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SDK API Reference

Exported symbols

from opencomplai import (
    assess,
    AssessmentInput,
    ModelMetadata,
    RiskResult,
    ScanStatusArtifact,
    SystemManifest,
)

assess(input: AssessmentInput) -> RiskResult

Run the rule engine against an AssessmentInput and return a RiskResult.

result = assess(assessment_input)

Parameters:

Parameter Type Description
input AssessmentInput The assessment input containing model metadata and optional rule answers.

Returns: RiskResult

AssessmentInput

Input to the risk assessment engine.

Field Type Default Description
model ModelMetadata (required) Metadata describing the AI model.
answers dict[str, Any] {} Rule-specific answers keyed by rule ID.

ModelMetadata

Metadata describing the AI model being assessed.

Field Type Description
name str Human-readable model name.
version str Model version identifier.
modality str e.g. text, image, multimodal.
use_case str Primary intended use case.
deployment_context str e.g. production, research, internal.

RiskResult

Output of the risk assessment engine.

Field Type Description
model_name str Model name from input.
model_version str Model version from input.
risk_level RiskLevel One of unacceptable, high, limited, minimal.
rules_evaluated int Total number of rules evaluated.
rules_passed int Number of passing rules.
rules_failed int Number of failing rules.
rule_results list[RuleResult] Per-rule pass/fail with rationale.
evidence_summary str Human-readable evidence summary.
generated_at str ISO 8601 timestamp.

RuleResult

Result for a single assessed rule.

Field Type Description
rule_id str Unique rule identifier (e.g. EU_AIA_ART6_HIGH_RISK).
rule_name str Human-readable rule name.
passed bool True if the rule passed.
rationale str Explanation of the outcome.
reference str EU AI Act article or clause reference.

ScanStatusArtifact

Machine-readable signed status artifact produced by opencomplai check. This is the CI-gate output written to compliance-artifact.json.

Field Type Description
install_id str UUID identifying the install instance.
system_id str System identifier from manifest.
commit_ref str Git commit reference.
result ScanResult pass, control_fail, validation_fail, policy_block, trap_detected, or degraded_complete.
failed_controls list[str] IDs of failing control checks.
evidence_hashes list[str] SHA-256 hashes of evidence objects.
rationale_hash str SHA-256 of the assessment rationale.
duration_ms int Check duration in milliseconds.
pending_verifications_count int Number of outstanding verification tasks.
signature str \| None Base64-encoded signature; None in unsigned OSS mode.

SystemManifest

System-of-record description of the AI system. Created by opencomplai init.

Field Type Default Description
system_id str (required) Unique system identifier.
intended_purpose str (required) Primary intended purpose (maps to Annex III categories).
compliance_target str EU_AI_ACT Compliance framework target.
high_risk_presumption bool False Provider presumes high-risk pending classification.
commit_ref str HEAD Git commit reference.

Enums

RiskLevel

from opencomplai_core.models import RiskLevel

RiskLevel.UNACCEPTABLE  # "unacceptable"
RiskLevel.HIGH          # "high"
RiskLevel.LIMITED       # "limited"
RiskLevel.MINIMAL       # "minimal"

ScanResult

from opencomplai_core.models import ScanResult

ScanResult.PASS                 # "pass"
ScanResult.CONTROL_FAIL         # "control_fail"
ScanResult.VALIDATION_FAIL      # "validation_fail"
ScanResult.POLICY_BLOCK         # "policy_block"
ScanResult.TRAP_DETECTED        # "trap_detected"
ScanResult.DEGRADED_COMPLETE    # "degraded_complete"