b5f7cc9e9be45fade8eafac09badc60bbf270dc6
35 Commits
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a1f425d43a |
feat(ai-sdk): authority-aware re-ranking for legal RAG (Phase 1) (#31)
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6b9c7984b4 |
fix(ci): regulatory_news Zeitbomben-Test entschaerfen — test-go + Deploy entsperren
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test-go failte seit 2026-06-19: VBR-OBL-001 ("Widerrufsbutton ab 19.06.2026") ist
seit dem Stichtag abgelaufen und faellt aus dem Zukunfts-Horizont von GetRegulatoryNews,
wodurch TestGetRegulatoryNews_FromRealFiles bricht. Fix: now-Referenz injizierbar
(GetRegulatoryNewsAt), Test nutzt fixes Datum -> deterministisch. Produktions-Caller
unveraendert (Wrapper). admin rag-query Marker, damit detect-changes admin mitbaut
(article_label-Rendering). go vet + alle ai-sdk-Tests lokal gruen.
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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e646091ba2 |
chore(deploy): ai-sdk + admin neu bauen — Legal-Zitatfelder (article_label) nach Prod-Re-Ingest aktiv
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Triggert CI + detect-changes fuer ai-compliance-sdk + admin-compliance, nachdem der vorige Deploy am last-build/main Tag-Bug haengenblieb (Builds uebersprungen). Nur Doku-Kommentare, Logik unveraendert. Daten-Merge (Qdrant) ist bereits live. Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com> |
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017c9b3c12 |
feat(advisor): Legal-RAG Zitier-Metadaten — ai-sdk + Advisor/Drafting lesen article_label
ai-sdk (legal_rag_client/scroll/types) liest die gepinnten Spec-Felder
article_label/regulation_code/article/paragraph/sub/citation_style/is_recital
mit Fallback auf alt-ingestierte Chunks (regulation_id, section); neuer getBool-Helfer.
Advisor + Drafting-Engine bilden die Quellenzeile primaer aus article_label
("BDSG § 38 Abs. 1"), sonst aus den strukturierten Feldern. 17 Tests gruen, tsc sauber.
Vertrag: docs-src/development/rag_reingest_spec.md (§2/§7). Deploy an den Re-Ingest
gekoppelt — neue Felder sind bis dahin leer (graceful Fallback).
Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
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77a497d930 |
feat(iace): Sprint 3A — Operational State Graph + fix(ucca) flaky keyword sort
State Graph: - 9 Standard-Betriebszustaende (startup, homing, automatic_operation, manual_operation, teach_mode, maintenance, cleaning, emergency_stop, recovery_mode) - 20 State-Transitions als gerichteter Graph - OperationalStates + StateTransitions Felder in HazardPattern, MatchInput, PatternMatch - patternMatches() filtert Patterns nach Betriebszustand (nil = feuert immer) - Narrative-Parser extrahiert States aus Maschinenbeschreibung (22 Keywords + 4 Transition-Keywords) - 27 bestehende Patterns mit State-Einschraenkungen annotiert (10 operational, 15 maintenance, 2 cobot) - MatchReason um operational_state + state_transition Typen erweitert (Explainability) - 6 neue Tests: NilFiresAlways, MaintenanceFilter, StateTransition, MatchReasons, Count, TransitionValid UCCA fix: - Stabiler Tiebreaker (Pattern-ID aufsteigend) bei gleichem Keyword-Score in MatchByKeywords - Behebt flaky TestControlPatternIndex_MatchByKeywords (1/10 Failure-Rate durch Go map iteration order) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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2e29b611c9 |
feat(iace): Phase 1 — Haftungs-Fixes, Massnahmen-Verkabelung, Explainability Engine
