mirror of
https://github.com/x1xhlol/system-prompts-and-models-of-ai-tools.git
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62 lines
2.2 KiB
Python
62 lines
2.2 KiB
Python
"""
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Account Timeline helpers — narrative renderers for UI + email digests.
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`render_timeline_markdown()` produces a human-readable Arabic timeline
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suitable for the customer's QBR or daily brief. The narrative is
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deterministic from the event stream → reproducible audit trail.
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"""
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from __future__ import annotations
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from datetime import datetime
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from typing import Any
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from auto_client_acquisition.revenue_memory.projections import AccountTimeline
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def render_timeline_markdown(timeline: AccountTimeline) -> str:
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"""Render an account timeline as a brief Arabic Markdown summary."""
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lines: list[str] = []
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lines.append(f"# Timeline — Account {timeline.account_id}")
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if timeline.first_seen:
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lines.append(f"**أول تفاعل:** {timeline.first_seen.date()}")
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if timeline.last_activity:
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lines.append(f"**آخر نشاط:** {timeline.last_activity.date()}")
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lines.append("")
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lines.append(
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f"**ملخص:** {timeline.n_messages_sent} رسالة · "
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f"{timeline.n_replies} رد · {timeline.n_meetings} اجتماع · "
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f"{timeline.n_signals} إشارة شراء"
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)
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lines.append("")
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lines.append("## التسلسل الزمني")
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if not timeline.entries:
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lines.append("_لا أحداث مسجلة بعد._")
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else:
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for entry in timeline.entries[-30:]: # last 30 events
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stamp = entry.occurred_at.strftime("%Y-%m-%d %H:%M")
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lines.append(f"- `{stamp}` — {entry.headline}")
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return "\n".join(lines)
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def timeline_to_dashboard_dict(timeline: AccountTimeline) -> dict[str, Any]:
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"""Compact dict for the Dashboard widget."""
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return {
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"account_id": timeline.account_id,
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"metrics": {
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"messages": timeline.n_messages_sent,
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"replies": timeline.n_replies,
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"meetings": timeline.n_meetings,
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"signals": timeline.n_signals,
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},
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"last_activity": timeline.last_activity.isoformat() if timeline.last_activity else None,
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"recent": [
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{
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"at": e.occurred_at.isoformat(),
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"type": e.event_type,
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"headline": e.headline,
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}
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for e in timeline.entries[-10:]
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],
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}
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