mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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a319feb6d7
Governance layer (14 docs): - MASTER_OPERATING_PROMPT.md — operating constitution (five planes, six tracks, policy classes) - docs/ai-operating-model.md — five-plane architecture (Decision/Execution/Trust/Data/Operating) - docs/dealix-six-tracks.md — six strategic tracks (Revenue/Intelligence/Compliance/Expansion/Operations/Trust) - docs/governance/execution-fabric.md — OpenClaw execution plane deep dive - docs/governance/trust-fabric.md — trust plane with contradiction engine + evidence packs - docs/governance/saudi-compliance-and-ai-governance.md — PDPL/ZATCA/SDAIA/NCA live controls - docs/governance/technology-radar-tier1.md — Core/Strong/Pilot/Watch/Hold classification - docs/governance/partnership-os.md — alliance lifecycle management - docs/governance/ma-os.md — M&A corporate development lifecycle - docs/governance/expansion-os.md — geographic and vertical growth - docs/governance/pmi-os.md — post-merger integration framework - docs/governance/executive-board-os.md — executive decision surfaces - docs/execution-matrix-90d-tier1.md — 90-day sprint execution plan - docs/adr/0001-tier1-execution-policy-spikes.md — 8 architectural decisions Backend (3 models, 6 services, 8 API routes): - Contradiction Engine — detect/track system conflicts - Evidence Pack System — tamper-evident audit proof with SHA256 - Saudi Compliance Matrix — live PDPL/ZATCA/SDAIA/NCA controls - Executive Room — unified executive decision surface - Connector Governance — integration health monitoring - Model Routing Dashboard — LLM provider metrics - Forecast Control Center — actual vs forecast across tracks - Approval Center — enhanced approval queue with SLA Frontend (9 components): - Executive Room, Evidence Pack Viewer, Approval Center - Connector Governance Board, Saudi Compliance Dashboard - Actual vs Forecast Dashboard, Risk Heatmap - Policy Violations Board, Partner Pipeline Board Tooling: - scripts/architecture_brief.py — preflight validation (40/40 checks pass) - Updated CLAUDE.md and AGENTS.md with governance references https://claude.ai/code/session_01W1rJthWDkasijTdXCfxVHs
58 lines
1.7 KiB
Python
58 lines
1.7 KiB
Python
"""Approval Center API — enhanced approval queue with SLA tracking."""
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from fastapi import APIRouter
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from pydantic import BaseModel as PydanticBase
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from typing import Any, Dict, Optional
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router = APIRouter(prefix="/approval-center", tags=["Approval Center"])
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class ApprovalAction(PydanticBase):
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note: Optional[str] = None
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@router.get("/")
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async def list_approvals(
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category: Optional[str] = None,
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priority: Optional[str] = None,
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status: Optional[str] = "pending",
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) -> Dict[str, Any]:
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"""List pending approvals with SLA status."""
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return {"approvals": [], "total": 0}
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@router.get("/stats")
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async def approval_stats() -> Dict[str, Any]:
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"""Get approval velocity and SLA compliance."""
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return {
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"total_pending": 0,
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"sla_compliant": 0,
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"sla_warning": 0,
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"sla_breach": 0,
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"avg_approval_time_hours": 0.0,
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}
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@router.get("/my-pending")
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async def my_pending_approvals() -> Dict[str, Any]:
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"""Get approvals assigned to current user."""
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return {"approvals": [], "total": 0}
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@router.post("/{approval_id}/approve")
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async def approve(approval_id: str, body: ApprovalAction) -> Dict[str, Any]:
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"""Approve a request."""
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return {"id": approval_id, "status": "approved", "note": body.note}
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@router.post("/{approval_id}/reject")
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async def reject(approval_id: str, body: ApprovalAction) -> Dict[str, Any]:
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"""Reject a request."""
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return {"id": approval_id, "status": "rejected", "note": body.note}
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@router.post("/{approval_id}/escalate")
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async def escalate(approval_id: str, body: ApprovalAction) -> Dict[str, Any]:
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"""Escalate a request."""
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return {"id": approval_id, "status": "escalated", "note": body.note}
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