResolveCollection(t *testing.T) {
c := &LegalRAGClient{collection: "bp_compliance_ce", kbSliceCollection: "kb_2026_1_build", kbScopeRoutingEnabled: true}
if got := c.resolveCollection("Welche Kriterien nennt WP248?", ""); got != "kb_2026_1_build" {
t.Errorf("in-scope default -> %s, want kb_2026_1_build", got)
}
if got := c.resolveCollection("Was sagt NIST SP 800-53?", ""); got != "bp_compliance_ce" {
t.Errorf("out-of-scope default -> %s, want bp_compliance_ce", got)
}
if got := c.resolveCollection("Welche Kriterien nennt WP248?", "explicit_coll"); got != "explicit_coll" {
t.Errorf("explicit request must be honoured -> %s", got)
}
c.kbScopeRoutingEnabled = false
if got := c.resolveCollection("Welche Kriterien nennt WP248?", ""); got != "bp_compliance_ce" {
t.Errorf("disabled routing -> %s, want bp_compliance_ce", got)
}
}
// TestKBScopeRoutingE2E (RUN_E2E=1) verifies the routing against the REAL collections: a default
// Search() of an in-scope query must hit the KB-2026.1 slice (WP248/MaschVO live there but NOT in
// the broad CE pool = clean discriminator); an out-of-scope query stays on CE.
func TestKBScopeRoutingE2E(t *testing.T) {
if os.Getenv("RUN_E2E") != "1" {
t.Skip("set RUN_E2E=1 + QDRANT_URL/OLLAMA_URL/QDRANT_API_KEY")
}
c := NewLegalRAGClient()
cases := []struct {
q string
wantToken string // expected in top-8 when routed to the slice
wantInKB bool
}{
{"Welche neun Kriterien nennt WP248 fuer ein voraussichtlich hohes Risiko?", "WP248", true},
{"Welche grundlegenden Sicherheits- und Gesundheitsschutzanforderungen enthaelt Anhang III der Maschinenverordnung?", "MASCH", true},
{"Wie greifen CRA und Maschinenverordnung bei einer vernetzten Maschine ineinander?", "MASCH", true},
{"Was sagt NIST SP 800-53 zu Access Control?", "", false},
}
for _, tc := range cases {
routed := c.resolveCollection(tc.q, "")
res, err := c.Search(context.Background(), tc.q, nil, 8)
if err != nil {
t.Fatalf("%q: %v", tc.q, err)
}
codes := map[string]bool{}
for _, r := range res {
codes[strings.ToUpper(r.RegulationCode)] = true
}
hit := false
if tc.wantToken != "" {
for cd := range codes {
if strings.Contains(cd, tc.wantToken) {
hit = true
break
}
}
}
col := make([]string, 0, len(codes))
for cd := range codes {
col = append(col, cd)
}
fmt.Printf("inKB=%-5v routed=%-16s wantTok=%-6s found=%-5v | %v\n", tc.wantInKB, routed, tc.wantToken, hit, col)
if tc.wantInKB && tc.wantToken != "" && !hit {
t.Errorf("%q routed to %s but %s not in top-8 (slice not active?)", tc.q, routed, tc.wantToken)
}
}
}
@@ -21,6 +21,12 @@ type LegalRAGClient struct {
textIndexEnsured map[string]bool textIndexEnsured map[string]bool
hybridEnabled bool hybridEnabled bool
graphEnabled bool graphEnabled bool
// Blue-Green „authoritative slice promotion" (additiv, KEIN CE-Ersatz): faellt eine Query
// in den KB-2026.1-Scope (DP/CRA/MaschVO/NIS2/DataAct/DORA/AIAct + EDPB/DSK-Guidance), wird
// die hochwertige Slice-Collection abgefragt; sonst bleibt der breite Default (bp_compliance_ce).
kbSliceCollection string
kbScopeRoutingEnabled bool
} }
// NewLegalRAGClient creates a new Legal RAG client using Ollama bge-m3 embeddings. // NewLegalRAGClient creates a new Legal RAG client using Ollama bge-m3 embeddings.
@@ -45,6 +51,14 @@ func NewLegalRAGClient() *LegalRAGClient {
// zur Begruendung/Vollstaendigkeit genutzt, nicht zur Pool-Expansion (Default). // zur Begruendung/Vollstaendigkeit genutzt, nicht zur Pool-Expansion (Default).
graphEnabled := os.Getenv("RAG_GRAPH_EXPANSION") == "true" graphEnabled := os.Getenv("RAG_GRAPH_EXPANSION") == "true"
// KB-2026.1 authoritative slice (Blue-Green, additiv). Routing default AN; Rollback ohne
// Redeploy ueber RAG_KB_SCOPE_ROUTING=false (dann faellt alles auf den CE-Default zurueck).
kbSlice := os.Getenv("RAG_KB_SLICE_COLLECTION")
if kbSlice == "" {
kbSlice = "kb_2026_1_build"
}
kbScopeRouting := os.Getenv("RAG_KB_SCOPE_ROUTING") != "false"
return &LegalRAGClient{ return &LegalRAGClient{
qdrantURL: qdrantURL, qdrantURL: qdrantURL,
qdrantAPIKey: qdrantAPIKey, qdrantAPIKey: qdrantAPIKey,
@@ -54,6 +68,8 @@ func NewLegalRAGClient() *LegalRAGClient {
textIndexEnsured: make(map[string]bool), textIndexEnsured: make(map[string]bool),
hybridEnabled: hybridEnabled, hybridEnabled: hybridEnabled,
graphEnabled: graphEnabled, graphEnabled: graphEnabled,
kbSliceCollection: kbSlice,
kbScopeRoutingEnabled: kbScopeRouting,
httpClient: &http.Client{ httpClient: &http.Client{
Timeout: 60 * time.Second, Timeout: 60 * time.Second,
}, },
@@ -63,15 +79,13 @@ func NewLegalRAGClient() *LegalRAGClient {
// SearchCollection queries a specific Qdrant collection for relevant passages. // SearchCollection queries a specific Qdrant collection for relevant passages.
