Platform bundle: marketing publish, IT ops, packaging, agents mesh.
Volledige Foodlinkk Command Center uitbreiding met social automatisering, reclamefolder filters, Proxmox monitoring en documentatie.
This commit is contained in:
Aissa
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from __future__ import annotations
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import asyncio
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import json
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from datetime import date, datetime, timezone
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from typing import Any
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from app.config import settings
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from app.db import execute, fetch_all, fetch_one
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from app.services import ollama
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def _safe_count(table: str, where: str = "", params: tuple = ()) -> int:
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try:
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clause = f" WHERE {where}" if where else ""
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row = fetch_one(f"SELECT COUNT(*) AS c FROM {table}{clause}", params or None)
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return int(row["c"]) if row else 0
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except Exception:
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return 0
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def _safe_sum(table: str, column: str, where: str = "", params: tuple = ()) -> float:
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try:
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clause = f" WHERE {where}" if where else ""
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row = fetch_one(f"SELECT COALESCE(SUM({column}), 0) AS total FROM {table}{clause}", params or None)
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return float(row["total"]) if row else 0.0
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except Exception:
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return 0.0
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def serialize_stats(data: dict[str, Any]) -> dict[str, Any]:
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def _default(o: Any) -> Any:
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if hasattr(o, "isoformat"):
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return o.isoformat()
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if hasattr(o, "__float__"):
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try:
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return float(o)
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except (TypeError, ValueError):
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pass
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return str(o)
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return json.loads(json.dumps(data, default=_default))
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def collect_briefing_data() -> dict[str, Any]:
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data: dict[str, Any] = {
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"date": date.today().isoformat(),
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"generated_at": datetime.now(timezone.utc).isoformat(),
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}
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data["clients"] = _safe_count("clients")
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data["deals"] = _safe_count("deals")
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data["products"] = _safe_count("products")
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data["suppliers"] = _safe_count("suppliers")
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data["pipeline_eur"] = _safe_sum("deals", "value", "stage NOT IN ('won', 'lost')")
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data["pending_approvals"] = _safe_count("agent_events", "status = 'needs_approval'")
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try:
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data["deals_by_stage"] = fetch_all(
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"SELECT stage, COUNT(*) AS cnt, COALESCE(SUM(value), 0) AS total FROM deals GROUP BY stage ORDER BY cnt DESC"
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)
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except Exception:
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data["deals_by_stage"] = []
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try:
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data["recent_clients"] = fetch_all(
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"SELECT name, stage, email, created_at FROM clients ORDER BY created_at DESC LIMIT 5"
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)
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except Exception:
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data["recent_clients"] = []
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try:
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data["recent_events"] = fetch_all(
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"""SELECT agent_name, event_type, title, status, created_at
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FROM agent_events ORDER BY created_at DESC LIMIT 12"""
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)
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except Exception:
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data["recent_events"] = []
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try:
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data["pending_items"] = fetch_all(
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"""SELECT agent_name, title, event_type, created_at
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FROM agent_events WHERE status = 'needs_approval'
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ORDER BY created_at DESC LIMIT 8"""
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)
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except Exception:
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data["pending_items"] = []
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try:
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row = fetch_one(
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"""SELECT COUNT(*) AS docs, COALESCE(SUM(word_count), 0) AS words,
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COALESCE(AVG(sentiment_compound), 0) AS avg_sentiment
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FROM document_analytics"""
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)
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data["nas_docs"] = int(row["docs"] or 0) if row else 0
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data["nas_words"] = int(row["words"] or 0) if row else 0
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data["nas_sentiment"] = round(float(row["avg_sentiment"] or 0), 3) if row else 0.0
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except Exception:
