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
142 lines
4.2 KiB
Python
142 lines
4.2 KiB
Python
"""Contradiction Engine — detects and tracks conflicts across the platform."""
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from __future__ import annotations
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from datetime import datetime, timezone
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from typing import Any, Dict, List, Optional
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from sqlalchemy import select, func
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from sqlalchemy.ext.asyncio import AsyncSession
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from app.models.contradiction import (
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Contradiction,
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ContradictionSeverity,
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ContradictionStatus,
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ContradictionType,
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)
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class ContradictionEngine:
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"""Manages contradiction lifecycle: detect → review → resolve."""
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async def register(
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self,
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db: AsyncSession,
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*,
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tenant_id: str,
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source_a: str,
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source_b: str,
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claim_a: str,
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claim_b: str,
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contradiction_type: str = "factual",
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severity: str = "medium",
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detected_by: str = "manual",
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evidence: Optional[Dict[str, Any]] = None,
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) -> Contradiction:
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contradiction = Contradiction(
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tenant_id=tenant_id,
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source_a=source_a,
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source_b=source_b,
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claim_a=claim_a,
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claim_b=claim_b,
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contradiction_type=ContradictionType(contradiction_type),
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severity=ContradictionSeverity(severity),
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status=ContradictionStatus.DETECTED,
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detected_by=detected_by,
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evidence=evidence or {},
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)
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db.add(contradiction)
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await db.commit()
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await db.refresh(contradiction)
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return contradiction
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async def get_active(
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self, db: AsyncSession, *, tenant_id: str
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) -> List[Contradiction]:
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stmt = (
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select(Contradiction)
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.where(Contradiction.tenant_id == tenant_id)
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.where(
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Contradiction.status.in_([
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ContradictionStatus.DETECTED,
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ContradictionStatus.REVIEWING,
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])
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)
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.order_by(Contradiction.created_at.desc())
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)
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result = await db.execute(stmt)
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return list(result.scalars().all())
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async def get_by_id(
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self, db: AsyncSession, *, tenant_id: str, contradiction_id: str
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) -> Optional[Contradiction]:
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stmt = (
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select(Contradiction)
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.where(Contradiction.tenant_id == tenant_id)
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.where(Contradiction.id == contradiction_id)
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)
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result = await db.execute(stmt)
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return result.scalar_one_or_none()
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async def resolve(
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self,
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db: AsyncSession,
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*,
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tenant_id: str,
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contradiction_id: str,
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resolution: str,
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resolved_by_id: str,
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status: str = "resolved",
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) -> Optional[Contradiction]:
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contradiction = await self.get_by_id(
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db, tenant_id=tenant_id, contradiction_id=contradiction_id
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)
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if not contradiction:
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return None
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contradiction.status = ContradictionStatus(status)
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contradiction.resolution = resolution
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contradiction.resolved_by_id = resolved_by_id
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contradiction.resolved_at = datetime.now(timezone.utc)
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await db.commit()
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await db.refresh(contradiction)
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return contradiction
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async def get_stats(
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self, db: AsyncSession, *, tenant_id: str
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) -> Dict[str, Any]:
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base = select(func.count()).where(Contradiction.tenant_id == tenant_id)
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total_result = await db.execute(base)
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total = total_result.scalar() or 0
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active_result = await db.execute(
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base.where(
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Contradiction.status.in_([
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ContradictionStatus.DETECTED,
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ContradictionStatus.REVIEWING,
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])
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)
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)
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active = active_result.scalar() or 0
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critical_result = await db.execute(
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base.where(Contradiction.severity == ContradictionSeverity.CRITICAL)
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.where(
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Contradiction.status.in_([
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ContradictionStatus.DETECTED,
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ContradictionStatus.REVIEWING,
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])
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)
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)
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critical = critical_result.scalar() or 0
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return {
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"total": total,
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"active": active,
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"resolved": total - active,
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"critical_active": critical,
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}
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contradiction_engine = ContradictionEngine()
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