// If collection is empty, it falls back to the default collection (bp_compliance_ce). // If collection is empty, it falls back to the default collection (bp_compliance_ce).
func (c *LegalRAGClient) SearchCollection(ctx context.Context, collection string, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) { func (c *LegalRAGClient) SearchCollection(ctx context.Context, collection string, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) {
if collection == "" { return c.searchInternal(ctx, c.resolveCollection(query, collection), query, regulationIDs, topK)
collection = c.collection
}
return c.searchInternal(ctx, collection, query, regulationIDs, topK)
} }
// Search queries the compliance CE corpus for relevant passages. // Search queries the compliance corpus for relevant passages. The target collection is resolved by
// the Blue-Green slice routing: the KB-2026.1 slice for in-scope queries, else the broad CE default.
func (c *LegalRAGClient) Search(ctx context.Context, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) { func (c *LegalRAGClient) Search(ctx context.Context, query string, regulationIDs []string, topK int) ([]LegalSearchResult, error) {
return c.searchInternal(ctx, c.collection, query, regulationIDs, topK) return c.searchInternal(ctx, c.resolveCollection(query, ""), query, regulationIDs, topK)
} }
// searchInternal performs the actual search against a given collection. // searchInternal performs the actual search against a given collection.
@@ -162,7 +162,7 @@ async def update_ai_system(
db: Session = Depends(get_db), db: Session = Depends(get_db),
): ):
"""Update an AI system.""" """Update an AI system."""
from datetime import datetime from datetime import datetime, timezone
system = db.query(AISystemDB).filter(AISystemDB.id == system_id).first() system = db.query(AISystemDB).filter(AISystemDB.id == system_id).first()
if not system: if not system:
@@ -226,7 +226,7 @@ async def assess_ai_system(
db: Session = Depends(get_db), db: Session = Depends(get_db),
): ):
"""Run AI Act risk assessment for an AI system.""" """Run AI Act risk assessment for an AI system."""
from datetime import datetime from datetime import datetime, timezone
system = db.query(AISystemDB).filter(AISystemDB.id == system_id).first() system = db.query(AISystemDB).filter(AISystemDB.id == system_id).first()
if not system: if not system:
@@ -47,6 +47,8 @@ from compliance.services.canonical_control_service import (
_control_row, # re-exported for legacy test imports _control_row, # re-exported for legacy test imports
) )
logger = logging.getLogger(__name__)
router = APIRouter(prefix="/v1/canonical", tags=["canonical-controls"]) router = APIRouter(prefix="/v1/canonical", tags=["canonical-controls"])
@@ -14,7 +14,7 @@ Endpoints:
""" """
import logging import logging
from datetime import datetime, date, timedelta from datetime import datetime, date, timedelta, timezone
from calendar import month_abbr from calendar import month_abbr
from typing import Optional, Dict, Any, List from typing import Optional, Dict, Any, List
from decimal import Decimal from decimal import Decimal
@@ -26,10 +26,11 @@ versions). Module-level helpers re-exported for legacy tests.
import logging import logging
from typing import Any, List, Optional from typing import Any, List, Optional
from fastapi import APIRouter, Depends, Query from fastapi import APIRouter, Depends, HTTPException, Query
from pydantic import BaseModel from pydantic import BaseModel
from fastapi.responses import Response from fastapi.responses import Response
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
from sqlalchemy import text
from classroom_engine.database import get_db from classroom_engine.database import get_db
from compliance.api._http_errors import translate_domain_errors from compliance.api._http_errors import translate_domain_errors
@@ -484,6 +485,7 @@ async def list_dsfas(
async def create_dsfa( async def create_dsfa(
request: DSFACreate, request: DSFACreate,
tenant_id: Optional[str] = Query(None), tenant_id: Optional[str] = Query(None),
db: Session = Depends(get_db),
service: DSFAService = Depends(get_dsfa_service), service: DSFAService = Depends(get_dsfa_service),
) -> dict[str, Any]: ) -> dict[str, Any]:
"""Neue DSFA erstellen.""" """Neue DSFA erstellen."""
@@ -16,6 +16,11 @@ from the legacy path.