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data["nas_docs"] = data["nas_words"] = 0
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data["nas_sentiment"] = 0.0
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try:
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data["nas_files"] = fetch_all(
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"""SELECT filename, doc_type, sentiment_label, word_count
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FROM document_analytics ORDER BY analyzed_at DESC LIMIT 8"""
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)
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except Exception:
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data["nas_files"] = []
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try:
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data["top_words"] = fetch_all(
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"""SELECT lemma, SUM(count) AS total FROM document_word_counts
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WHERE NOT is_stopword GROUP BY lemma ORDER BY total DESC LIMIT 10"""
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)
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except Exception:
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data["top_words"] = []
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try:
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data["calendar_events"] = fetch_all(
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"""SELECT ce.title, ce.starts_at, ce.ends_at, c.name AS client_name
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FROM calendar_events ce
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LEFT JOIN clients c ON c.id = ce.client_id
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WHERE ce.starts_at >= NOW() - INTERVAL '1 day'
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AND ce.starts_at <= NOW() + INTERVAL '7 days'
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ORDER BY ce.starts_at ASC LIMIT 10"""
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)
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except Exception:
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data["calendar_events"] = []
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# Retail intelligence
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data["supermarkets"] = _safe_count("supermarkets")
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data["crm_partnerships"] = _safe_count("supermarkets", "partnership_status = 'active'")
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data["wholesalers"] = _safe_count("wholesalers")
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try:
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data["top_opportunities"] = fetch_all(
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"""SELECT s.name, s.chain, s.city, ros.halal_opportunity_score
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FROM retail_opportunity_scores ros
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JOIN supermarkets s ON s.id = ros.supermarket_id
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ORDER BY ros.halal_opportunity_score DESC LIMIT 5"""
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)
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except Exception:
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data["top_opportunities"] = []
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try:
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data["milestones_pending"] = fetch_all(
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"""SELECT sm.title, sm.milestone_type, sm.status, sm.target_date, sm.value_eur,
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s.name AS store_name, s.chain, c.name AS client_name
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FROM sales_milestones sm
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LEFT JOIN supermarkets s ON s.id = sm.supermarket_id
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LEFT JOIN clients c ON c.id = sm.client_id
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WHERE sm.status IN ('pending', 'in_progress')
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ORDER BY sm.target_date ASC NULLS LAST, sm.created_at DESC LIMIT 8"""
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)
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except Exception:
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data["milestones_pending"] = []
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try:
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data["milestones_recent"] = fetch_all(
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"""SELECT sm.title, sm.milestone_type, sm.status, sm.completed_at, sm.value_eur,
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s.name AS store_name, s.chain
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FROM sales_milestones sm
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LEFT JOIN supermarkets s ON s.id = sm.supermarket_id
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ORDER BY sm.created_at DESC LIMIT 5"""
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)
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except Exception:
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data["milestones_recent"] = []
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try:
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data["rss_highlights"] = fetch_all(
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"""SELECT i.title, i.link, i.summary, f.name AS feed_name, f.url AS feed_url
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FROM rss_items i JOIN rss_feeds f ON f.id = i.feed_id AND f.is_active = TRUE
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WHERE i.title ILIKE ANY (ARRAY['%kant%','%maaltijd%','%supermarkt%','%retail%','%halal%','%jumbo%','%meal%'])
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ORDER BY i.published_at DESC NULLS LAST LIMIT 6"""
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)
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except Exception:
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data["rss_highlights"] = []
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try:
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data["market_trends"] = fetch_all(
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"SELECT trend_name, description, opportunity_score FROM market_trends ORDER BY updated_at DESC LIMIT 4"
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)
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except Exception:
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data["market_trends"] = []
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return data
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def build_template_report(data: dict[str, Any]) -> str:
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lines = [
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f"# Foodlinkk Dagrapport — {data['date']}",
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"",
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f"*Gegenereerd: {data['generated_at'][:19]} UTC · Model: {settings.OLLAMA_MODEL}*",
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"",