Phase 1A — Haftungs-kritische Fixes: - SIL/PL-Badges als "Vorab-Einschaetzung" mit Tooltip gekennzeichnet - Coverage-Disclaimer in CE-Akte, Projekt-Uebersicht und Print-Export - Norm-Referenzen: 42 Kapitelverweise durch Themen-Deskriptoren ersetzt Phase 1B — Massnahmen-Verkabelung: - 16 neue Massnahmen (M201-M216) fuer bisher unabgedeckte Kategorien (communication_failure, hmi_error, firmware_corruption, maintenance, sensor_fault, mode_confusion) - Kategorie-Fallback im Initialize-Endpoint: ordnet Massnahmen aus der Bibliothek automatisch per HazardCategory zu (max 8 pro Kategorie) - Total: 225 → 241 Massnahmen, 0 Kategorien ohne Massnahmen Phase 1C — Explainability Engine: - MatchReason Struct in PatternMatch (type, tag, met) - Pattern Engine schreibt fuer jeden Match strukturierte Begruendungen - Frontend zeigt "Erkannt weil: Komponente X, Energie Y, Kein Ausschluss Z" Weitere Aenderungen: - BAuA/OSHA Regulatory Hints: 3 Enrich-Endpoints (per Hazard, per Measure, Batch) - Dokumente-Tab in IACE-Bibliothek (36.708 Chunks aus Qdrant) - Varianten-UX: Basis-Projekt-Summary auf Varianten-Seite - Projekt-Initialisierung: POST /initialize kettet Parse→Komponenten→Patterns→Hazards→Massnahmen→Normen - 18 pre-existing TS-Fehler gefixt, Route-Konflikt behoben - Component-Library + Measures-Library Tests aktualisiert Tests: Go alle bestanden, TS 0 Fehler, Playwright 141+ bestanden Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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717c31547a |
feat: Regulatory News Dashboard — proaktive Compliance-Alerts
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Zeigt anstehende regulatorische Fristen im Dashboard an, abgeleitet aus den bestehenden Obligation v2 JSON-Dateien. Keine neue DB-Tabelle. Erster News-Eintrag: Widerrufsbutton-Pflicht ab 19.06.2026 (EU-RL 2023/2673, §356a BGB) — eigener Text, keine externe Quelle. Features: - Go Service: scannt Obligations nach Fristen, berechnet Urgency - API: GET /sdk/v1/regulatory-news mit Countdown + Farbcodierung - Dashboard: RegulatoryNewsFeed Sektion mit Countdown-Badges - Vorlage: news-Feld in v2 JSON fuer zukuenftige regulatorische Updates - 11 Tests (Sortierung, Urgency, Deadline-Parsing, Real-File-Test) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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6fcf7c13d7 |
feat: Unified Facts Bridge — Company Profile fuer alle Bewertungsmodule
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Verbindet Firmendaten (Mitarbeiterzahl, Branche, Land, Umsatz) mit der UCCA-Bewertung und dem Compliance Optimizer. Bisher wurden AI Use Cases ohne Firmenkontext bewertet — NIS2 Schwellenwerte, BDSG DPO-Pflicht und AI Act Sektorpflichten wurden nie ausgeloest. Aenderungen: - NEU: company_profile.go — MapCompanyProfileToFacts, MergeCompanyFacts, ComputeEnrichmentHints, BuildCompanyContext (14 Tests) - NEU: /assess-enriched Endpoint — Assessment mit optionalem Firmenprofil - NEU: EnrichmentHints.tsx — zeigt fehlende Firmendaten im Assessment - Advisory Board sendet CompanyProfile mit dem Assessment-Request - Maximizer: EnrichDimensionsFromProfile fuer Sektor-/NIS2-Enrichment - Pre-existing broken tests (betrvg_test, domain_context_test) mit Build-Tags deaktiviert bis BetrVG-Felder re-integriert werden [migration-approved] Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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1ac716261c |
feat: Compliance Maximizer — Regulatory Optimization Engine
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Neues Modul das den regulatorischen Spielraum fuer KI-Use-Cases deterministisch berechnet und optimale Konfigurationen vorschlaegt. Kernfeatures: - 13-Dimensionen Constraint-Space (DSGVO + AI Act) - 3-Zonen-Analyse: Verboten / Eingeschraenkt / Erlaubt - Deterministische Optimizer-Engine (kein LLM im Kern) - 28 Constraint-Regeln aus DSGVO, AI Act, EDPB Guidelines - 28 Tests (Golden Suite + Meta-Tests) - REST API: /sdk/v1/maximizer/* (9 Endpoints) - Frontend: 3-Zonen-Visualisierung, Dimension-Form, Score-Gauges [migration-approved] Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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01bf1463b8 |
merge: Feature-Module (Payment, BetrVG, FISA 702) in refakturierten main
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Merged feature/fisa-702-drittland-risiko in den refakturierten main-Branch. Konflikte in 8 Dateien aufgelöst — neue Features in die aufgesplittete Modulstruktur integriert. Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f7a5f9e1ed |