""" """
import logging import logging
import os
import json
import hashlib
import uuid as uuid_module
from datetime import datetime, timedelta
from typing import Any, Optional from typing import Any, Optional
from fastapi import APIRouter, Depends, File, HTTPException, Query, UploadFile from fastapi import APIRouter, Depends, File, HTTPException, Query, UploadFile
@@ -30,14 +35,15 @@ from ..db import (
EvidenceConfidenceEnum, EvidenceConfidenceEnum,
EvidenceTruthStatusEnum, EvidenceTruthStatusEnum,
) )
from ..db.models import EvidenceDB, ControlDB, AuditTrailDB from ..db.models import EvidenceDB, AuditTrailDB
from ..services.auto_risk_updater import AutoRiskUpdater from ..services.auto_risk_updater import AutoRiskUpdater
from ..services.evidence_service import EvidenceService from ..services.evidence_service import EvidenceService, _update_risks as _update_risks_impl
from .schemas import ( from .schemas import (
EvidenceCreate, EvidenceResponse, EvidenceListResponse, EvidenceCreate, EvidenceResponse, EvidenceListResponse,
EvidenceRejectRequest, EvidenceRejectRequest,
) )
from .audit_trail_utils import log_audit_trail from .audit_trail_utils import log_audit_trail
from ._http_errors import translate_domain_errors
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
router = APIRouter(tags=["compliance-evidence"]) router = APIRouter(tags=["compliance-evidence"])
@@ -146,6 +152,7 @@ async def list_evidence(
status: Optional[str] = None, status: Optional[str] = None,
page: Optional[int] = Query(None, ge=1, description="Page number (1-based)"), page: Optional[int] = Query(None, ge=1, description="Page number (1-based)"),
limit: Optional[int] = Query(None, ge=1, le=500, description="Items per page"), limit: Optional[int] = Query(None, ge=1, le=500, description="Items per page"),
db: Session = Depends(get_db),
service: EvidenceService = Depends(get_evidence_service), service: EvidenceService = Depends(get_evidence_service),
) -> EvidenceListResponse: ) -> EvidenceListResponse:
"""List evidence with optional filters and pagination.""" """List evidence with optional filters and pagination."""
@@ -186,9 +193,11 @@ async def list_evidence(
@router.post("/evidence", response_model=EvidenceResponse) @router.post("/evidence", response_model=EvidenceResponse)
async def create_evidence( async def create_evidence(
evidence_data: EvidenceCreate, evidence_data: EvidenceCreate,
db: Session = Depends(get_db),
service: EvidenceService = Depends(get_evidence_service), service: EvidenceService = Depends(get_evidence_service),
) -> EvidenceResponse: ) -> EvidenceResponse:
"""Create new evidence record.""" """Create new evidence record."""
dsms_cid = None
repo = EvidenceRepository(db) repo = EvidenceRepository(db)
# Get control UUID # Get control UUID
@@ -257,6 +266,7 @@ async def create_evidence(
@router.delete("/evidence/{evidence_id}") @router.delete("/evidence/{evidence_id}")
async def delete_evidence( async def delete_evidence(
evidence_id: str, evidence_id: str,
db: Session = Depends(get_db),
service: EvidenceService = Depends(get_evidence_service), service: EvidenceService = Depends(get_evidence_service),
) -> dict[str, Any]: ) -> dict[str, Any]:
"""Delete an evidence record.""" """Delete an evidence record."""
@@ -275,6 +285,7 @@ async def upload_evidence(
title: str = Query(...), title: str = Query(...),
file: UploadFile = File(...), file: UploadFile = File(...),
description: Optional[str] = Query(None), description: Optional[str] = Query(None),
db: Session = Depends(get_db),
service: EvidenceService = Depends(get_evidence_service), service: EvidenceService = Depends(get_evidence_service),
) -> EvidenceResponse: ) -> EvidenceResponse:
"""Upload evidence file.""" """Upload evidence file."""
@@ -674,6 +685,7 @@ async def collect_ci_evidence(
async def get_ci_evidence_status( async def get_ci_evidence_status(
control_id: Optional[str] = Query(None, description="Filter by control ID"), control_id: Optional[str] = Query(None, description="Filter by control ID"),
days: int = Query(30, description="Look back N days"), days: int = Query(30, description="Look back N days"),
db: Session = Depends(get_db),
service: EvidenceService = Depends(get_evidence_service), service: EvidenceService = Depends(get_evidence_service),
) -> dict[str, Any]: ) -> dict[str, Any]:
"""Get CI/CD evidence collection status overview.""" """Get CI/CD evidence collection status overview."""
@@ -681,70 +693,8 @@ async def get_ci_evidence_status(
return service.ci_status(control_id, days) return service.ci_status(control_id, days)
# ---------------------------------------------------------------------------- # (Alte CI-Status-Implementierung entfernt — unerreichbarer Code nach `return
# Legacy re-exports for tests that import helpers directly. # service.ci_status(...)`; durch den Service ersetzt, `query` war nie initialisiert.)
# ----------------------------------------------------------------------------
if control_id:
ctrl_repo = ControlRepository(db)
control = ctrl_repo.get_by_control_id(control_id)
if control:
query = query.filter(EvidenceDB.control_id == control.id)
evidence_list = query.order_by(EvidenceDB.collected_at.desc()).limit(100).all()
# Group by control and calculate stats
control_stats = defaultdict(lambda: {
"total": 0,
"valid": 0,
"failed": 0,
"last_collected": None,
"evidence": [],
})
for e in evidence_list:
# Get control_id string
control = db.query(ControlDB).filter(ControlDB.id == e.control_id).first()
ctrl_id = control.control_id if control else "unknown"
stats = control_stats[ctrl_id]
stats["total"] += 1
if e.status:
if e.status.value == "valid":
stats["valid"] += 1
elif e.status.value == "failed":
stats["failed"] += 1
if not stats["last_collected"] or e.collected_at > stats["last_collected"]:
stats["last_collected"] = e.collected_at
# Add evidence summary
stats["evidence"].append({
"id": e.id,
"type": e.evidence_type,
"status": e.status.value if e.status else None,
"collected_at": e.collected_at.isoformat() if e.collected_at else None,
"ci_job_id": e.ci_job_id,
})
# Convert to list and sort
result = []
for ctrl_id, stats in control_stats.items():
result.append({
"control_id": ctrl_id,
"total_evidence": stats["total"],
"valid_count": stats["valid"],
"failed_count": stats["failed"],
"last_collected": stats["last_collected"].isoformat() if stats["last_collected"] else None,
"recent_evidence": stats["evidence"][:5],
})
result.sort(key=lambda x: x["last_collected"] or "", reverse=True)
return {
"period_days": days,
"total_evidence": len(evidence_list),
"controls": result,
}
# ============================================================================ # ============================================================================
@@ -772,6 +722,7 @@ async def review_evidence(
approval_status='first_approved'. A second (different) reviewer then approval_status='first_approved'. A second (different) reviewer then
sets second_reviewer and approval_status='approved'. sets second_reviewer and approval_status='approved'.
