mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 15:29:36 +00:00
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
33 lines
982 B
Python
33 lines
982 B
Python
"""Model Routing API — LLM provider metrics and health."""
|
|
|
|
from fastapi import APIRouter
|
|
from typing import Any, Dict
|
|
|
|
from app.services.model_routing_dashboard import model_routing_dashboard
|
|
|
|
router = APIRouter(prefix="/model-routing", tags=["Model Routing"])
|
|
|
|
|
|
@router.get("/dashboard")
|
|
async def routing_dashboard() -> Dict[str, Any]:
|
|
"""Get model routing dashboard."""
|
|
return model_routing_dashboard.get_routing_stats("system")
|
|
|
|
|
|
@router.get("/health")
|
|
async def provider_health() -> Dict[str, Any]:
|
|
"""Get LLM provider health status."""
|
|
return {"providers": model_routing_dashboard.get_provider_health()}
|
|
|
|
|
|
@router.get("/costs")
|
|
async def routing_costs() -> Dict[str, Any]:
|
|
"""Get model routing cost attribution."""
|
|
return model_routing_dashboard.get_cost_summary("system")
|
|
|
|
|
|
@router.get("/recommendations")
|
|
async def routing_recommendations() -> Dict[str, Any]:
|
|
"""Get routing optimization recommendations."""
|
|
return {"recommendations": []}
|