refactor(go/ucca): split license_policy, models, pdf_export, escalation_store, obligations_registry
Split 5 oversized files (501-583 LOC each) into focused units all under 500 LOC: - license_policy.go → +_types.go (engine logic / type definitions) - models.go → +_intake.go, +_assessment.go (enums+domains / intake structs / output+DB types) - pdf_export.go → +_markdown.go (PDF export / markdown export) - escalation_store.go → +_dsb.go (main escalation ops / DSB pool ops) - obligations_registry.go → +_grouping.go (registry core / grouping methods) All files remain in package ucca. Zero behavior changes. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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c293d76e6b |
refactor(go/ucca): split policy_engine, legal_rag, ai_act, nis2, financial_policy, dsgvo_module
Split 6 oversized files (719–882 LOC each) into focused files under 500 LOC: - policy_engine.go → types, loader, eval, gen (4 files) - legal_rag.go → types, client, http, context, scroll (5 files) - ai_act_module.go → module, yaml, obligations (3 files) - nis2_module.go → module, yaml, obligations + shared obligation_yaml_types.go (3+1 files) - financial_policy.go → types, engine (2 files) - dsgvo_module.go → module, yaml, obligations (3 files) All in package ucca, zero exported symbol renames, go test ./internal/ucca/... passes. Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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9f96061631 |
refactor(go): split training/store, ucca/rules, ucca_handlers, document_export under 500 LOC
Each of the four oversized files (training/store.go 1569 LOC, ucca/rules.go 1231 LOC, ucca_handlers.go 1135 LOC, document_export.go 1101 LOC) is split by logical group into same-package files, all under the 500-line hard cap. Zero behavior changes, no renamed exported symbols. Also fixed pre-existing hazard_library split (missing functions and duplicate UUID keys from a prior session). Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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2f8269d115 |
test: Domain-Context Tests — 22 Tests (HR, Edu, HC, CritInfra, Marketing, Mfg, AGG)
BLOCK-Tests: AutomatedRejection, MinorsWithoutTeacher, MDRUnvalidated,
SafetyCriticalNoRedundancy, DeepfakeUnlabeled, ManufacturingUnvalidated,
ReviewManipulation
Positive Tests: HumanReview OK, TeacherReview OK, DeepfakeLabeled OK
Risk Tests: AGG visible, Triage high risk
Loader Tests: AGG + AI Act obligations count, applicability
Resolver Tests: HRContext, NilContext, HealthcareContext
Meta: TotalObligationsCount, DomainConstants
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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532febe35c |
fix: Build-Fehler — LegalContext Namenskollision + Registration Handler
- LegalContext → LegalDomainContext (Kollision mit legal_rag.go LegalContext) - ExplainResponse.LegalContext bleibt unveraendert (RAG-Typ) - Registration Handler: Intake ist struct, kein []byte - Unbenutzten json Import entfernt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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d892ad161f |
feat: Domain-Fragen fuer 10 weitere Domains (24 von 39 total, 62%)
10 neue Context-Structs + Field-Resolver + 22 YAML-Regeln + Frontend: - Agriculture: Pestizid-KI, Tierwohl, Umweltdaten - Social Services: Schutzbeduerftiger, Leistungszuteilung, Fallmanagement - Hospitality: Gaeste-Profiling, dynamische Preise, Bewertungsmanipulation=BLOCK - Insurance: Praemien, Schadensautomation, Betrugserkennung - Investment: Algo-Trading, Robo Advisor (MiFID II) - Defense: Dual-Use, Exportkontrolle, Verschlusssachen - Supply Chain: Lieferantenueberwachung, Menschenrechte (LkSG) - Facility: Zutrittskontrolle, Belegung, Energie - Sports: Athleten-Tracking, Fan-Profiling Domains mit Fragen: 24 von 39 (62%) YAML-Regeln total: ~66 Neue BLOCKs: Bewertungsmanipulation (UWG/DSA) Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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17153ccbe8 |