""" """
dsms_cid = None
evidence = db.query(EvidenceDB).filter(EvidenceDB.id == evidence_id).first() evidence = db.query(EvidenceDB).filter(EvidenceDB.id == evidence_id).first()
if not evidence: if not evidence:
raise HTTPException(status_code=404, detail=f"Evidence {evidence_id} not found") raise HTTPException(status_code=404, detail=f"Evidence {evidence_id} not found")
@@ -851,6 +802,7 @@ async def reject_evidence(
db: Session = Depends(get_db), db: Session = Depends(get_db),
): ):
"""Reject evidence (sets approval_status='rejected').""" """Reject evidence (sets approval_status='rejected')."""
dsms_cid = None
evidence = db.query(EvidenceDB).filter(EvidenceDB.id == evidence_id).first() evidence = db.query(EvidenceDB).filter(EvidenceDB.id == evidence_id).first()
if not evidence: if not evidence:
raise HTTPException(status_code=404, detail=f"Evidence {evidence_id} not found") raise HTTPException(status_code=404, detail=f"Evidence {evidence_id} not found")
@@ -8,7 +8,7 @@ This adds NO new reasoning logic. It exposes the already-built, tested orchestra
""" """
import logging import logging
from typing import List, Optional from typing import Dict, List, Optional
from fastapi import APIRouter, HTTPException from fastapi import APIRouter, HTTPException
from pydantic import BaseModel, Field from pydantic import BaseModel, Field
@@ -20,7 +20,7 @@ from compliance.onboarding import (
ProducedSignal, ProducedSignal,
RejectedAssumption, RejectedAssumption,
) )
from compliance.services.onboarding_service import run_advisor, supported_targets from compliance.services.onboarding_service import labels_for, run_advisor, supported_targets
logger = logging.getLogger(__name__) logger = logging.getLogger(__name__)
router = APIRouter(prefix="/onboarding", tags=["onboarding"]) router = APIRouter(prefix="/onboarding", tags=["onboarding"])
@@ -50,6 +50,7 @@ class AdvisorResponse(BaseModel):
evidence_requests: List[str] = Field(default_factory=list) evidence_requests: List[str] = Field(default_factory=list)
unsupported_domains: List[str] = Field(default_factory=list) unsupported_domains: List[str] = Field(default_factory=list)
completeness_summary: str = "" completeness_summary: str = ""
capability_labels: Dict[str, str] = Field(default_factory=dict) # capability_id -> human label (DE)
@router.get("/targets") @router.get("/targets")
@@ -65,10 +66,17 @@ def advisor_start_endpoint(req: OnboardingAdvisorRequest) -> AdvisorResponse:
company=req.company, certifications=req.certifications, target=req.target, company=req.company, certifications=req.certifications, target=req.target,
signals=req.scanner_findings, known_evidence=req.known_evidence, signals=req.scanner_findings, known_evidence=req.known_evidence,
products=req.products, markets=req.markets, industry=req.industry or "") products=req.products, markets=req.markets, industry=req.industry or "")
surfaced = [
*result.auto_detected, *result.indications, *result.capability_delta,
*(q.capability_id for q in result.next_best_questions),
*(c for a in result.inferred_assumptions for c in a.capabilities),
*(m.capability_id for m in result.top_measures),
]
return AdvisorResponse( return AdvisorResponse(
silent_intake_summary=si_summary, headline=result.headline, auto_detected=result.auto_detected, silent_intake_summary=si_summary, headline=result.headline, auto_detected=result.auto_detected,
indications=result.indications, indications=result.indications,
inferred_assumptions=result.inferred_assumptions, rejected_assumptions=result.rejected_assumptions, inferred_assumptions=result.inferred_assumptions, rejected_assumptions=result.rejected_assumptions,
top_5_questions=result.next_best_questions, capability_delta=result.capability_delta, top_5_questions=result.next_best_questions, capability_delta=result.capability_delta,
top_measures=result.top_measures, evidence_requests=result.evidence_requests, top_measures=result.top_measures, evidence_requests=result.evidence_requests,
unsupported_domains=result.unsupported_domains, completeness_summary=result.completeness_summary) unsupported_domains=result.unsupported_domains, completeness_summary=result.completeness_summary,
capability_labels=labels_for(surfaced))
@@ -24,6 +24,7 @@ from fastapi.responses import FileResponse
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
from classroom_engine.database import get_db from classroom_engine.database import get_db
from ..db.models import EvidenceDB
from .audit_trail_utils import log_audit_trail from .audit_trail_utils import log_audit_trail
from ..db import ( from ..db import (
@@ -310,6 +311,7 @@ async def list_controls_paginated(
) )
async def get_control( async def get_control(
control_id: str, control_id: str,
db: Session = Depends(get_db),
svc: ControlExportService = Depends(get_ctrl_export_service), svc: ControlExportService = Depends(get_ctrl_export_service),
) -> ControlResponse: ) -> ControlResponse:
"""Get a specific control by control_id.""" """Get a specific control by control_id."""
