/* MonthEndIQ — Reports page * * Architecture: each ReportSection_* component renders a self-contained report * block and exposes a static .toPlainText(data) method. Export generators * (PDF, PPTX, Board Pack) should consume the same data model — the report * object returned by buildReportModel() — so reporting logic lives here once. */ const { useState: useStateR, useEffect: useEffectR, useRef: useRefR, useMemo: useMemoR } = React; /* ── Report data model builder ───────────────────────────────────────────── */ function buildReportModel(data, analysisType, periodMode) { if (!data) return null; const isBvA = (analysisType || data.analysis_type) === "budget_vs_actual"; const { kpis, movements, commentary, waterfall, period, selected_period, revenue_split, expense_split } = data; const allRows = movements || []; const favRows = allRows.filter(m => m.is_fav && m.variance !== 0); const advRows = allRows.filter(m => !m.is_fav && m.variance !== 0); const largestFav = favRows.length ? favRows.reduce((a, b) => Math.abs(a.variance) > Math.abs(b.variance) ? a : b) : null; const largestAdv = advRows.length ? advRows.reduce((a, b) => Math.abs(a.variance) > Math.abs(b.variance) ? a : b) : null; const profKpi = (kpis || []).find(k => !k.pct_only && k.icon === "wallet"); const revKpi = (kpis || []).find(k => !k.pct_only && k.icon === "trending-up"); const topFav = favRows.sort((a, b) => Math.abs(b.variance) - Math.abs(a.variance)).slice(0, 5); const topAdv = advRows.sort((a, b) => Math.abs(b.variance) - Math.abs(a.variance)).slice(0, 5); return { isBvA, periodLabel: period?.label || selected_period || "", priorLabel: period?.prior || (isBvA ? "Budget" : "Prior"), periodMode, kpis: kpis || [], profKpi, revKpi, movements: allRows, commentary: commentary || [], waterfall, revenue_split: revenue_split || [], expense_split: expense_split || [], largestFav, largestAdv, topFav, topAdv, favCount: favRows.length, advCount: advRows.length, totalFav: favRows.reduce((s, m) => s + Math.abs(m.variance || 0), 0), totalAdv: advRows.reduce((s, m) => s + Math.abs(m.variance || 0), 0), }; } /* ── Formatters (shared) ─────────────────────────────────────────────────── */ const rfmtGBP = (v) => window.fmtCurrency(v); const rfmtSignedGBP = (v) => window.fmtCurrency(v, { signed: true }); const rfmtPct = (v) => { if (v == null || isNaN(v)) return "—"; return (v > 0 ? "+" : v < 0 ? "-" : "") + Math.abs(v).toFixed(1) + "%"; }; /* ── Section wrapper ─────────────────────────────────────────────────────── */ function ReportSection({ id, title, sub, icon, children, className, action }) { const { Icon } = window; return (

{title}

{sub &&
{sub}
}
{action}
{children}
); } /* ═══════════════════════════════════════════════════════════════════════════ * REPORT SECTIONS — each is a reusable component * ═══════════════════════════════════════════════════════════════════════════ */ /* ── Executive Summary ───────────────────────────────────────────────────── */ function ReportExecutiveSummary({ model }) { const { Icon } = window; if (!model) return null; const { isBvA, periodLabel, priorLabel, profKpi, revKpi, largestFav, largestAdv, favCount, advCount, totalFav, totalAdv } = model; const profVar = profKpi?.variance; const profFav = profKpi?.is_fav; const headline = profKpi ? (isBvA ? `Operating Profit was ${rfmtGBP(Math.abs(profVar))} ${profFav ? "above" : "below"} budget at ${rfmtGBP(profKpi.value)}, versus a budget of ${rfmtGBP(profKpi.prior)}.` : `Operating Profit ${profVar >= 0 ? "increased" : "decreased"} by ${rfmtGBP(Math.abs(profVar))} to ${rfmtGBP(profKpi.value)}, from ${rfmtGBP(profKpi.prior)} in the prior period.`) : ""; const revLine = revKpi ? (isBvA ? `Total Revenue was ${rfmtGBP(revKpi.value)} against a budget of ${rfmtGBP(revKpi.prior)} (${rfmtPct(revKpi.pct)}).` : `Total Revenue was ${rfmtGBP(revKpi.value)}, ${revKpi.variance >= 0 ? "up" : "down"} ${rfmtGBP(Math.abs(revKpi.variance))} (${rfmtPct(revKpi.pct)}) versus the prior period.`) : ""; const varSummary = `There were ${favCount} favourable variance${favCount !== 1 ? "s" : ""} totalling ${rfmtGBP(totalFav)} and ${advCount} adverse variance${advCount !== 1 ? "s" : ""} totalling ${rfmtGBP(totalAdv)}.`; return (

