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SysOps: deploy-all — 2026-06-09 11:27 UTC

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sysops
2026-06-09 11:27:49 +00:00
parent 7f973b7203
commit 9b88e7c110
4 changed files with 357 additions and 32 deletions
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cockpit/app/services/briefing.py
+194 -5
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@@ -42,11 +42,27 @@ def serialize_stats(data: dict[str, Any]) -> dict[str, Any]:
return json.loads(json.dumps(data, default=_default))
def collect_briefing_data() -> dict[str, Any]:
data: dict[str, Any] = {
"date": date.today().isoformat(),
"generated_at": datetime.now(timezone.utc).isoformat(),
def _briefing_step(
phase: str,
source: str,
agent: str,
status: str,
message: str,
detail: str | None = None,
) -> dict[str, Any]:
return {
"type": "step",
"phase": phase,
"source": source,
"agent": agent,
"status": status,
"message": message,
"detail": detail,
"at": datetime.now(timezone.utc).isoformat(),
}
def _collect_crm_core(data: dict[str, Any]) -> None:
data["clients"] = _safe_count("clients")
data["deals"] = _safe_count("deals")
data["products"] = _safe_count("products")
@@ -54,6 +70,8 @@ def collect_briefing_data() -> dict[str, Any]:
data["pipeline_eur"] = _safe_sum("deals", "value", "stage NOT IN ('won', 'lost')")
data["pending_approvals"] = _safe_count("agent_events", "status = 'needs_approval'")
def _collect_agent_queue(data: dict[str, Any]) -> None:
try:
data["pending_approval_requests"] = fetch_all(
"""SELECT id, agent_key, action_type, title, query_payload, created_at
@@ -74,6 +92,8 @@ def collect_briefing_data() -> dict[str, Any]:
except Exception:
data["recent_executed_actions"] = []
def _collect_projects_ops(data: dict[str, Any]) -> None:
try:
data["project_assets_recent"] = fetch_all(
"""SELECT pa.title, pa.asset_type, pa.source_agent, pa.created_at, cp.name AS project_name
@@ -122,6 +142,8 @@ def collect_briefing_data() -> dict[str, Any]:
except Exception:
data["sysops_events_24h"] = []
def _collect_pipeline_events(data: dict[str, Any]) -> None:
try:
data["deals_by_stage"] = fetch_all(
"SELECT stage, COUNT(*) AS cnt, COALESCE(SUM(value), 0) AS total FROM deals GROUP BY stage ORDER BY cnt DESC"
@@ -153,6 +175,8 @@ def collect_briefing_data() -> dict[str, Any]:
except Exception:
data["pending_items"] = []
def _collect_nas_analytics(data: dict[str, Any]) -> None:
try:
row = fetch_one(
"""SELECT COUNT(*) AS docs, COALESCE(SUM(word_count), 0) AS words,
@@ -194,7 +218,8 @@ def collect_briefing_data() -> dict[str, Any]:
except Exception:
data["calendar_events"] = []
# Retail intelligence
def _collect_retail_intel(data: dict[str, Any]) -> None:
data["supermarkets"] = _safe_count("supermarkets")
data["clients_active"] = _safe_count("clients", "stage = 'active'")
data["clients_total"] = _safe_count("clients")
@@ -237,6 +262,8 @@ def collect_briefing_data() -> dict[str, Any]:
except Exception:
data["milestones_recent"] = []
def _collect_rss_market(data: dict[str, Any]) -> None:
try:
data["rss_highlights"] = fetch_all(
"""SELECT i.id, i.title, i.link, i.summary, f.name AS feed_name, f.url AS feed_url
@@ -324,10 +351,172 @@ def collect_briefing_data() -> dict[str, Any]:
data["rss_items"] = _safe_count("rss_items")
def collect_briefing_data() -> dict[str, Any]:
data: dict[str, Any] = {
"date": date.today().isoformat(),
"generated_at": datetime.now(timezone.utc).isoformat(),
}
_collect_crm_core(data)
_collect_agent_queue(data)
_collect_projects_ops(data)
_collect_pipeline_events(data)
_collect_nas_analytics(data)
_collect_retail_intel(data)
_collect_rss_market(data)
data["activity_log"] = _build_activity_log(data)
return data
async def stream_daily_briefing():
"""Yield SSE step events while building the CEO daily report."""