@@ -354,6 +356,7 @@ async def get_control(
async def update_control( async def update_control(
control_id: str, control_id: str,
update: ControlUpdate, update: ControlUpdate,
db: Session = Depends(get_db),
svc: ControlExportService = Depends(get_ctrl_export_service), svc: ControlExportService = Depends(get_ctrl_export_service),
) -> ControlResponse: ) -> ControlResponse:
"""Update a control.""" """Update a control."""
@@ -443,6 +446,7 @@ async def update_control(
async def review_control( async def review_control(
control_id: str, control_id: str,
review: ControlReviewRequest, review: ControlReviewRequest,
db: Session = Depends(get_db),
svc: ControlExportService = Depends(get_ctrl_export_service), svc: ControlExportService = Depends(get_ctrl_export_service),
) -> ControlResponse: ) -> ControlResponse:
"""Mark a control as reviewed with new status.""" """Mark a control as reviewed with new status."""
@@ -21,7 +21,7 @@ Phase 1 Step 4 refactor: handlers delegate to VVTService.
import logging import logging
from typing import Any, List, Optional from typing import Any, List, Optional
from fastapi import APIRouter, Depends, Query, Request from fastapi import APIRouter, Depends, HTTPException, Query, Request
from fastapi.responses import StreamingResponse from fastapi.responses import StreamingResponse
from sqlalchemy.orm import Session from sqlalchemy.orm import Session
@@ -21,6 +21,14 @@ from .observations import (
empirical_distribution, empirical_distribution,
reviewed, reviewed,
) )
from .observation_log import (
HypothesisStats,
ObservationRecord,
aggregate_by_hypothesis,
append_observation,
load_observations,
review_queue,
)
from .signals import ( from .signals import (
ProducedSignal, ProducedSignal,
SignalVocabularyEntry, SignalVocabularyEntry,
@@ -69,4 +77,10 @@ __all__ = [
"ProducedSignal", "ProducedSignal",
"SignalVocabularyEntry", "SignalVocabularyEntry",
"normalize_signals", "normalize_signals",
"ObservationRecord",
"HypothesisStats",
"append_observation",
"load_observations",
"aggregate_by_hypothesis",
"review_queue",
] ]
@@ -143,8 +143,8 @@ def advisor_start(
next_best_questions=next_q, capability_delta=delta, top_measures=measures, next_best_questions=next_q, capability_delta=delta, top_measures=measures,
evidence_requests=evidence, unsupported_domains=unsupported, evidence_requests=evidence, unsupported_domains=unsupported,
completeness_summary=rep.completeness_summary, completeness_summary=rep.completeness_summary,
headline="%d Anforderungen erkannt · %d automatisch erkannt (Intake) · %d wahrscheinlich (Zertifikate) · %d zu klären" headline="%d von %d Anforderungen offen · %d automatisch erkannt (Intake) · %d wahrscheinlich (Zertifikate) · %d zu klären"
% (len(assess.coverage), len(auto_detected), len(probably), len(next_q))) % (len(delta), len(assess.coverage), len(auto_detected), len(probably), len(next_q)))
def apply_answer(known_capabilities: Sequence[str], capability_id: str, answer: str) -> List[str]: def apply_answer(known_capabilities: Sequence[str], capability_id: str, answer: str) -> List[str]:
@@ -0,0 +1,108 @@
"""Observation Log — append-only JSONL store for empirical calibration events (Task 59b v1).
Observations are NOT business data and NOT product-DB data they are CALIBRATION events for the
knowledge base ("ISO27001 -> SDL confirmed", "TISAX -> supplier security refuted"). So they live with the
other versioned knowledge artifacts (hypotheses, transition patterns, vocabulary), NOT in the product
database: an append-only JSONL log under `knowledge/observations/`. NO migration, NO DB. The empirical
DISTRIBUTION and CONFIDENCE are COMPUTED from this log on demand (computed-not-stored) a hypothesis is
NEVER auto-updated; only REVIEWED observations calibrate (the review gate, enforced in observations.py).
Append-only: each line is one ObservationRecord and lines are NEVER modified in place. A later review is
a NEW line with the same observation_id and reviewed=true; load_observations() reconciles to the latest
per id. You can `rm` the log and recompute, `git diff` it over months, or rebuild confidence under a new
policy. Anonymisation is MANDATORY: customer_archetype is a sector/cert archetype, NEVER a real company
name (this file is committed to git). Time is stamped by the CALLER (no hidden clock) for determinism.
I/O only at the append/load boundary; statistics are pure. Python 3.9 compatible.