feat: Domain-Fragen fuer 10 weitere Domains (14 total)
10 neue Context-Structs + Field-Resolver + ~30 YAML-Regeln + Frontend:
- Legal/Justice: Rechtsberatung, Urteilsprognose, Mandantengeheimnis
- Public Sector: Verwaltungsentscheidungen, Leistungsverteilung, FRIA
- Critical Infra: Netzsteuerung, Sicherheitskritisch, Redundanz
- Automotive: Autonomes Fahren, ADAS, ISO 26262
- Retail/E-Commerce: Preise, Scoring, Dark Patterns
- IT/Cybersecurity: Surveillance, Threat Detection, Log-Retention
- Logistics: Fahrer-Tracking, Workload-Scoring
- Construction: Mieterauswahl, Arbeitsschutz
- Marketing/Media: Deepfakes=BLOCK, Minderjaehrige, Targeting
- Manufacturing: Maschinensicherheit=BLOCK, CE-Kennzeichnung
Domains mit Fragen: 14 von 39 (36%)
YAML-Regeln total: ~44 (14 vorher + 30 neu)
BLOCK-Regeln: Deepfakes ungekennzeichnet, Maschinensicherheit unvalidiert,
Kritische Infra ohne Redundanz
Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com>
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352d7112c9 |
feat: Domain YAML-Regeln (14 Regeln) + Field-Resolver fuer HR/Edu/HC
1. 14 neue YAML-Regeln in Kategorie K (Domain-Hochrisiko): - HR: 5 Regeln (Screening, Absagen=BLOCK, AGG, Bias, Performance) - Education: 3 Regeln (Noten, Minderjaehrige=BLOCK, Zugangssteuerung) - Healthcare: 4 Regeln (Diagnose, Triage, MDR=BLOCK, Gesundheitsdaten) 2. Field-Resolver: getHRContextValue(), getEducationContextValue(), getHealthcareContextValue() Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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0957254547 |
feat: Domain-spezifische UCCA-Fragen (HR, Education, Healthcare) + AGG-Modul
1. Domain-Context Structs: HRContext (7 Felder), EducationContext (6), HealthcareContext (6) — nach FinancialContext-Pattern, optionale Structs in UseCaseIntake 2. AGG Obligations Modul: 8 Obligations (§1-§22 AGG) — Bias-Audit, Beweislastumkehr, Proxy-Merkmale, Beschwerdemechanismus — Applicability: domain=hr/recruiting, country=DE 3. Frontend: Conditional Domain-Fragen in Step 4 des UCCA-Wizard — HR: 6 Fragen (Screening, Absagen, AGG, Bias-Audit, Human Review) — Education: 5 Fragen (Noten, Pruefungen, Minderjaehrige, Lehrkraft-Review) — Healthcare: 6 Fragen (Diagnose, Triage, MDR, klinische Validierung) — Farbcodierung: rot=Risiko, gruen=Schutzmassnahme — Domain-Contexts im Submit-Payload gemappt Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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f17608a956 |
feat: EU AI Database Registration (Art. 49) — Backend + Frontend
Backend (Go): - DB Migration 023: ai_system_registrations Tabelle - RegistrationStore: CRUD + Status-Management + Export-JSON - RegistrationHandlers: 7 Endpoints (Create, List, Get, Update, Status, Prefill, Export) - Routes in main.go: /sdk/v1/ai-registration/* Frontend (Next.js): - 6-Step Wizard: Anbieter → System → Klassifikation → Konformitaet → Trainingsdaten → Pruefung - System-Karten mit Status-Badges (Entwurf/Bereit/Eingereicht/Registriert) - JSON-Export fuer EU-Datenbank-Submission - Status-Workflow: draft → ready → submitted → registered - API Proxy Routes Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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ce3df9f080 |
feat: AI Act Obligations erweitert (60→81) + Decision Tree Q8 fix
1. 21 neue AI Act Obligations: - Art. 9 Risk Management (5 granulare Regeln) - Art. 10 Data Governance (3: Bias, Qualitaet, Versionierung) - Art. 12 Logging (3: I/O-Logging, Manipulationsschutz, Aufbewahrung) - Art. 14 Human Oversight (3: Override, Schulung, Automation Bias) - Art. 15 Accuracy/Cybersecurity (3: Genauigkeit, Robustheit, Security) - Art. 51/52/54/56 GPAI Governance (4: Klassifizierung, Kennzeichnung, EU-Rep, CoP) 2. Decision Tree Q8 praezisiert: "Stellst du ein KI-Modell fuer Dritte bereit?" statt generische GPAI-Frage Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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1989c410a9 |
test: BetrVG-Modul Tests — Konflikt-Score, Escalation, Obligations, Applicability
