feat(awooop): show callback gap freshness
This commit is contained in:
@@ -120,7 +120,13 @@ class CallbackReplyAuditSummary(BaseModel):
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outbound_incident_ref_total: int
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outbound_reply_markup_total: int = 0
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outbound_reply_markup_missing_incident_ref_total: int = 0
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outbound_reply_markup_missing_incident_ref_recent_1h_total: int = 0
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outbound_reply_markup_missing_incident_ref_recent_24h_total: int = 0
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outbound_reply_markup_missing_incident_ref_latest_sent_at: datetime | None = None
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outbound_reply_markup_missing_trace_ref_total: int = 0
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outbound_reply_markup_missing_trace_ref_recent_1h_total: int = 0
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outbound_reply_markup_missing_trace_ref_recent_24h_total: int = 0
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outbound_reply_markup_missing_trace_ref_latest_sent_at: datetime | None = None
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outbound_reply_markup_missing_incident_ref_top_prefixes: list[
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OutboundReplyMarkupGapPrefix
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] = Field(default_factory=list)
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@@ -527,10 +527,47 @@ async def _fetch_callback_reply_audit_summary(
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'[]'::jsonb
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) = '[]'::jsonb
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) AS outbound_reply_markup_missing_incident_ref_total,
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COUNT(*) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND COALESCE(
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source_envelope #> '{source_refs,incident_ids}',
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'[]'::jsonb
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) = '[]'::jsonb
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AND COALESCE(sent_at, queued_at) >= NOW() - INTERVAL '1 hour'
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) AS outbound_reply_markup_missing_incident_ref_recent_1h_total,
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COUNT(*) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND COALESCE(
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source_envelope #> '{source_refs,incident_ids}',
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'[]'::jsonb
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) = '[]'::jsonb
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AND COALESCE(sent_at, queued_at) >= NOW() - INTERVAL '24 hours'
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) AS outbound_reply_markup_missing_incident_ref_recent_24h_total,
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MAX(COALESCE(sent_at, queued_at)) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND COALESCE(
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source_envelope #> '{source_refs,incident_ids}',
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'[]'::jsonb
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) = '[]'::jsonb
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) AS outbound_reply_markup_missing_incident_ref_latest_sent_at,
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COUNT(*) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND NOT has_trace_ref
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) AS outbound_reply_markup_missing_trace_ref_total,
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COUNT(*) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND NOT has_trace_ref
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AND COALESCE(sent_at, queued_at) >= NOW() - INTERVAL '1 hour'
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) AS outbound_reply_markup_missing_trace_ref_recent_1h_total,
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COUNT(*) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND NOT has_trace_ref
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AND COALESCE(sent_at, queued_at) >= NOW() - INTERVAL '24 hours'
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) AS outbound_reply_markup_missing_trace_ref_recent_24h_total,
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MAX(COALESCE(sent_at, queued_at)) FILTER (
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WHERE source_envelope #>> '{reply_markup,present}' = 'true'
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AND NOT has_trace_ref
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) AS outbound_reply_markup_missing_trace_ref_latest_sent_at,
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COALESCE((
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SELECT jsonb_agg(
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jsonb_build_object(
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@@ -739,9 +776,27 @@ def _callback_reply_audit_summary_from_row(
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"outbound_reply_markup_missing_incident_ref_total": _safe_int(
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row.get("outbound_reply_markup_missing_incident_ref_total")
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),
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"outbound_reply_markup_missing_incident_ref_recent_1h_total": _safe_int(
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row.get("outbound_reply_markup_missing_incident_ref_recent_1h_total")
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),
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"outbound_reply_markup_missing_incident_ref_recent_24h_total": _safe_int(
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row.get("outbound_reply_markup_missing_incident_ref_recent_24h_total")
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),
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"outbound_reply_markup_missing_incident_ref_latest_sent_at": row.get(
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"outbound_reply_markup_missing_incident_ref_latest_sent_at"
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),
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"outbound_reply_markup_missing_trace_ref_total": _safe_int(
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row.get("outbound_reply_markup_missing_trace_ref_total")
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),
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"outbound_reply_markup_missing_trace_ref_recent_1h_total": _safe_int(
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row.get("outbound_reply_markup_missing_trace_ref_recent_1h_total")
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),
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"outbound_reply_markup_missing_trace_ref_recent_24h_total": _safe_int(
