mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 15:29:36 +00:00
79 lines
2.4 KiB
Python
79 lines
2.4 KiB
Python
"""Audit page — live operational audit snapshot from health and admin endpoints."""
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from __future__ import annotations
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import os
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from typing import Any
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import httpx
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import pandas as pd
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import streamlit as st
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st.title("التدقيق التشغيلي")
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API = os.getenv("DEALIX_API_URL", "http://127.0.0.1:8001")
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API_KEY = os.getenv("DEALIX_ADMIN_API_KEY", "")
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def _headers() -> dict[str, str]:
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return {"X-API-Key": API_KEY} if API_KEY else {}
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def _get(path: str) -> Any:
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try:
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response = httpx.get(f"{API}{path}", headers=_headers(), timeout=8)
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return response.json() if response.status_code == 200 else {"error": response.status_code}
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except Exception as exc:
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return {"error": str(exc)}
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health = _get("/health/deep")
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costs = _get("/api/v1/admin/costs?window_hours=24")
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approvals = _get("/api/v1/admin/approvals/stats")
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dlq = _get("/api/v1/admin/dlq/stats")
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c1, c2, c3, c4 = st.columns(4)
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c1.metric("الحالة العامة", health.get("status", "?") if isinstance(health, dict) else "?")
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c2.metric(
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"الموافقات المعلقة",
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approvals.get("pending", 0) if isinstance(approvals, dict) else 0,
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)
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totals = costs.get("totals", {}) if isinstance(costs, dict) else {}
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c3.metric("إنفاق 24 ساعة", f"${totals.get('usd', 0)}")
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c4.metric(
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"عمق DLQ",
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(sum(queue.get("depth", 0) for queue in dlq.values()) if isinstance(dlq, dict) else 0),
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)
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st.subheader("فحوصات الصحة")
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checks = health.get("checks", {}) if isinstance(health, dict) else {}
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if checks:
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rows = []
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for name, info in checks.items():
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rows.append(
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{
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"check": name,
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"status": info.get("status"),
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"latency_ms": info.get("latency_ms", ""),
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"detail": info,
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}
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)
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st.dataframe(pd.DataFrame(rows), use_container_width=True, hide_index=True)
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else:
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st.info("لا توجد بيانات صحة متاحة حالياً.")
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st.subheader("ملخص طوابير الفشل")
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if isinstance(dlq, dict) and dlq:
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rows = []
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for queue_name, info in dlq.items():
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rows.append(
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{
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"queue": queue_name,
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"depth": info.get("depth", 0),
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"last_error": info.get("last_error", ""),
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}
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)
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st.dataframe(pd.DataFrame(rows), use_container_width=True, hide_index=True)
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else:
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st.info("لا توجد بيانات DLQ متاحة حالياً.")
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