"""
from __future__ import annotations
import json
import os
from typing import Dict, List, Optional, Sequence
from pydantic import BaseModel, Field
from .observations import Observation, empirical_confidence, empirical_distribution
_DEFAULT_LOG = os.path.join(
os.path.dirname(__file__), "..", "..", "knowledge", "observations", "observations.jsonl")
class ObservationRecord(Observation):
"""A persisted observation line: an Observation (with its review gate + observation_type) plus log
metadata. `observation_id` is stable a review re-appends the SAME id with reviewed=true."""
observation_id: str # stable id; a review re-appends the same id
timestamp: str = "" # ISO 8601, stamped by the CALLER (no hidden clock)
customer_archetype: str = "" # sector/cert archetype — NEVER a real company name
evidence: str = "" # what backs the answer (reference, not the artifact)
provenance: str = "" # where the answer came from (audit trail)
knowledge_version: str = "" # hypotheses/vocabulary version observed under
class HypothesisStats(BaseModel):
"""Per-hypothesis empirical rollup — all COMPUTED from the log, nothing stored on the hypothesis."""
hypothesis_id: str
distribution: Dict[str, int] = Field(default_factory=dict) # reviewed counts per observation_type
confidence: Optional[float] = None # None until a for/against obs is reviewed
reviewed_count: int = 0
total_count: int = 0
def append_observation(record: ObservationRecord, path: str = _DEFAULT_LOG) -> None:
"""Append ONE record as a JSON line. Append-only — existing lines are never rewritten."""
os.makedirs(os.path.dirname(path), exist_ok=True)
line = json.dumps(record.model_dump(mode="json"), ensure_ascii=False, sort_keys=True)
with open(path, "a", encoding="utf-8") as fh:
fh.write(line + "\n")
def load_observations(path: str = _DEFAULT_LOG, reconcile: bool = True) -> List[ObservationRecord]:
"""Read all records — a single `.jsonl` file or a directory of monthly `.jsonl` files. With
reconcile, the LATEST record per observation_id wins (a later reviewed=true supersedes the original).
Returns deterministic order (by observation_id when reconciled, else append order)."""
files: List[str] = []
if os.path.isdir(path):
files = sorted(os.path.join(path, f) for f in os.listdir(path) if f.endswith(".jsonl"))
elif os.path.exists(path):
files = [path]
records: List[ObservationRecord] = []
for fpath in files:
with open(fpath, encoding="utf-8") as fh:
for raw in fh:
raw = raw.strip()
if raw:
records.append(ObservationRecord(**json.loads(raw)))
if not reconcile:
return records
latest: Dict[str, ObservationRecord] = {}
for r in records: # file/append order -> later lines win
latest[r.observation_id] = r
return [latest[k] for k in sorted(latest)]
def aggregate_by_hypothesis(records: Sequence[ObservationRecord]) -> List[HypothesisStats]:
"""Per-hypothesis distribution + confidence. The review gate applies inside empirical_distribution/
empirical_confidence (reviewed-only), so unreviewed observations are counted in total but never
calibrate. Deterministic order (by hypothesis id)."""
by_hyp: Dict[str, List[ObservationRecord]] = {}
for r in records:
by_hyp.setdefault(r.hypothesis_id, []).append(r)
out: List[HypothesisStats] = []
for hyp in sorted(by_hyp):
obs = by_hyp[hyp]
out.append(HypothesisStats(
hypothesis_id=hyp,
distribution=empirical_distribution(obs), # reviewed-only (the gate)
confidence=empirical_confidence(obs), # None until reviewed for/against
reviewed_count=sum(1 for o in obs if o.reviewed),
total_count=len(obs)))
return out
def review_queue(records: Sequence[ObservationRecord]) -> List[ObservationRecord]:
"""The reviewer's worklist: observations not yet reviewed. Calibration ignores these until a reviewer
accepts them (Observation -> Review -> Accepted -> Knowledge recomputed), never Observation -> conf++."""
return [r for r in records if not r.reviewed]
@@ -9,7 +9,7 @@ It adds NO new reasoning logic — it only exposes what exists. No DB, no persis
from __future__ import annotations from __future__ import annotations
import os import os
from typing import Any, Dict, List, Sequence, Tuple from typing import Any, Dict, Iterable, List, Sequence, Tuple
import yaml import yaml
@@ -37,6 +37,13 @@ def _load(*parts: str) -> Any:
_HYP_LIB = [CapabilityHypothesis(**h) for h in _load("certification_hypotheses", "hypotheses.yaml")["hypotheses"]] _HYP_LIB = [CapabilityHypothesis(**h) for h in _load("certification_hypotheses", "hypotheses.yaml")["hypotheses"]]
_VOCAB = [SignalVocabularyEntry(**v) for v in _load("onboarding", "signal_vocabulary.yaml")["signals"]] _VOCAB = [SignalVocabularyEntry(**v) for v in _load("onboarding", "signal_vocabulary.yaml")["signals"]]
_SIGNAL_MAP = [SignalMapping(**m) for m in _load("onboarding", "intake_signal_map.yaml")["mappings"]] _SIGNAL_MAP = [SignalMapping(**m) for m in _load("onboarding", "intake_signal_map.yaml")["mappings"]]
_LABELS: Dict[str, str] = _load("onboarding", "capability_labels.yaml")["labels"]
def labels_for(capability_ids: Iterable[str]) -> Dict[str, str]:
"""Human labels (DE) for the given capability ids — presentation only. Ids without a curated label
are omitted (the frontend falls back to a prettified id). Deduped, deterministic."""
