foodlinkk-command-center/cockpit/templates/briefing.py

from __future__ import annotations

import asyncio
import json
from datetime import date, datetime, timezone
from typing import Any

from app.config import settings
from app.db import execute, fetch_all, fetch_one
from app.services import ollama


def _safe_count(table: str, where: str = "", params: tuple = ()) -> int:
    try:
        clause = f" WHERE {where}" if where else ""
        row = fetch_one(f"SELECT COUNT(*) AS c FROM {table}{clause}", params or None)
        return int(row["c"]) if row else 0
    except Exception:
        return 0


def _safe_sum(table: str, column: str, where: str = "", params: tuple = ()) -> float:
    try:
        clause = f" WHERE {where}" if where else ""
        row = fetch_one(f"SELECT COALESCE(SUM({column}), 0) AS total FROM {table}{clause}", params or None)
        return float(row["total"]) if row else 0.0
    except Exception:
        return 0.0


def serialize_stats(data: dict[str, Any]) -> dict[str, Any]:
    """JSON-safe copy of briefing stats (datetimes, decimals)."""

    def _default(o: Any) -> Any:
        if hasattr(o, "isoformat"):
            return o.isoformat()
        if hasattr(o, "__float__"):
            try:
                return float(o)
            except (TypeError, ValueError):
                pass
        return str(o)

    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(),
    }
    data["clients"] = _safe_count("clients")
    data["deals"] = _safe_count("deals")
    data["products"] = _safe_count("products")
    data["suppliers"] = _safe_count("suppliers")
    data["pipeline_eur"] = _safe_sum("deals", "value", "stage NOT IN ('won', 'lost')")
    data["pending_approvals"] = _safe_count("agent_events", "status = 'needs_approval'")

    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"
        )
    except Exception:
        data["deals_by_stage"] = []

    try:
        data["recent_clients"] = fetch_all(
            "SELECT name, stage, email, created_at FROM clients ORDER BY created_at DESC LIMIT 5"
        )
    except Exception:
        data["recent_clients"] = []

    try:
        data["recent_events"] = fetch_all(
            """
            SELECT agent_name, event_type, title, status, created_at
            FROM agent_events ORDER BY created_at DESC LIMIT 12
            """
        )
    except Exception:
        data["recent_events"] = []

    try:
        data["pending_items"] = fetch_all(
            """
            SELECT agent_name, title, event_type, created_at
            FROM agent_events WHERE status = 'needs_approval'
            ORDER BY created_at DESC LIMIT 8
            """
        )
    except Exception:
        data["pending_items"] = []

    try:
        row = fetch_one(
            """
            SELECT COUNT(*) AS docs, COALESCE(SUM(word_count), 0) AS words,
                   COALESCE(AVG(sentiment_compound), 0) AS avg_sentiment
            FROM document_analytics
            """
        )
        data["nas_docs"] = int(row["docs"] or 0) if row else 0
        data["nas_words"] = int(row["words"] or 0) if row else 0
        data["nas_sentiment"] = round(float(row["avg_sentiment"] or 0), 3) if row else 0.0
    except Exception:
        data["nas_docs"] = data["nas_words"] = 0
        data["nas_sentiment"] = 0.0

    try:
        data["nas_files"] = fetch_all(
            """
            SELECT filename, doc_type, sentiment_label, word_count
            FROM document_analytics ORDER BY analyzed_at DESC LIMIT 8
            """
        )
    except Exception:
        data["nas_files"] = []

    try:
        data["top_words"] = fetch_all(
            """
            SELECT lemma, SUM(count) AS total FROM document_word_counts
            WHERE NOT is_stopword GROUP BY lemma ORDER BY total DESC LIMIT 10
            """
        )
    except Exception:
        data["top_words"] = []

    try:
        data["calendar_events"] = fetch_all(
            """
            SELECT ce.title, ce.starts_at, ce.ends_at, c.name AS client_name
            FROM calendar_events ce
            LEFT JOIN clients c ON c.id = ce.client_id
            WHERE ce.starts_at >= NOW() - INTERVAL '1 day'
              AND ce.starts_at <= NOW() + INTERVAL '7 days'
            ORDER BY ce.starts_at ASC LIMIT 10
            """
        )
    except Exception:
        data["calendar_events"] = []

    return data


def build_template_report(data: dict[str, Any]) -> str:
    lines = [
        f"# Foodlinkk Dagrapport — {data['date']}",
        "",
        f"*Gegenereerd: {data['generated_at'][:19]} UTC · Model: {settings.OLLAMA_MODEL}*",
        "",
        "## KPI's",
        f"- **Klanten:** {data['clients']}",
        f"- **Deals totaal:** {data['deals']}",
        f"- **Pipeline (actief):** €{data['pipeline_eur']:,.0f}",
        f"- **Producten:** {data['products']}",
        f"- **Leveranciers:** {data['suppliers']}",
        f"- **Openstaande goedkeuringen:** {data['pending_approvals']}",
        "",
        "## Pipeline per stage",
    ]
    if data.get("deals_by_stage"):
        for row in data["deals_by_stage"]:
            lines.append(f"- **{row.get('stage')}:** {row.get('cnt')} deals · €{float(row.get('total') or 0):,.0f}")
    else:
        lines.append("- Geen deals in database.")