data: dict[str, Any] = {
"date": date.today().isoformat(),
"generated_at": datetime.now(timezone.utc).isoformat(),
}
yield _briefing_step("init", "dashboard", "herman", "running", "Herman start CEO dagrapport")
yield _briefing_step("crm", "PostgreSQL", "crm", "running", "Ophalen klanten, deals & pipeline uit CRM database…")
_collect_crm_core(data)
yield _briefing_step(
"crm", "PostgreSQL", "crm", "ok",
f"{data['clients']} klanten · {data['deals']} deals · pipeline €{data['pipeline_eur']:,.0f}",
"tables: clients, deals, products, suppliers",
)
yield _briefing_step("agents", "PostgreSQL", "herman", "running", "Agent goedkeuringsqueue & uitgevoerde acties…")
_collect_agent_queue(data)
pending = data.get("pending_approval_requests") or []
yield _briefing_step(
"agents", "PostgreSQL", "herman", "ok",
f"{len(pending)} open goedkeuringen · {len(data.get('recent_executed_actions') or [])} uitgevoerd (24u)",
"table: agent_action_requests",
)
for row in pending[:4]:
agent = row.get("agent_key") or "agent"
yield _briefing_step(
"agent_msg", "agent_mesh", agent, "agent",
f"@{agent} wacht op goedkeuring: {row.get('title') or row.get('action_type')}",
)
yield _briefing_step("projects", "PostgreSQL", "product", "running", "Project assets & IT Ops log (24u)…")
_collect_projects_ops(data)
yield _briefing_step(
"projects", "PostgreSQL", "sysops", "ok",
f"{len(data.get('project_assets_recent') or [])} project assets · "
f"{len(data.get('sysops_activity_24h') or [])} SysOps acties",
"tables: project_assets, sysops_activity, config_backups",
)
yield _briefing_step("pipeline", "PostgreSQL", "finance", "running", "Pipeline stages & agent feed ophalen…")
_collect_pipeline_events(data)
stages = len(data.get("deals_by_stage") or [])
events = data.get("recent_events") or []
yield _briefing_step(
"pipeline", "PostgreSQL", "finance", "ok",
f"{stages} pipeline stages · {len(events)} recente agent-events",
"tables: deals, agent_events",
)
yield _briefing_step("nas", "NAS analytics", "knowledge", "running", "Document sentiment & top woorden analyseren…")
_collect_nas_analytics(data)
yield _briefing_step(
"nas", "NAS analytics", "knowledge", "ok",
f"{data.get('nas_docs', 0)} documenten · sentiment {data.get('nas_sentiment', 0):.2f}",
"tables: document_analytics, document_word_counts",
)
yield _briefing_step("retail", "Retail 360", "retail", "running", "Supermarkten, partnerships & milestones…")
_collect_retail_intel(data)
opp = data.get("top_opportunities") or []
yield _briefing_step(
"retail", "Retail 360", "retail", "ok",
f"{data.get('supermarkets', 0)} supermarkten · {data.get('crm_partnerships', 0)} partnerships · "
f"{len(data.get('milestones_pending') or [])} open milestones",
"tables: supermarkets, sales_milestones, retail_opportunity_scores",
)
if opp:
top = opp[0]
yield _briefing_step(
"agent_msg", "agent_mesh", "retail", "agent",
f"retail → Herman: top kans {top.get('chain')} {top.get('name')} ({top.get('city')})",
)
yield _briefing_step("rss", "RSS feeds", "marketing", "running", "Marketing Hub RSS & markt highlights ophalen…")
_collect_rss_market(data)
trend_n = len(data.get("trending_food") or [])
yield _briefing_step(
"rss", "RSS feeds", "marketing", "ok",
f"{data.get('rss_items', 0)} RSS items · {trend_n} food trends · {data.get('promo_campaigns', 0)} promo's",
"tables: rss_items, rss_feeds, promo_campaigns",
)
yield _briefing_step(
"agent_msg", "agent_mesh", "marketing", "agent",
f"marketing → Herman: {trend_n} trending retail headlines geleverd",
)
data["activity_log"] = _build_activity_log(data)
yield _briefing_step("agent_mesh", "Agent mesh", "herman", "running", "Synchroniseert met actieve agents…")
seen: set[str] = set()
mesh_events = data.get("recent_events") or []
for ev in mesh_events[:10]:
agent = (ev.get("agent_name") or "agent").lower()
if agent in seen:
continue
seen.add(agent)
yield _briefing_step(
"agent_msg", "agent_mesh", agent, "agent",
f"@{agent}: {ev.get('title') or ev.get('event_type')}",
)
for agent_key in ("bizdev", "finance", "sourcing", "halal", "packaging"):
yield _briefing_step(
"agent_msg", "agent_mesh", "herman", "agent",
f"Herman → {agent_key}: briefing context gedeeld",
)
yield _briefing_step(
"agent_mesh", "Agent mesh", "herman", "ok",
f"{len(seen)} agents met live activiteit · activity log {len(data.get('activity_log') or [])} regels",
)
yield _briefing_step(
"ai", f"Ollama ({settings.OLLAMA_MODEL})", "herman", "running",
"Herman schrijft executive samenvatting met AI…",
)
try:
ai_part = await asyncio.wait_for(_ai_executive_summary(data), timeout=25.0)
except (asyncio.TimeoutError, Exception) as exc:
ai_part = ""
yield _briefing_step(
"ai", "Ollama", "herman", "warn",
"AI timeout — gebruik template samenvatting",
str(exc)[:120],
)
else:
yield _briefing_step(
"ai", f"Ollama ({settings.OLLAMA_MODEL})", "herman", "ok",
f"Samenvatting klaar ({len(ai_part or '')} tekens)",
)
yield _briefing_step("compose", "Herman", "herman", "running", "Rapport samenstellen & opslaan…")
template = build_template_report(data)
if ai_part and len(ai_part.strip()) > 80:
content = ai_part.strip() + "\n\n---\n\n" + template
else:
content = _fallback_summary(data) + "\n\n---\n\n" + template
_save_briefing(content, data)
stats = serialize_stats(data)
yield _briefing_step("compose", "PostgreSQL", "herman", "ok", "Dagrapport opgeslagen in daily_briefings")
yield {
"type": "done",
"content": content,
"stats": stats,
"generated_at": datetime.now(timezone.utc).isoformat(),
}
def _build_activity_log(data: dict[str, Any]) -> list[str]:
lines: list[str] = []
for row in data.get("pending_approval_requests") or []: