e6201d5239
Implement full evidence integrity pipeline to prevent compliance theater: - Confidence levels (E0-E4), truth status tracking, assertion engine - Four-Eyes approval workflow, audit trail, reject endpoint - Evidence distribution dashboard, LLM audit routes - Traceability matrix (backend endpoint + Compliance Hub UI tab) - Anti-fake badges, control status machine, normative patterns - 2 migrations, 4 test suites, MkDocs documentation Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
59 lines
1.2 KiB
Python
59 lines
1.2 KiB
Python
"""Database models and repository for Compliance module."""
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from .models import (
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RegulationDB,
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RequirementDB,
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ControlDB,
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ControlMappingDB,
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EvidenceDB,
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RiskDB,
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AuditExportDB,
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LLMGenerationAuditDB,
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AssertionDB,
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RegulationTypeEnum,
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ControlTypeEnum,
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ControlDomainEnum,
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RiskLevelEnum,
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EvidenceStatusEnum,
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ControlStatusEnum,
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EvidenceConfidenceEnum,
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EvidenceTruthStatusEnum,
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)
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from .repository import (
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RegulationRepository,
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RequirementRepository,
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ControlRepository,
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EvidenceRepository,
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RiskRepository,
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AuditExportRepository,
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)
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__all__ = [
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# Models
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"RegulationDB",
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"RequirementDB",
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"ControlDB",
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"ControlMappingDB",
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"EvidenceDB",
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"RiskDB",
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"AuditExportDB",
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"LLMGenerationAuditDB",
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"AssertionDB",
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# Enums
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"RegulationTypeEnum",
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"ControlTypeEnum",
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"ControlDomainEnum",
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"RiskLevelEnum",
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"EvidenceStatusEnum",
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"ControlStatusEnum",
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"EvidenceConfidenceEnum",
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"EvidenceTruthStatusEnum",
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# Repositories
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"RegulationRepository",
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"RequirementRepository",
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"ControlRepository",
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"EvidenceRepository",
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"RiskRepository",
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"AuditExportRepository",
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]
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