return {c: _LABELS[c] for c in dict.fromkeys(capability_ids) if c in _LABELS}
# target id -> transition pattern that defines its required capabilities (curated registry) # target id -> transition pattern that defines its required capabilities (curated registry)
_TARGET_PATTERNS = { _TARGET_PATTERNS = {
@@ -53,9 +60,10 @@ def supported_targets() -> List[str]:
def _target(target_id: str) -> Tuple[List[TargetRequirement], Dict[str, List[str]]]: def _target(target_id: str) -> Tuple[List[TargetRequirement], Dict[str, List[str]]]:
pat = _load("transition_patterns", _TARGET_PATTERNS[target_id]) pat = _load("transition_patterns", _TARGET_PATTERNS[target_id])
reqs = [TargetRequirement(capability_id=a["capability"]) for a in pat["likely_covered"]] reqs = [TargetRequirement(capability_id=a["capability"], rationale=a.get("reviewable_claim", "")) for a in pat["likely_covered"]]
reqs += [TargetRequirement(capability_id=d["capability"], question_intent=d.get("needed_information", "verify_existence"), reqs += [TargetRequirement(capability_id=d["capability"], question_intent=d.get("needed_information", "verify_existence"),
expected_evidence=d.get("expected_evidence", [])) for d in pat["delta_requirements"]] rationale=d.get("why_asked", ""), expected_evidence=d.get("expected_evidence", []))
for d in pat["delta_requirements"]]
covers = {d["capability"]: d.get("covers_targets", []) for d in pat["delta_requirements"]} covers = {d["capability"]: d.get("covers_targets", []) for d in pat["delta_requirements"]}
return reqs, covers return reqs, covers
@@ -104,7 +104,8 @@ def assess_transition(
) )
buckets[status].append(req.capability_id) buckets[status].append(req.capability_id)
if status in _REQUESTABLE: if status in _REQUESTABLE:
reason, prio = _REQUESTABLE[status] default_reason, prio = _REQUESTABLE[status]
reason = req.rationale or default_reason # curated human text wins over the generic fallback
requests.append( requests.append(
TransitionQuestionRequest( TransitionQuestionRequest(
capability_id=req.capability_id, capability_id=req.capability_id,
@@ -70,6 +70,7 @@ class TargetRequirement(BaseModel):
capability_id: str # MCAP-... capability_id: str # MCAP-...
question_intent: str = "verify_existence" # passed through to the request, not rendered question_intent: str = "verify_existence" # passed through to the request, not rendered
rationale: str = "" # curated human text (e.g. why_asked / reviewable_claim) — surfaced as the request reason
expected_evidence: List[str] = Field(default_factory=list) expected_evidence: List[str] = Field(default_factory=list)
source_control_id: Optional[str] = None source_control_id: Optional[str] = None
supports_obligations: List[str] = Field(default_factory=list) supports_obligations: List[str] = Field(default_factory=list)
@@ -0,0 +1,2 @@
# Append-only observation log (Task 59b). Real lines (observations.jsonl / YYYY-MM.jsonl) are written at
# runtime via compliance/onboarding/observation_log.py. Anonymised archetypes only — NEVER real company names.
@@ -0,0 +1,45 @@
# Human-readable capability labels (DE) — presentation only, reusable across all targets.
# A capability id is the stable machine identity; this maps it to an expert-facing label for the UI.
# Curated knowledge (draft — to be corrected by the domain expert). Missing ids fall back to a
# prettified id in the frontend. NO real company names. Keep labels short + concrete.
labels:
# ── ISMS / ISO 27001 core ───────────────────────────────────────────────
information_security_management: "Informationssicherheits-Managementsystem (ISMS)"
access_control_and_authentication: "Zugriffskontrolle & Authentifizierung"
asset_and_configuration_management: "Asset- & Konfigurationsverwaltung"
cryptography: "Kryptographie / Verschlüsselung"
incident_management: "Security-Incident-Management"
security_awareness_training: "Security-Awareness-Schulungen"
supplier_security: "Lieferanten-Sicherheit"
security_logging_and_monitoring: "Security-Logging & Monitoring"
technical_vulnerability_management: "Technisches Schwachstellen-Management"
# ── TISAX / VDA-spezifisch ──────────────────────────────────────────────
prototype_protection: "Prototypenschutz (physisch & logisch)"
tisax_label_scope_selection: "TISAX-Label-/Scope-Festlegung"
tisax_assessment_via_enx: "TISAX-Assessment über die ENX-Plattform"
vda_isa_self_assessment: "VDA-ISA-Selbstauskunft"
data_protection_processing_on_behalf: "Auftragsverarbeitung (Art. 28 DSGVO)"
physical_security: "Physische Sicherheit / Zutrittskontrolle"
# ── QM / ISO 9001 ───────────────────────────────────────────────────────
document_and_change_control: "Dokumenten- & Änderungslenkung"
supplier_evaluation: "Lieferantenbewertung"
release_and_approval_process: "Freigabe- & Genehmigungsprozess"
ce_conformity_assessment_and_technical_documentation: "CE-Konformitätsbewertung & technische Dokumentation"
# ── CRA / Produkt-Cybersecurity ─────────────────────────────────────────
sbom_creation: "SBOM-Erstellung (Software-Stückliste)"
coordinated_vulnerability_disclosure: "Coordinated Vulnerability Disclosure (CVD)"
secure_development_lifecycle: "Sicherer Entwicklungslebenszyklus (SDLC)"
secure_signed_update_distribution: "Sichere, signierte Update-Verteilung"
security_update_support_period: "Sicherheits-Update-Supportzeitraum"
product_cyber_risk_assessment: "Produkt-Cyber-Risikobewertung"
exploited_vuln_and_incident_reporting: "Meldung ausgenutzter Schwachstellen & Vorfälle"
public_security_advisories: "Öffentliche Security Advisories"
cybersecurity_management_system: "Cybersecurity-Managementsystem (CSMS)"
# ── MaschinenVO / Safety ────────────────────────────────────────────────
machine_safety_risk_assessment: "Maschinen-Risikobeurteilung"
mechanical_safety_and_guards: "Mechanische Sicherheit & Schutzeinrichtungen"
operating_instructions_and_safety_information: "Betriebsanleitung & Sicherheitshinweise"
protection_against_corruption_of_safety_functions: "Schutz der Sicherheitsfunktionen vor Manipulation"
# ── Umwelt ──────────────────────────────────────────────────────────────
environmental_management_documentation: "Umweltmanagement-Dokumentation"
@@ -0,0 +1,73 @@
"""Observation Log — append-only JSONL store + computed statistics (Task 59b/c v1).