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row.get("outbound_reply_markup_missing_trace_ref_recent_24h_total")
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),
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"outbound_reply_markup_missing_trace_ref_latest_sent_at": row.get(
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"outbound_reply_markup_missing_trace_ref_latest_sent_at"
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),
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"outbound_reply_markup_missing_incident_ref_top_prefixes": (
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top_missing_prefixes
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),
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@@ -670,7 +670,17 @@ def test_list_callback_replies_response_preserves_callback_evidence() -> None:
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"outbound_incident_ref_total": 80,
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"outbound_reply_markup_total": 30,
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"outbound_reply_markup_missing_incident_ref_total": 4,
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"outbound_reply_markup_missing_incident_ref_recent_1h_total": 1,
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"outbound_reply_markup_missing_incident_ref_recent_24h_total": 2,
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"outbound_reply_markup_missing_incident_ref_latest_sent_at": (
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datetime(2026, 5, 18, 8, 15, 0)
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),
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"outbound_reply_markup_missing_trace_ref_total": 2,
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"outbound_reply_markup_missing_trace_ref_recent_1h_total": 0,
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"outbound_reply_markup_missing_trace_ref_recent_24h_total": 1,
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"outbound_reply_markup_missing_trace_ref_latest_sent_at": (
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datetime(2026, 5, 18, 7, 40, 0)
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),
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"outbound_reply_markup_missing_incident_ref_top_prefixes": [
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{
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"prefix": "silence",
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@@ -732,7 +742,19 @@ def test_list_callback_replies_response_preserves_callback_evidence() -> None:
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assert dumped["summary"]["outbound_trace_ref_total"] == 92
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assert dumped["summary"]["outbound_reply_markup_total"] == 30
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assert dumped["summary"]["outbound_reply_markup_missing_incident_ref_total"] == 4
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assert dumped["summary"][
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"outbound_reply_markup_missing_incident_ref_recent_1h_total"
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] == 1
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assert dumped["summary"][
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"outbound_reply_markup_missing_incident_ref_latest_sent_at"
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] == "2026-05-18T08:15:00"
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assert dumped["summary"]["outbound_reply_markup_missing_trace_ref_total"] == 2
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assert dumped["summary"][
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"outbound_reply_markup_missing_trace_ref_recent_24h_total"
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] == 1
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assert dumped["summary"][
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"outbound_reply_markup_missing_trace_ref_latest_sent_at"
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] == "2026-05-18T07:40:00"
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assert dumped["summary"][
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"outbound_reply_markup_missing_incident_ref_top_prefixes"
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][0] == {
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@@ -774,7 +796,17 @@ def test_callback_reply_audit_summary_marks_missing_snapshots() -> None:
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"outbound_incident_ref_total": 3200,
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"outbound_reply_markup_total": 100,
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"outbound_reply_markup_missing_incident_ref_total": 12,
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"outbound_reply_markup_missing_incident_ref_recent_1h_total": 2,
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"outbound_reply_markup_missing_incident_ref_recent_24h_total": 3,
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"outbound_reply_markup_missing_incident_ref_latest_sent_at": (
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datetime(2026, 5, 25, 8, 42, 22)
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),
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"outbound_reply_markup_missing_trace_ref_total": 5,
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"outbound_reply_markup_missing_trace_ref_recent_1h_total": 1,
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"outbound_reply_markup_missing_trace_ref_recent_24h_total": 2,
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"outbound_reply_markup_missing_trace_ref_latest_sent_at": (
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datetime(2026, 5, 25, 8, 42, 22)
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),
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"outbound_reply_markup_missing_incident_ref_top_prefixes": [
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{
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"prefix": "silence",
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@@ -819,6 +851,14 @@ def test_callback_reply_audit_summary_marks_missing_snapshots() -> None:
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assert summary["outbound_total"] == 5256
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assert summary["outbound_trace_ref_total"] == 4300
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assert summary["outbound_reply_markup_missing_trace_ref_total"] == 5
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assert summary["outbound_reply_markup_missing_trace_ref_recent_1h_total"] == 1
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assert summary["outbound_reply_markup_missing_trace_ref_recent_24h_total"] == 2
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assert summary["outbound_reply_markup_missing_trace_ref_latest_sent_at"] == (
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datetime(2026, 5, 25, 8, 42, 22)
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)