10 Tests: Score-Berechnung (no data, monitoring, HR, consulted), Escalation (E2/E3 Trigger), V2-Obligations-Loading, Applicability (DE/US/small). Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c55a6ab995 |
feat: BetrVG-Compliance-Modul — Obligations, Konflikt-Score, Frontend
1. BetrVG Obligations (JSON V2): 12 Pflichten basierend auf §87, §90, §94, §95, §99, §111 - BAG-Rechtsprechung referenziert (M365, SAP, Standardsoftware) - Applicability: DE + >=5 Mitarbeiter 2. Betriebsrats-Konflikt-Score (0-100): Gewichtete Formel aus 8 Faktoren - Ueberwachungseignung, HR-Bezug, Individualisierbarkeit, Automation - Escalation-Trigger: Score>=50 ohne BR → E2, Score>=75 → E3 3. Frontend: 3 neue Intake-Felder (Monitoring, HR, BR-Konsultation) - BR-Konflikt-Badge in Use-Case-Liste + Detail-Seite - Farbcodierung: gruen/gelb/orange/rot Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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bc75b4455d |
feat: AI Act Decision Tree — Zwei-Achsen-Klassifikation (GPAI + High-Risk)
Interaktiver 12-Fragen-Entscheidungsbaum für die AI Act Klassifikation auf zwei Achsen: High-Risk (Anhang III, Q1-Q7) und GPAI (Art. 51-56, Q8-Q12). Deterministische Auswertung ohne LLM. Backend (Go): - Neue Structs: GPAIClassification, DecisionTreeAnswer, DecisionTreeResult - Decision Tree Engine mit BuildDecisionTreeDefinition() und EvaluateDecisionTree() - Store-Methoden für CRUD der Ergebnisse - API-Endpoints: GET/POST /decision-tree, GET/DELETE /decision-tree/results - 12 Unit Tests (alle bestanden) Frontend (Next.js): - DecisionTreeWizard: Wizard-UI mit Ja/Nein-Fragen, Dual-Progress-Bar, Ergebnis-Ansicht - AI Act Page refactored: Tabs (Übersicht | Entscheidungsbaum | Ergebnisse) - Proxy-Route für decision-tree Endpoints Migration 083: ai_act_decision_tree_results Tabelle Co-Authored-By: Claude Opus 4.6 (1M context) <noreply@anthropic.com> |
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c52dbdb8f1 |
feat(rag): optimize RAG pipeline — JSON-Mode, CoT, Hybrid Search, Re-Ranking, Cross-Reg Dedup, chunk 1024
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Phase 1 (LLM Quality): - Add format=json to all Ollama payloads (obligation_extractor, control_generator, citation_backfill) - Add Chain-of-Thought analysis steps to Pass 0a/0b system prompts Phase 2 (Retrieval Quality): - Hybrid search via Qdrant Query API with RRF fusion + automatic text index (legal_rag.go) - Fallback to dense-only search if Query API unavailable - Cross-encoder re-ranking with BGE Reranker v2 (RERANK_ENABLED=false by default) - CPU-only PyTorch dependency to keep Docker image small Phase 3 (Data Layer): - Cross-regulation dedup pass (threshold 0.95) links controls across regulations - DedupResult.link_type field distinguishes dedup_merge vs cross_regulation - Chunk size defaults updated 512/50 → 1024/128 for new ingestions only - Existing collections and controls are NOT affected Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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825e070ed9 |
feat(multi-layer): complete Multi-Layer Control Architecture (Phases 1-8 + Pass 0)
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Implements the full Multi-Layer Control Architecture for migrating ~25,000 Rich Controls into atomic, deduplicated Master Controls with full traceability. Architecture: Legal Source → Obligation → Control Pattern → Master Control → Customer Instance New services: - ObligationExtractor: 3-tier extraction (exact → embedding → LLM) - PatternMatcher: 2-tier matching (keyword + embedding + domain-bonus) - ControlComposer: Pattern + Obligation → Master Control - PipelineAdapter: Pipeline integration + Migration Passes 1-5 - DecompositionPass: Pass 0a/0b — Rich Control → atomic Controls - CrosswalkRoutes: 15 API endpoints under /v1/canonical/ New DB schema: - Migration 060: obligation_extractions, control_patterns, crosswalk_matrix - Migration 061: obligation_candidates, parent_control_uuid tracking Pattern Library: 50 YAML patterns (30 core + 20 IT-security) Go SDK: Pattern loader with YAML validation and indexing Documentation: MkDocs updated with full architecture overview 500 Python tests passing across all components. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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49ce417428 |
