mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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b4531f0a4c
- Replace repo-preflight with docs-governance workflow and check_docs_links.py - Class B bundle: require correlation_id for external_*; AuditMetadata trace fields - Root-safe TIER1 §2; optional .githooks pre-push for main - Add RELEASE_READINESS_MATRIX_AR, SOURCE_OF_TRUTH_INDEX, operational severity, external index - ExecWeeklyGovernanceContract; expand trust-fabric, execution-fabric, ADR-0001, ws5, Saudi overlays - Wire MASTER TOC, enterprise-readiness, completion-program, architecture_brief paths Made-with: Cursor
149 lines
4.6 KiB
Python
149 lines
4.6 KiB
Python
"""Tests for decision plane bundle (Completion Program WS2)."""
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from __future__ import annotations
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import pytest
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from app.services.core_os.decision_memo import AuditMetadata, DecisionMemo, FinancialImpact
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from app.services.core_os.decision_plane_contracts import (
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ApprovalPacket,
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EvidencePack,
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ExecutionIntent,
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assemble_decision_bundle,
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new_evidence_pack_id,
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validate_class_b_bundle,
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)
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def test_assemble_decision_bundle_keys():
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memo = DecisionMemo(
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objective="Test objective",
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decision_context="ctx",
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inputs_used=["a"],
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assumptions=["x"],
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recommendation_ar="do thing",
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alternatives_considered=["b"],
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expected_financial_impact=FinancialImpact(),
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risk_register=[],
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confidence_score=80.0,
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required_approvals=["CEO"],
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next_best_action="approve",
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rollback_plan="revert",
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evidence_links=[],
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audit_metadata=AuditMetadata(agent_id="test_agent", timestamp="2026-01-01T00:00:00Z"),
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)
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ep = EvidencePack(
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pack_id=new_evidence_pack_id(),
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sources=["https://example.com/doc"],
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provenance_score=70.0,
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)
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ap = ApprovalPacket(
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approval_class="A2",
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reversibility_class="R2",
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sensitivity_class="S2",
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actor_type="recommender_agent",
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approvers_required=["CFO"],
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)
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ei = ExecutionIntent(
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workflow_key="partner_approval_v1",
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idempotency_key="idem-001",
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requested_side_effect_class="internal_write",
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correlation_id="corr-1",
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)
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bundle = assemble_decision_bundle(
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evidence_pack=ep,
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approval_packet=ap,
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execution_intent=ei,
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memo_json=memo.to_json(),
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)
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assert set(bundle.keys()) == {
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"memo_json",
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"evidence_pack_json",
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"risk_register_json",
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"approval_packet_json",
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"execution_intent_json",
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}
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assert bundle["approval_packet_json"]["approval_class"] == "A2"
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assert bundle["execution_intent_json"]["idempotency_key"] == "idem-001"
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validate_class_b_bundle(bundle)
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def test_validate_class_b_bundle_requires_correlation_for_external_commitment():
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memo = DecisionMemo(
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objective="x",
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decision_context="c",
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inputs_used=["i"],
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assumptions=["a"],
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recommendation_ar="r",
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alternatives_considered=["b"],
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expected_financial_impact=FinancialImpact(),
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risk_register=[],
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confidence_score=50.0,
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required_approvals=["CFO"],
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next_best_action="n",
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rollback_plan="rb",
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evidence_links=[],
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audit_metadata=AuditMetadata(agent_id="a", timestamp="2026-01-01T00:00:00Z"),
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)
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ep = EvidencePack(pack_id=new_evidence_pack_id(), provenance_score=1.0)
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ap = ApprovalPacket(
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approval_class="A2",
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reversibility_class="R2",
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sensitivity_class="S2",
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actor_type="executor_system",
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approvers_required=["CFO"],
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)
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ei = ExecutionIntent(
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workflow_key="w",
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idempotency_key="k",
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requested_side_effect_class="external_commitment",
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correlation_id=" ",
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payload_summary="x",
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)
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bundle = assemble_decision_bundle(
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evidence_pack=ep,
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approval_packet=ap,
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execution_intent=ei,
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memo_json=memo.to_json(),
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)
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with pytest.raises(ValueError, match="correlation_id"):
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validate_class_b_bundle(bundle)
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def test_validate_class_b_bundle_rejects_missing_memo_approvals():
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memo = DecisionMemo(
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objective="x",
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decision_context="c",
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inputs_used=["i"],
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assumptions=["a"],
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recommendation_ar="r",
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alternatives_considered=["b"],
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expected_financial_impact=FinancialImpact(),
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risk_register=[],
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confidence_score=50.0,
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required_approvals=[], # invalid for Class B
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next_best_action="n",
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rollback_plan="rb",
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evidence_links=[],
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audit_metadata=AuditMetadata(agent_id="a", timestamp="2026-01-01T00:00:00Z"),
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)
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ep = EvidencePack(pack_id=new_evidence_pack_id(), provenance_score=1.0)
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ap = ApprovalPacket(
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approval_class="A1",
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reversibility_class="R0",
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sensitivity_class="S0",
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actor_type="human",
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)
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ei = ExecutionIntent(
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workflow_key="w",
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idempotency_key="k",
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requested_side_effect_class="none",
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)
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bundle = assemble_decision_bundle(
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evidence_pack=ep,
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approval_packet=ap,
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execution_intent=ei,
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memo_json=memo.to_json(),
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)
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with pytest.raises(ValueError, match="required_approvals"):
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validate_class_b_bundle(bundle)
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