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assert summary[
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"outbound_reply_markup_missing_incident_ref_recent_24h_total"
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] == 3
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assert summary["outbound_reply_markup_missing_trace_ref_top_prefixes"][0][
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"prefix"
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] == "unknown"
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@@ -844,7 +884,17 @@ def test_callback_reply_audit_summary_marks_mixed_legacy_snapshots_partial() ->
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"outbound_incident_ref_total": 920,
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"outbound_reply_markup_total": 1322,
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"outbound_reply_markup_missing_incident_ref_total": 684,
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"outbound_reply_markup_missing_incident_ref_recent_1h_total": 0,
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"outbound_reply_markup_missing_incident_ref_recent_24h_total": 0,
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"outbound_reply_markup_missing_incident_ref_latest_sent_at": (
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datetime(2026, 5, 25, 10, 59, 49)
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),
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"outbound_reply_markup_missing_trace_ref_total": 154,
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"outbound_reply_markup_missing_trace_ref_recent_1h_total": 0,
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"outbound_reply_markup_missing_trace_ref_recent_24h_total": 23,
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"outbound_reply_markup_missing_trace_ref_latest_sent_at": (
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datetime(2026, 5, 25, 12, 13, 1)
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),
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"outbound_reply_markup_missing_incident_ref_top_prefixes": [
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{
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"prefix": "silence",
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@@ -894,6 +944,11 @@ def test_callback_reply_audit_summary_marks_mixed_legacy_snapshots_partial() ->
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assert summary["callback_snapshot_captured_total"] == 1
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assert summary["outbound_trace_ref_total"] == 4230
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assert summary["outbound_reply_markup_missing_trace_ref_total"] == 154
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assert summary["outbound_reply_markup_missing_trace_ref_recent_1h_total"] == 0
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assert summary["outbound_reply_markup_missing_trace_ref_recent_24h_total"] == 23
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assert summary["outbound_reply_markup_missing_trace_ref_latest_sent_at"] == (
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datetime(2026, 5, 25, 12, 13, 1)
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)
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assert summary["outbound_reply_markup_missing_trace_ref_top_prefixes"][0][
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"recent_24h_total"
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] == 23
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@@ -3060,6 +3060,8 @@
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"outbound": "Outbound mirror",
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"outboundDetail": "source_refs {sourceRefs}; trace refs {traceRefs}; incident refs {incidentRefs}; coverage {coverage}",
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"outboundReplyMarkupDetail": "reply_markup {replyMarkup}; missing trace refs {missingTraceRefs}; missing incident refs {missingIncidentRefs}",
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"outboundReplyMarkupTraceFreshness": "Missing trace activity: 1h {recent1h} / 24h {recent24h} / latest {latest}",
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"outboundReplyMarkupIncidentFreshness": "Missing incident activity: 1h {recent1h} / 24h {recent24h} / latest {latest}",
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"outboundReplyMarkupTopPrefixes": "Missing incident top prefixes: {prefixes}",
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"outboundReplyMarkupTraceTopPrefixes": "Missing trace top prefixes: {prefixes}",
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"outboundReplyMarkupTopPrefixItem": "{prefix} {total} (24h {recent}, last {last})",
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@@ -3061,6 +3061,8 @@
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"outbound": "出站鏡像",
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"outboundDetail": "source_refs {sourceRefs};trace refs {traceRefs};incident refs {incidentRefs};覆蓋 {coverage}",
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"outboundReplyMarkupDetail": "reply_markup {replyMarkup};缺 trace refs {missingTraceRefs};缺 incident refs {missingIncidentRefs}",
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"outboundReplyMarkupTraceFreshness": "缺 trace 活躍度:1h {recent1h} / 24h {recent24h} / 最新 {latest}",
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"outboundReplyMarkupIncidentFreshness": "缺 incident 活躍度:1h {recent1h} / 24h {recent24h} / 最新 {latest}",
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"outboundReplyMarkupTopPrefixes": "缺 incident top prefixes:{prefixes}",
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"outboundReplyMarkupTraceTopPrefixes": "缺 trace top prefixes:{prefixes}",
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"outboundReplyMarkupTopPrefixItem": "{prefix} {total}(24h {recent},最後 {last})",
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@@ -153,7 +153,13 @@ interface CallbackReplyAuditSummary {
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outbound_incident_ref_total?: number;
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outbound_reply_markup_total?: number;
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outbound_reply_markup_missing_incident_ref_total?: number;
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outbound_reply_markup_missing_incident_ref_recent_1h_total?: number;
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outbound_reply_markup_missing_incident_ref_recent_24h_total?: number;
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outbound_reply_markup_missing_incident_ref_latest_sent_at?: string | null;
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outbound_reply_markup_missing_trace_ref_total?: number;
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outbound_reply_markup_missing_trace_ref_recent_1h_total?: number;
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outbound_reply_markup_missing_trace_ref_recent_24h_total?: number;