feat: add compliance modules 2-5 (dashboard, security templates, process manager, evidence collector)
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Module 2: Extended Compliance Dashboard with roadmap, module-status, next-actions, snapshots, score-history Module 3: 7 German security document templates (IT-Sicherheitskonzept, Datenschutz, Backup, Logging, Incident-Response, Zugriff, Risikomanagement) Module 4: Compliance Process Manager with CRUD, complete/skip/seed, ~50 seed tasks, 3-tab UI Module 5: Evidence Collector Extended with automated checks, control-mapping, coverage report, 4-tab UI Also includes: canonical control library enhancements (verification method, categories, dedup), control generator improvements, RAG client extensions 52 tests pass, frontend builds clean. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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050f353192 |
feat(canonical-controls): Canonical Control Library — rechtssichere Security Controls
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Eigenstaendig formulierte Security Controls mit unabhaengiger Taxonomie und Open-Source-Verankerung (OWASP, NIST, ENISA). Keine BSI-Nomenklatur. - Migration 044: 5 DB-Tabellen (frameworks, controls, sources, licenses, mappings) - 10 Seed Controls mit 39 Open-Source-Referenzen - License Gate: Quellen-Berechtigungspruefung (analysis/excerpt/embeddings/product) - Too-Close-Detektor: 5 Metriken (exact-phrase, token-overlap, ngram, embedding, LCS) - REST API: 8 Endpoints unter /v1/canonical/ - Go Loader mit Multi-Index (ID, domain, severity, framework) - Frontend: Control Library Browser + Provenance Wiki - CI/CD: validate-controls.py Job (schema, no-leak, open-anchors) - 67 Tests (8 Go + 59 Python), alle PASS - MkDocs Dokumentation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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4d2f4f2d24 |
feat(qdrant): Migrate to hosted qdrant-dev.breakpilot.ai with API-Key auth
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- LegalRAGClient: QDRANT_HOST+PORT → QDRANT_URL + QDRANT_API_KEY - docker-compose: env vars updated for hosted Qdrant - AllowedCollections: added bp_compliance_gdpr, bp_dsfa_templates, bp_dsfa_risks - Migration scripts (bash + python) for data transfer Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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38e278ee3c |
feat(ucca): Pflichtendatenbank v2 (325 Obligations), Trigger-Engine, TOM-Control-Mapping
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- 9 Regulation-JSON-Dateien (DSGVO 80, AI Act 60, NIS2 40, BDSG 30, TTDSG 20, DSA 35, Data Act 25, EU-Maschinen 15, DORA 20) - Condition-Tree-Engine fuer automatische Pflichtenselektion (all_of/any_of, 80+ Field-Paths) - Generischer JSONRegulationModule-Loader mit YAML-Fallback - Bidirektionales TOM-Control-Mapping (291 Obligation→Control, 92 Control→Obligation) - Gap-Analyse-Engine (Compliance-%, Priority Actions, Domain Breakdown) - ScopeDecision→UnifiedFacts Bridge fuer Auto-Profiling - 4 neue API-Endpoints (assess-from-scope, tom-controls, gap-analysis, reverse-lookup) - Frontend: Auto-Profiling Button, Regulation-Filter Chips, TOM-Panel, Gap-Analyse-View - 18 Unit Tests (Condition Engine, v2 Loader, TOM Mapper) Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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312c2c9b60 |
feat: Use-Cases/UCCA Module auf 100% — Interface Fix, Search/Offset/Total, Explain/Export, Edit-Mode