    lines.extend(["", "## Recente klanten"])
    for row in data.get("recent_clients") or []:
        lines.append(f"- {row.get('name')} ({row.get('stage')})")
    if not data.get("recent_clients"):
        lines.append("- Geen klanten.")

    lines.extend([
        "",
        "## NAS share — documenten",
        f"- Ingelezen documenten: **{data['nas_docs']}**",
        f"- Totaal woorden geanalyseerd: **{data['nas_words']}**",
        f"- Gemiddeld sentiment: **{data['nas_sentiment']}**",
        "",
    ])
    for row in data.get("nas_files") or []:
        lines.append(f"- {row.get('filename')} · {row.get('doc_type')} · sentiment: {row.get('sentiment_label')}")

    if data.get("top_words"):
        lines.extend(["", "## Top woorden (NAS corpus)"])
        for row in data["top_words"]:
            lines.append(f"- {row.get('lemma')}: {row.get('total')}×")

    if data.get("calendar_events"):
        lines.extend(["", "## Agenda (7 dagen)"])
        for row in data["calendar_events"]:
            ts = row.get("starts_at")
            ts_s = ts.isoformat()[:16] if hasattr(ts, "isoformat") else str(ts)[:16]
            lines.append(f"- [{ts_s}] {row.get('title')} ({row.get('client_name') or '-'})")

    lines.extend(["", "## Recente agent activiteit"])
    for row in data.get("recent_events") or []:
        ts = row.get("created_at")
        ts_s = ts.isoformat()[:16] if hasattr(ts, "isoformat") else str(ts)[:16]
        lines.append(f"- [{ts_s}] **{row.get('agent_name')}** — {row.get('title') or row.get('event_type')}")

    if data.get("pending_items"):
        lines.extend(["", "## ⚠️ Wacht op jouw goedkeuring"])
        for row in data["pending_items"]:
            lines.append(f"- {row.get('agent_name')}: {row.get('title')}")

    return "\n".join(lines)


async def _ai_executive_summary(data: dict[str, Any], template: str) -> str:
    prompt = (
        "Schrijf alleen deze twee secties in het Nederlands (markdown):\n"
        "## Samenvatting\n(4-6 zinnen voor CEO Aïssa)\n\n"
        "## Actiepunten vandaag\n(minimaal 5 concrete bullets)\n\n"
        f"Gebaseerd op:\n- Pipeline €{data['pipeline_eur']:,.0f}\n"
        f"- {data['clients']} klanten, {data['deals']} deals\n"
        f"- {data['pending_approvals']} goedkeuringen open\n"
        f"- {data['nas_docs']} NAS documenten\n"
    )
    system = "Je bent Herman, co-CEO Foodlinkk. Kort, zakelijk, actionable."
    try:
        return await ollama.generate(prompt, system=system, timeout=120.0)
    except Exception:
        return ""


def _save_briefing(content: str, data: dict[str, Any]) -> None:
    safe = serialize_stats(data)
    metadata = {"stats": safe, "model": settings.OLLAMA_MODEL, "type": "daily_ceo_report"}
    try:
        execute(
            "INSERT INTO daily_briefings (content, generated_by, metadata) VALUES (%s, %s, %s::jsonb)",
            (content, "herman", json.dumps(metadata)),
        )
    except Exception:
        pass
    try:
        execute(
            """
            INSERT INTO agent_events (agent_name, agent_type, event_type, title, body, status, channel, metadata)
            VALUES (%s, %s, %s, %s, %s, %s, %s, %s::jsonb)
            """,
            (
                "herman", "herman_delegate", "briefing",
                f"CEO dagrapport {data['date']}", content[:2000],
                "completed", "dashboard", json.dumps({"stats": safe}),
            ),
        )
    except Exception:
        pass


async def generate_daily_briefing() -> tuple[str, dict[str, Any]]:
    data = collect_briefing_data()
    template = build_template_report(data)
    try:
        ai_part = await asyncio.wait_for(_ai_executive_summary(data, template), timeout=90.0)
    except (asyncio.TimeoutError, Exception):
        ai_part = ""

    if ai_part and len(ai_part.strip()) > 40:
        content = ai_part.strip() + "\n\n---\n\n" + template
    else:
        content = template + "\n\n---\n\n*AI-samenvatting niet beschikbaar (Ollama busy) — bovenstaande data is live uit je database.*"

    _save_briefing(content, data)
    return content, serialize_stats(data)