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outbound_reply_markup_missing_trace_ref_latest_sent_at?: string | null;
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outbound_reply_markup_missing_incident_ref_top_prefixes?: Array<{
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prefix?: string | null;
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total?: number | null;
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@@ -2476,6 +2482,15 @@ function CallbackReplyAuditSummaryPanel({
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summary.outbound_trace_ref_total ?? summary.outbound_incident_ref_total ?? 0,
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outboundTotal
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);
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const formatShortDateTime = (value?: string | null) =>
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value
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? new Date(value).toLocaleString("zh-TW", {
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month: "2-digit",
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day: "2-digit",
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hour: "2-digit",
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minute: "2-digit",
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})
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: "--";
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const formatPrefixGaps = (
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items?: Array<{
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prefix?: string | null;
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@@ -2487,19 +2502,11 @@ function CallbackReplyAuditSummaryPanel({
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items ?? []
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).slice(0, 3)
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.map((item) => {
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const lastSeen = item.last_sent_at
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? new Date(item.last_sent_at).toLocaleString("zh-TW", {
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month: "2-digit",
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day: "2-digit",
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hour: "2-digit",
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minute: "2-digit",
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})
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: "--";
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return t("outboundReplyMarkupTopPrefixItem", {
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prefix: item.prefix || "--",
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total: item.total ?? 0,
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recent: item.recent_24h_total ?? 0,
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last: lastSeen,
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last: formatShortDateTime(item.last_sent_at),
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});
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})
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.join(" / ") || "--";
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@@ -2513,14 +2520,13 @@ function CallbackReplyAuditSummaryPanel({
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summary.callback_snapshot_captured_total ?? 0,
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callbackTotal
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);
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const latestCallback = summary.latest_callback_at
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? new Date(summary.latest_callback_at).toLocaleString("zh-TW", {
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month: "2-digit",
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day: "2-digit",
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hour: "2-digit",
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minute: "2-digit",
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})
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: "--";
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const latestCallback = formatShortDateTime(summary.latest_callback_at);
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const latestMissingTraceRef = formatShortDateTime(
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summary.outbound_reply_markup_missing_trace_ref_latest_sent_at
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);
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const latestMissingIncidentRef = formatShortDateTime(
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summary.outbound_reply_markup_missing_incident_ref_latest_sent_at
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);
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const snapshotClass = {
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captured: "border-[#9bc7a4] bg-[#f0faf2] text-[#17602a]",
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partial: "border-[#d9b36f] bg-[#fff7e8] text-[#8a5a08]",
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@@ -2556,6 +2562,30 @@ function CallbackReplyAuditSummaryPanel({
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summary.outbound_reply_markup_missing_trace_ref_total ?? 0,
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})}
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</p>
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<p className="mt-1 text-xs leading-5 text-[#5f5b52]">
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{t("outboundReplyMarkupTraceFreshness", {
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recent1h:
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summary.outbound_reply_markup_missing_trace_ref_recent_1h_total ??
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0,
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recent24h:
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summary.outbound_reply_markup_missing_trace_ref_recent_24h_total ??
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0,
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latest: latestMissingTraceRef,
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})}
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</p>
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<p className="mt-1 text-xs leading-5 text-[#5f5b52]">
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{t("outboundReplyMarkupIncidentFreshness", {
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recent1h:
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summary
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.outbound_reply_markup_missing_incident_ref_recent_1h_total ??
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0,
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recent24h:
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summary
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.outbound_reply_markup_missing_incident_ref_recent_24h_total ??
