mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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109 lines
3.1 KiB
Python
109 lines
3.1 KiB
Python
"""مستودع Proof Ledger — عمليات DB غير متزامنة."""
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from __future__ import annotations
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import uuid
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from datetime import UTC, datetime, timedelta
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from typing import Any
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from sqlalchemy import func, select
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from sqlalchemy.ext.asyncio import AsyncSession
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from db.models import ProofLedgerEventRecord
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def _iso_utc(dt: datetime | None) -> str:
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if not dt:
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return ""
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if dt.tzinfo is None:
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dt = dt.replace(tzinfo=UTC)
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return dt.isoformat()
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def _new_pl_id() -> str:
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return f"pl_{uuid.uuid4().hex[:20]}"
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async def proof_ledger_append(
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session: AsyncSession,
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*,
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tenant_id: str,
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event_type: str,
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revenue_influenced_sar_estimate: float,
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notes_ar: str,
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extra: dict[str, Any] | None = None,
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) -> dict[str, Any]:
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rec = ProofLedgerEventRecord(
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id=_new_pl_id(),
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tenant_id=tenant_id or "default",
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event_type=event_type,
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revenue_influenced_sar_estimate=float(revenue_influenced_sar_estimate),
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notes_ar=notes_ar or "",
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extra_json=extra or {},
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)
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session.add(rec)
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await session.flush()
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return {
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"id": rec.id,
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"tenant_id": rec.tenant_id,
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"event_type": rec.event_type,
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"revenue_influenced_sar_estimate": rec.revenue_influenced_sar_estimate,
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"notes_ar": rec.notes_ar,
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"extra_json": rec.extra_json,
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"created_at": _iso_utc(rec.created_at),
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}
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async def proof_ledger_list(
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session: AsyncSession,
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*,
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tenant_id: str,
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limit: int = 100,
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) -> list[dict[str, Any]]:
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q = (
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select(ProofLedgerEventRecord)
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.where(ProofLedgerEventRecord.tenant_id == tenant_id)
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.order_by(ProofLedgerEventRecord.created_at.desc())
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.limit(min(max(limit, 1), 500))
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)
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result = await session.execute(q)
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rows = result.scalars().all()
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out: list[dict[str, Any]] = []
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for r in rows:
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out.append(
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{
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"id": r.id,
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"event_type": r.event_type,
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"ts": _iso_utc(r.created_at),
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"revenue_influenced_sar_estimate": r.revenue_influenced_sar_estimate,
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"notes_ar": r.notes_ar,
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"extra_json": r.extra_json,
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}
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)
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return out
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async def proof_ledger_weekly_report(
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session: AsyncSession,
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*,
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tenant_id: str,
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) -> dict[str, Any]:
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since = datetime.now(tz=UTC) - timedelta(days=7)
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q = select(
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func.count(ProofLedgerEventRecord.id),
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func.coalesce(func.sum(ProofLedgerEventRecord.revenue_influenced_sar_estimate), 0.0),
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).where(
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ProofLedgerEventRecord.tenant_id == tenant_id,
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ProofLedgerEventRecord.created_at >= since,
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)
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result = await session.execute(q)
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row = result.one()
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count, total_est = int(row[0] or 0), float(row[1] or 0.0)
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return {
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"tenant_id": tenant_id,
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"window_days": 7,
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"event_count": count,
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"revenue_influenced_sar_estimate_sum": total_est,
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"disclaimer_ar": "تقديرات تشغيلية فقط — ليست إيرادات محققة أو مؤكدة محاسبياً.",
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}
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