Files
breakpilot-compliance/backend-compliance
Benjamin Admin aa99111a87 feat(completeness): Regulatory Completeness Engine — auditable coverage, not confidence
Phase A½. The move from feature to product development: for every assessment, answer "how sure are
we that this answer is COMPLETE?" — different from confidence. The product never claims full coverage;
it makes its own knowledge state transparent and auditable. Shows what we do NOT know and why.

- compliance/completeness/: assess_completeness(identified, corpus_status, uncertain, assumptions,
  assessed_obligations) -> CompletenessReport. Separates IDENTIFIED from ASSESSED (validated corpus
  AND determined applicability) and justifies every gap. Two kinds of open: corpus gap (future_corpus)
  and applicability uncertainty (query_required + deciding question, e.g. Data Act / generates_usage_data).
- The metric is COUNTS, never a single percentage: "Identifiziert N · bewertet M · offen K ·
  Unsicherheiten U · Begründung ja" + an honest audit statement.
- ADR-007: auditable honesty; phase order A factory -> A½ Completeness -> B new domains; the
  transparency selling point. Deterministic, no LLM; corpus status + obligation count injected.
- reference suite: "Regulatory Completeness" section runs an industrial-dishwasher assessment
  (assessed CRA/MaschinenVO; open EMV/Environmental=future_corpus, Data Act=query_required) and notes
  Environmental flips open->validated automatically once the corpus lands.

11 completeness tests (54 with adjacent modules), mypy --strict clean (15 files), check-loc 0.
Product code with no app caller + ADR/reference = non-runtime -> no deploy (ADR-001). Freeze-safe.

Co-Authored-By: Claude Opus 4.7 <noreply@anthropic.com>
2026-06-27 14:16:12 +02:00
..

backend-compliance

Python/FastAPI service implementing the DSGVO compliance API: DSR, DSFA, consent, controls, risks, evidence, audit, vendor management, ISMS, change requests, document generation.

Port: 8002 (container: bp-compliance-backend) Stack: Python 3.12, FastAPI, SQLAlchemy 2.x, Alembic, Keycloak auth.

Architecture

compliance/
├── api/            # Routers (thin, ≤30 LOC per handler)
├── services/       # Business logic
├── repositories/   # DB access
├── domain/         # Value objects, domain errors
├── schemas/        # Pydantic models, split per domain
└── db/models/      # SQLAlchemy ORM, one module per aggregate

The service follows this layered target structure but not all files are fully refactored yet. Phase 1 backlog is tracked in .claude/rules/loc-exceptions.txt (27 backend-compliance files currently excepted).

See ../AGENTS.python.md for the full convention and ../.claude/rules/architecture.md for the non-negotiable rules.

Run locally

cd backend-compliance
pip install -r requirements.txt
export COMPLIANCE_DATABASE_URL=...  # Postgres (Hetzner or local)
uvicorn main:app --reload --port 8002

Tests

pytest compliance/tests/ -v
pytest --cov=compliance --cov-report=term-missing

Layout: tests/unit/, tests/integration/, tests/contracts/. Contract tests diff /openapi.json against tests/contracts/openapi.baseline.json.

Public API surface

404+ endpoints across /api/v1/*. Grouped by domain: ai, audit, consent, dsfa, dsr, gdpr, vendor, evidence, change-requests, generation, projects, company-profile, isms. Every path is a contract — see the "Public endpoints" rule in the root CLAUDE.md.

Environment

Var Purpose
COMPLIANCE_DATABASE_URL Postgres DSN, sslmode=require
KEYCLOAK_* Auth verification
QDRANT_URL, QDRANT_API_KEY Vector search
CORE_VALKEY_URL Session cache

Don't touch

Database schema, __tablename__, column names, existing migrations under migrations/. See root CLAUDE.md rule 3.