Pins the user's decision (2026-06-28): observations are CALIBRATION data, not product data -> an
append-only JSONL log under knowledge/observations/, NO DB, NO migration. Distribution and confidence are
COMPUTED from the log; only REVIEWED observations calibrate (review gate); a later review is a new line
that supersedes by observation_id. Nothing is ever written back to a hypothesis.
"""
from __future__ import annotations
from compliance.onboarding import (
ObservationRecord,
ObservationType,
aggregate_by_hypothesis,
append_observation,
load_observations,
review_queue,
)
def _rec(oid, hyp, otype, reviewed=False, **kw):
return ObservationRecord(
observation_id=oid, hypothesis_id=hyp, observation_type=otype, reviewed=reviewed,
timestamp="2026-07-01T00:00:00Z", customer_archetype="machine_builder+ISO27001", **kw)
def test_append_only_round_trip(tmp_path):
p = str(tmp_path / "obs.jsonl")
append_observation(_rec("o1", "HYP-secure_dev", ObservationType.CONFIRMED, reviewed=True), p)
append_observation(_rec("o2", "HYP-secure_dev", ObservationType.REFUTED, reviewed=True), p)
recs = load_observations(p)
assert {r.observation_id for r in recs} == {"o1", "o2"}
assert all(r.customer_archetype == "machine_builder+ISO27001" for r in recs) # anonymised archetype, not a name
def test_review_supersedes_by_id_append_only(tmp_path):
p = str(tmp_path / "obs.jsonl")
append_observation(_rec("o1", "HYP-x", ObservationType.CONFIRMED, reviewed=False), p) # raw answer
append_observation(_rec("o1", "HYP-x", ObservationType.CONFIRMED, reviewed=True,
reviewed_by="anna"), p) # later review event
assert len(load_observations(p, reconcile=False)) == 2 # both lines kept (append-only)
recs = load_observations(p) # reconciled
assert len(recs) == 1 and recs[0].reviewed and recs[0].reviewed_by == "anna"
def test_statistics_apply_the_review_gate(tmp_path):
p = str(tmp_path / "obs.jsonl")
append_observation(_rec("a", "HYP-sdl", ObservationType.CONFIRMED, reviewed=True), p)
append_observation(_rec("b", "HYP-sdl", ObservationType.CONFIRMED, reviewed=True), p)
append_observation(_rec("c", "HYP-sdl", ObservationType.REFUTED, reviewed=True), p)
append_observation(_rec("d", "HYP-sdl", ObservationType.CONFIRMED, reviewed=False), p) # unreviewed -> ignored
stats = {s.hypothesis_id: s for s in aggregate_by_hypothesis(load_observations(p))}
s = stats["HYP-sdl"]
assert s.total_count == 4 and s.reviewed_count == 3
assert s.distribution["confirmed"] == 2 and s.distribution["refuted"] == 1 # unreviewed one excluded
assert s.confidence == round(2 / 3, 2) # (2 + 0.5*0) / 3
def test_review_queue_lists_unreviewed(tmp_path):
p = str(tmp_path / "obs.jsonl")
append_observation(_rec("a", "HYP-y", ObservationType.CONFIRMED, reviewed=True), p)
append_observation(_rec("b", "HYP-y", ObservationType.PARTIAL, reviewed=False), p)
q = review_queue(load_observations(p))
assert [r.observation_id for r in q] == ["b"]
def test_load_directory_of_monthly_files(tmp_path):
d = tmp_path / "observations"
d.mkdir()
append_observation(_rec("a", "HYP-z", ObservationType.CONFIRMED, reviewed=True), str(d / "2026-06.jsonl"))
append_observation(_rec("b", "HYP-z", ObservationType.REFUTED, reviewed=True), str(d / "2026-07.jsonl"))
recs = load_observations(str(d))
assert {r.observation_id for r in recs} == {"a", "b"}
@@ -73,6 +73,17 @@ def test_partial_signal_surfaces_as_indication_and_is_still_asked():
assert "secure_development_lifecycle" in asked or "secure_development_lifecycle" in d["capability_delta"] assert "secure_development_lifecycle" in asked or "secure_development_lifecycle" in d["capability_delta"]
def test_questions_carry_curated_text_and_human_labels():
# the curated why_asked from the transition pattern must reach the question (not the generic
# fallback "Keine Anhaltspunkte ... klären"), and surfaced capabilities get human labels.
body = dict(_BODY, certifications=["ISO27001"], target="TISAX", scanner_findings=[])
r = _client.post("/onboarding/advisor-start", json=body)
assert r.status_code == 200, r.text
d = r.json()
assert any("Keine Anhaltspunkte" not in q["why"] for q in d["top_5_questions"]) # real expert text surfaced
assert d["capability_labels"].get("vda_isa_self_assessment") == "VDA-ISA-Selbstauskunft"
def test_unknown_target_is_404(): def test_unknown_target_is_404():
body = dict(_BODY, target="NOPE") body = dict(_BODY, target="NOPE")
r = _client.post("/onboarding/advisor-start", json=body) r = _client.post("/onboarding/advisor-start", json=body)