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"## KPI's",
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f"- **Klanten:** {data['clients']} · **Deals:** {data['deals']} · **Pipeline:** €{data['pipeline_eur']:,.0f}",
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f"- **Supermarkten in DB:** {data.get('supermarkets', 0)} · **CRM partnerships:** {data.get('crm_partnerships', 0)}",
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f"- **Groothandels:** {data.get('wholesalers', 0)} · **Goedkeuringen open:** {data['pending_approvals']}",
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"",
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]
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if data.get("top_opportunities"):
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lines.extend(["## Top halal-markt kansen (Retail 360)"])
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for row in data["top_opportunities"]:
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score = round(float(row.get("halal_opportunity_score") or 0))
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lines.append(f"- **{row.get('chain')} · {row.get('name')}** ({row.get('city')}) — score {score}/100")
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lines.append("")
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if data.get("milestones_pending"):
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lines.extend(["## Sales milestones — open"])
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for row in data["milestones_pending"]:
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td = row.get("target_date")
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td_s = td.isoformat()[:10] if hasattr(td, "isoformat") else str(td or "—")[:10]
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lines.append(f"- [{td_s}] **{row.get('title')}** · {row.get('chain') or ''} {row.get('store_name') or ''} · €{row.get('value_eur') or '—'}")
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lines.append("")
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if data.get("rss_highlights"):
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lines.extend(["## Kant-en-klaar & supermarkt nieuws"])
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for row in data["rss_highlights"]:
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lines.append(f"- [{row.get('feed_name')}] {row.get('title')}")
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lines.append("")
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if data.get("market_trends"):
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lines.extend(["## Markt trends"])
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for row in data["market_trends"]:
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pct = round(float(row.get("opportunity_score") or 0) * 100)
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lines.append(f"- **{row.get('trend_name')}** ({pct}% kans) — {row.get('description') or ''}")
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lines.append("")
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lines.extend(["## Pipeline per stage"])
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for row in data.get("deals_by_stage") or []:
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lines.append(f"- **{row.get('stage')}:** {row.get('cnt')} deals · €{float(row.get('total') or 0):,.0f}")
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if not data.get("deals_by_stage"):
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lines.append("- Geen deals in database.")
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if data.get("calendar_events"):
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lines.extend(["", "## Agenda (7 dagen)"])
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for row in data["calendar_events"]:
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ts = row.get("starts_at")
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ts_s = ts.isoformat()[:16] if hasattr(ts, "isoformat") else str(ts)[:16]
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lines.append(f"- [{ts_s}] {row.get('title')} ({row.get('client_name') or '-'})")
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if data.get("pending_items"):
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lines.extend(["", "## ⚠️ Wacht op jouw goedkeuring"])
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for row in data["pending_items"]:
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lines.append(f"- {row.get('agent_name')}: {row.get('title')}")
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return "\n".join(lines)
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async def _ai_executive_summary(data: dict[str, Any]) -> str:
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opp_lines = ""
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for row in data.get("top_opportunities") or []:
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opp_lines += f"- {row.get('chain')} {row.get('name')} ({row.get('city')}): score {round(float(row.get('halal_opportunity_score') or 0))}\n"
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ms_lines = ""
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for row in data.get("milestones_pending") or []:
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ms_lines += f"- {row.get('title')} ({row.get('chain') or 'CRM'}) deadline {row.get('target_date') or '?'}\n"
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prompt = (
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"Schrijf in het Nederlands (markdown) voor CEO Aïssa van Foodlinkk (halal kant-en-klaar maaltijden):\n\n"
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"## Samenvatting\n(5-7 zinnen: wat is vandaag belangrijk, pipeline, retail kansen, milestones)\n\n"
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"## Actiepunten vandaag — korte termijn\n(minimaal 5 concrete bullets met CRM/retail acties)\n\n"
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"## Lange termijn focus\n(3-5 bullets: groei supermarkt partnerships, halal markt, milestones komende weken)\n\n"
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f"Data vandaag ({data['date']}):\n"
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f"- Pipeline €{data['pipeline_eur']:,.0f}, {data['clients']} klanten, {data['deals']} deals\n"
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f"- {data.get('supermarkets',0)} supermarkten, {data.get('crm_partnerships',0)} actieve CRM partnerships\n"
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f"- {data['pending_approvals']} goedkeuringen open\n"
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f"Top kansen:\n{opp_lines or '- geen data'}\n"
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f"Milestones open:\n{ms_lines or '- geen milestones'}\n"
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)
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system = (
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"Je bent Herman, AI co-CEO van Foodlinkk. Schrijf warm, professioneel en actionable. "
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"Focus op halal kant-en-klaar retail groei in Nederland. Geen vage tekst — concrete namen en acties."