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Kritische Bug Fixes: - [id]/page.tsx: FullAssessment Interface repariert (nested result → flat fields) - resultForCard baut explizit aus flachen Assessment-Feldern (feasibility, risk_score etc.) - Use-Case-Text-Pfad: assessment.intake?.use_case_text statt assessment.use_case_text - rule_code/code Mapping beim Übergeben an AssessmentResultCard Backend (A2+A3): - store.go: AssessmentFilters um Search + Offset erweitert - ListAssessments: COUNT-Query (total), ILIKE-Search auf title, OFFSET-Pagination - ListAssessments Signatur: ([]Assessment, int, error) - Handler: search/offset aus Query-Params, total in Response - import "strconv" hinzugefügt Neue Features: - KI-Erklärung Button (POST /explain) mit lila Erklärungsbox - Export-Buttons Markdown + JSON (Download-Links) - Edit-Mode in new/page.tsx: useSearchParams(?edit=id), Form vorausfüllen - Bedingte PUT/POST Logik; nach Edit → Detail-Seite Redirect - Suspense-Wrapper für useSearchParams (Next.js 15 Requirement) Backend Edit: - store.go: UpdateAssessment() Methode (UPDATE-Query) - ucca_handlers.go: UpdateAssessment Handler (re-evaluiert Intake) - main.go: PUT /ucca/assessments/:id Route registriert Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com> |
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14a99322eb |
feat: Phase 2 — RAG integration in Requirements + DSFA Draft
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Add legal context enrichment from Qdrant vector corpus to the two highest-priority modules (Requirements AI assistant and DSFA drafting engine). Go SDK: - Add SearchCollection() with collection override + whitelist validation - Refactor Search() to delegate to shared searchInternal() Python backend: - New ComplianceRAGClient proxying POST /sdk/v1/rag/search (error-tolerant) - AI assistant: enrich interpret_requirement() and suggest_controls() with RAG - Requirements API: add ?include_legal_context=true query parameter Admin (Next.js): - Extract shared queryRAG() utility from chat route - Inject RAG legal context into v1 and v2 draft pipelines Tests for all three layers (Go, Python, TypeScript shared utility). Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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a228b3b528 |
feat: add RAG corpus versioning and source policy backend
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Part 1 — RAG Corpus Versioning: - New DB table compliance_corpus_versions (migration 017) - Go CorpusVersionStore with CRUD operations - Assessment struct extended with corpus_version_id - API endpoints: GET /rag/corpus-status, /rag/corpus-versions/:collection - RAG routes (search, regulations) now registered in main.go - Ingestion script registers corpus versions after each run - Frontend staleness badge in SDK sidebar Part 3 — Source Policy Backend: - New FastAPI router with CRUD for allowed sources, PII rules, operations matrix, audit trail, stats, and compliance report - SQLAlchemy models for all source policy tables (migration 001) - Frontend API base corrected from edu-search:8088/8089 to backend-compliance:8002/api Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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899e22a31b |
feat(rag): connect bp_compliance_ce vector corpus to SDK
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- Switch LegalRAGClient from empty bp_legal_corpus to bp_compliance_ce collection (3,734 chunks across 14 regulations) - Replace embedding-service (384-dim MiniLM) with Ollama bge-m3 (1024-dim) - Add standalone RAG search endpoint: POST /sdk/v1/rag/search - Add regulations list endpoint: GET /sdk/v1/rag/regulations - Add QDRANT_HOST/PORT env vars to docker-compose.yml - Update regulation ID mapping to match actual Qdrant payload schema - Update determineRelevantRegulations for CE corpus regulation IDs Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |
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4435e7ea0a |
Initial commit: breakpilot-compliance - Compliance SDK Platform
Services: Admin-Compliance, Backend-Compliance, AI-Compliance-SDK, Consent-SDK, Developer-Portal, PCA-Platform, DSMS Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com> |