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0,
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latest: latestMissingIncidentRef,
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})}
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</p>
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<p className="mt-1 text-xs leading-5 text-[#5f5b52]">
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{t("outboundReplyMarkupTraceTopPrefixes", {
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prefixes: topMissingTracePrefixes,
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@@ -21217,3 +21217,72 @@ GET /api/v1/health
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- KM governance:約 84.6%。
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- AI Provider lane visibility:約 92.2%。
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- 完整 AI 自動化管理產品化:約 97.85%。
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### 2026-05-25 — T192 Callback gap freshness(pre-deploy)
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**背景**:T191 已把缺 trace refs 與缺 incident refs 的 top prefixes 分開,但
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operator 仍只看到累積總數,例如 `missing_trace_ref_total = 417`,無法立即判斷
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它是歷史債還是 deploy 後仍在新增。T192 增加 freshness metrics,讓前端同時顯示
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1h / 24h / latest sent time。
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**完成變更**:
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- `/api/v1/platform/runs/callback-replies` summary 新增:
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- `outbound_reply_markup_missing_trace_ref_recent_1h_total`
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- `outbound_reply_markup_missing_trace_ref_recent_24h_total`
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- `outbound_reply_markup_missing_trace_ref_latest_sent_at`
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- `outbound_reply_markup_missing_incident_ref_recent_1h_total`
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- `outbound_reply_markup_missing_incident_ref_recent_24h_total`
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- `outbound_reply_markup_missing_incident_ref_latest_sent_at`
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- AwoooP Runs / TG Callback Evidence 前端新增:
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- 缺 trace 活躍度:1h / 24h / 最新
|
||||
- 缺 incident 活躍度:1h / 24h / 最新
|
||||
- 測試補上 Pydantic response serialization 與 service row mapping。
|
||||
|
||||
**local validation(完成)**:
|
||||
|
||||
```text
|
||||
python3 -m py_compile apps/api/src/services/platform_operator_service.py apps/api/src/api/v1/platform/operator_runs.py apps/api/tests/test_awooop_operator_timeline_labels.py
|
||||
jq empty apps/web/messages/zh-TW.json apps/web/messages/en.json
|
||||
PYTHONPATH=. DATABASE_URL='postgresql+asyncpg://test:test@localhost/test' /Users/ogt/.pyenv/shims/pytest apps/api/tests/test_awooop_operator_timeline_labels.py -q
|
||||
53 passed in 0.88s
|
||||
pnpm --dir apps/web exec tsc --noEmit --tsBuildInfoFile /tmp/awoooi-t192-tsconfig.tsbuildinfo
|
||||
pass
|
||||
pnpm --dir apps/web lint -- --file 'src/app/[locale]/awooop/runs/page.tsx'
|
||||
pass with pre-existing i18next/no-literal-string and unused icon warnings
|
||||
NEXT_PUBLIC_API_URL=https://awoooi.wooo.work pnpm --dir apps/web run build
|
||||
pass; Sentry global-error / instrumentation-client warnings are pre-existing
|
||||
git diff --check
|
||||
pass
|
||||
```
|
||||
|
||||
**production SQL dry-run(完成,read-only)**:
|
||||
|
||||
> 注意:`awooop_outbound_message` 有 RLS。直接用 `DATABASE_URL` 查詢時若未先
|
||||
> `set_config('app.project_id', 'awoooi', true)`,會正確隔離成 0 筆。API path
|
||||
> 經由 `get_db_context()` 會自動設定 tenant context。
|
||||
|
||||
```text
|
||||
missing_trace_total = 417
|
||||
missing_trace_recent_1h_total = 0
|
||||
missing_trace_recent_24h_total = 43
|
||||
missing_trace_latest_sent_at = 2026-05-25 12:13:01.534615
|
||||
missing_incident_total = 684
|
||||
missing_incident_recent_1h_total = 0
|
||||
missing_incident_recent_24h_total = 43
|
||||
missing_incident_latest_sent_at = 2026-05-25 12:13:01.534615
|
||||
```
|
||||
|
||||
**目前整體進度(pre-deploy)**:
|
||||
|
||||
- AwoooP 告警可觀測鏈:約 99.78%。
|
||||
- 低風險自動修復閉環:約 95.8%。
|
||||
- 前端 AI 自動化管理介面同步:約 99.65%。
|
||||
- Telegram outbound / callback DB coverage 可視化:約 99.75%。
|
||||
- callback / DB replayability:約 98.75%。
|
||||
- MCP / 自建 MCP 可視化:約 95.1%。
|
||||
- Sentry / SigNoz source correlation:約 94.5%。
|
||||
- Ansible / PlayBook 可視化:約 92.6%。
|
||||
- KM governance:約 84.6%。
|
||||
- AI Provider lane visibility:約 92.2%。
|
||||
- 完整 AI 自動化管理產品化:約 97.9%。
|
||||
|
||||
Reference in New Issue
Block a user