Period: {periodLabel}{isBvA ? " — Actual vs Budget" : ` vs ${priorLabel}`}

{headline}

{revLine &&

{revLine}

}

{varSummary}

{largestFav && (

Largest favourable variance:{" "} {largestFav.account} ({rfmtSignedGBP(largestFav.variance)})

)} {largestAdv && (

Largest adverse variance:{" "} {largestAdv.account} ({rfmtSignedGBP(largestAdv.variance)})

)}
); } /* ── KPI Summary ─────────────────────────────────────────────────────────── */ function ReportKpiSummary({ model }) { const { Icon, Delta } = window; if (!model) return null; return (
{model.kpis.filter(k => !k.pct_only).map(k => (
{k.label}
{rfmtGBP(k.value)}
{model.isBvA ? "Budget" : "Prior"}: {rfmtGBP(k.prior)} = 0}> {rfmtSignedGBP(k.variance)} · {rfmtPct(k.pct)}
))}
); } /* ── AI Narrative Commentary ─────────────────────────────────────────────── */ function ReportAINarrative({ sessionId, period, periodMode, analysisType }) { const { Icon, Button } = window; const [status, setStatus] = React.useState("idle"); // idle | loading | done | error const [narrative, setNarrative] = React.useState(null); const [verification, setVerification] = React.useState(null); const [copied, setCopied] = React.useState(false); const [errMsg, setErrMsg] = React.useState(""); const [contextNotes, setContextNotes] = React.useState(""); const [tonePreset, setTonePreset] = React.useState(() => { try { return localStorage.getItem("meiq_default_tone") || "board"; } catch { return "board"; } }); // board | management | client const generate = async () => { setStatus("loading"); try { const isBvA = analysisType === "budget_vs_actual"; const periodParam = isBvA ? (period?.label === "Actual" ? "full_year" : (period?.label || "full_year")) : (period?.label || null); const res = await fetch(apiUrl(`/api/commentary/${sessionId}`), { method: "POST", headers: { "Content-Type": "application/json" }, body: JSON.stringify({ period: periodParam, mode: periodMode || "monthly", context_notes: contextNotes.trim() || null, tone: tonePreset, currency_sym: (() => { try { return localStorage.getItem("meiq_currency_sym") || "£"; } catch { return "£"; } })() }), }); if (!res.ok) { const err = await res.json().catch(() => ({})); throw new Error(err.detail || `HTTP ${res.status}`); } const data = await res.json(); setNarrative(data.narrative); setVerification(data.verification || null); setStatus("done"); } catch (e) { console.error("[Commentary]", e); setErrMsg(e.message || ""); setStatus("error"); } }; const copy = () => { const div = document.createElement("div"); div.innerHTML = narrative; const text = div.innerText || div.textContent || ""; navigator.clipboard.writeText(text).catch(() => {}); setCopied(true); setTimeout(() => setCopied(false), 2000); }; return ( AI}> {status === "idle" && (
Generate board-ready narrative commentary
AI writes a full management pack narrative — revenue, costs, profitability and recommended actions.
{/* Tone preset selector */}
Commentary tone
{[ { key: "board", label: "Board Pack", desc: "Formal, CFO-level" }, { key: "management", label: "Management Review", desc: "Detailed & operational" }, { key: "client", label: "Client Digest", desc: "Plain English" }, ].map(t => ( ))}