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)
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try:
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return await ollama.generate(prompt, system=system, timeout=120.0)
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except Exception:
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return ""
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def _fallback_summary(data: dict[str, Any]) -> str:
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opp = data.get("top_opportunities") or []
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ms = data.get("milestones_pending") or []
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lines = [
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"## Samenvatting",
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f"Vandaag ({data['date']}) heb je **€{data['pipeline_eur']:,.0f}** in je pipeline en **{data.get('crm_partnerships',0)} actieve supermarkt-partnerships**. "
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f"In Retail 360 staan **{data.get('supermarkets',0)} filialen** met live CBS-data.",
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]
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if opp:
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top = opp[0]
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lines.append(
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f"De grootste halal-kans is **{top.get('chain')} · {top.get('name')}** in {top.get('city')} "
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f"(score {round(float(top.get('halal_opportunity_score') or 0))}/100)."
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)
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lines.extend(["", "## Actiepunten vandaag — korte termijn"])
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actions = [
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"Open Retail 360 en benader top-3 halal-gap filialen via CRM koppeling",
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f"Behandel {data['pending_approvals']} openstaande agent-goedkeuringen",
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"Check Marketing Live Feed voor kant-en-klaar trends",
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]
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if ms:
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actions.insert(0, f"Follow-up milestone: **{ms[0].get('title')}**")
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for a in actions[:6]:
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lines.append(f"- {a}")
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lines.extend(["", "## Lange termijn focus"])
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lines.extend([
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"- Schaal CRM partnerships van proposal naar actief in top-10 kans-filialen",
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"- Halal kant-en-klaar listing bij Jumbo/AH regio's met hoogste demografische vraag",
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"- Wekelijks milestones review in Retail 360 sales tab",
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])
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return "\n".join(lines)
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def _save_briefing(content: str, data: dict[str, Any]) -> None:
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safe = serialize_stats(data)
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metadata = {"stats": safe, "model": settings.OLLAMA_MODEL, "type": "daily_ceo_report"}
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try:
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execute(
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"INSERT INTO daily_briefings (content, generated_by, metadata) VALUES (%s, %s, %s::jsonb)",
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(content, "herman", json.dumps(metadata)),
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)
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except Exception:
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pass
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try:
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execute(
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"""INSERT INTO agent_events (agent_name, agent_type, event_type, title, body, status, channel, metadata)
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VALUES (%s, %s, %s, %s, %s, %s, %s, %s::jsonb)""",
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(
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"herman", "herman_delegate", "briefing",
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f"CEO dagrapport {data['date']}", content[:2000],
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"completed", "dashboard", json.dumps({"stats": safe}),
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),
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)
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except Exception:
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pass
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async def generate_daily_briefing() -> tuple[str, dict[str, Any]]:
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data = collect_briefing_data()
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template = build_template_report(data)
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try:
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ai_part = await asyncio.wait_for(_ai_executive_summary(data), timeout=25.0)
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except (asyncio.TimeoutError, Exception):
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ai_part = ""
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if ai_part and len(ai_part.strip()) > 80:
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content = ai_part.strip() + "\n\n---\n\n" + template
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else:
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content = _fallback_summary(data) + "\n\n---\n\n" + template
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_save_briefing(content, data)
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return content, serialize_stats(data)
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Reference in New Issue
Block a user