mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
synced 2026-06-18 15:29:36 +00:00
82 lines
2.4 KiB
Python
82 lines
2.4 KiB
Python
"""Evidence page — governance evidence from live approvals and DLQ state."""
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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("الدليل 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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approval_stats = _get("/api/v1/admin/approvals/stats")
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pending = _get("/api/v1/admin/approvals/pending")
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dlq_stats = _get("/api/v1/admin/dlq/stats")
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c1, c2 = st.columns(2)
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c1.metric(
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"موافقات معلقة",
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approval_stats.get("pending", 0) if isinstance(approval_stats, dict) else 0,
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)
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c2.metric(
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"إجمالي عناصر DLQ",
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(
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sum(queue.get("depth", 0) for queue in dlq_stats.values())
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if isinstance(dlq_stats, dict)
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else 0
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),
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)
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st.subheader("الأدلة الحالية على القرارات المعلقة")
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items = pending.get("items", []) if isinstance(pending, dict) else []
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if items:
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rows = []
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for item in items:
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rows.append(
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{
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"id": item.get("id"),
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"action": item.get("action"),
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"requested_by": item.get("requested_by"),
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"risk_score": item.get("risk_score"),
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"reason": item.get("reason"),
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"requested_at": item.get("requested_at"),
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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 قرارات معلقة حالياً.")
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st.subheader("حالة طوابير الفشل")
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if isinstance(dlq_stats, dict) and dlq_stats:
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rows = []
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for queue_name, stats in dlq_stats.items():
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rows.append(
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{
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"queue": queue_name,
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"depth": stats.get("depth", 0),
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"last_error": stats.get("last_error", ""),
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"last_seen_at": stats.get("last_seen_at", ""),
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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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