feat: instrument analysis
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OpenSquared
@@ -1391,21 +1391,47 @@ Règles : coef intermédiaire ∈ [-5,5] ; coef output en pips, |val| ∈ [30,20
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def refresh_auto_analyses():
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"""
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Re-run _run_auto_analysis for all causal_event_analyses rows with empty actual_json.
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Fills in real price data so comprehension scores can be computed.
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Returns detailed per-event debug info.
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"""
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try:
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from services.database import get_conn
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conn = get_conn()
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rows = conn.execute("""
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# Also return a DB state summary for all analyses (not just empty ones)
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all_rows = conn.execute("""
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SELECT a.id AS cea_id, a.market_event_id, a.template_id,
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a.actual_json
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a.actual_json, a.prediction_json,
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e.name AS event_name, e.start_date
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FROM causal_event_analyses a
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WHERE a.actual_json IS NULL OR a.actual_json = '{}' OR a.actual_json = 'null'
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LEFT JOIN market_events e ON e.id = a.market_event_id
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ORDER BY a.id DESC
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""").fetchall()
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db_state = []
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for r in all_rows:
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actual = r["actual_json"] or ""
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pred = r["prediction_json"] or ""
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db_state.append({
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"cea_id": r["cea_id"],
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"event_id": r["market_event_id"],
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"event_name": r["event_name"],
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"start_date": r["start_date"],
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"template_id": r["template_id"],
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"actual_empty": actual in (None, "", "{}", "null"),
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"pred_empty": pred in (None, "", "{}", "null"),
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"actual_keys": list(json.loads(actual).keys()) if actual not in (None, "", "{}", "null") else [],
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"pred_keys": list(json.loads(pred).keys()) if pred not in (None, "", "{}", "null") else [],
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})
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rows = [r for r in all_rows if (r["actual_json"] or "") in (None, "", "{}", "null")]
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print(f"[refresh] {len(rows)} analyses with empty actual_json out of {len(all_rows)} total", flush=True)
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conn.close()
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details = []
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refreshed, failed = 0, 0
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for row in rows:
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detail: dict = {"cea_id": row["cea_id"], "event_id": row["market_event_id"],
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"event_name": row["event_name"], "template_id": row["template_id"]}
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try:
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conn2 = get_conn()
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ev_row = conn2.execute(
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@@ -1413,18 +1439,33 @@ def refresh_auto_analyses():
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).fetchone()
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conn2.close()
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if not ev_row:
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detail["result"] = "event_not_found"
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details.append(detail)
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continue
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ok = _run_auto_analysis(dict(ev_row), row["template_id"])
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ev = dict(ev_row)
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detail["surprise_pct"] = ev.get("surprise_pct")
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detail["start_date"] = ev.get("start_date")
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ok = _run_auto_analysis(ev, row["template_id"])
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detail["result"] = "ok" if ok else "failed"
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if ok:
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refreshed += 1
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else:
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failed += 1
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detail["result"] = "run_returned_false"
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except Exception as _e:
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logger.warning(f"[refresh_auto_analyses] cea#{row['cea_id']}: {_e}")
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detail["result"] = f"exception: {_e}"
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failed += 1
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details.append(detail)
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logger.info(f"[refresh_auto_analyses] done: {refreshed} refreshed, {failed} failed")
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return {"refreshed": refreshed, "failed": failed, "total": len(rows)}
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print(f"[refresh] done: {refreshed} refreshed, {failed} failed", flush=True)
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return {
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"refreshed": refreshed,
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"failed": failed,
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"total": len(rows),
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"db_state": db_state,
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"details": details,
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}
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except Exception as e:
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logger.error(f"[refresh_auto_analyses] {e}")
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raise HTTPException(500, str(e))
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@@ -1023,10 +1023,12 @@ function ExplanationScore({
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}) {
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const [refreshing, setRefreshing] = useState(false)
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const [refreshDone, setRefreshDone] = useState(false)
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const [debugInfo, setDebugInfo] = useState<any>(null)
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// For each linked event, compute the comprehension score and collect scored ones
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const scored: number[] = []
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const totalLinked: number[] = []
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const debugRows: {id?: number; name: string; pred: string; actual: string; score: number | null; reason: string}[] = []
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for (const ev of events) {
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if (!ev.template_id) continue
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@@ -1035,7 +1037,35 @@ function ExplanationScore({
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const inst = causalInsts.find(ci => tmpl.instruments.includes(ci))
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if (!inst) continue
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totalLinked.push(ev.id ?? 0)
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// Detailed debug per event
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const hasPred = !!(ev.prediction_json && ev.prediction_json !== '{}')
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const hasActual = !!(ev.actual_json && ev.actual_json !== '{}')
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let reason = ''
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if (!hasPred) reason = 'prediction_json vide'
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else if (!hasActual) reason = 'actual_json vide'
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else {
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try {
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const preds = JSON.parse(ev.prediction_json!)
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const actuals = JSON.parse(ev.actual_json!)
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const outputNode = tmpl.graph_json.nodes.find(n =>
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(n.type === 'market_asset' || n.type === 'output') && n.instrument?.toUpperCase() === inst.toUpperCase()
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)
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if (!outputNode) reason = `nœud output "${inst}" introuvable (types: ${[...new Set(tmpl.graph_json.nodes.map(n => n.type))].join(',')})`
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else if (preds[outputNode.id] == null) reason = `preds["${outputNode.id}"] absent`
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else if (actuals[inst] == null && actuals[inst.toUpperCase()] == null) reason = `actuals["${inst}"] absent — clés: ${Object.keys(actuals).join(',')}`
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else reason = 'ok'
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} catch (e) { reason = `parse error: ${e}` }
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}
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debugRows.push({
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id: ev.id, name: ev.title?.slice(0, 30) ?? '?',
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pred: hasPred ? '✓' : '✗',
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actual: hasActual ? '✓' : '✗',
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score: null, reason,
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})
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const s = comprehensionScore(ev, tmpl, inst)
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if (debugRows.length > 0) debugRows[debugRows.length - 1].score = s
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if (s != null) scored.push(s)
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}
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@@ -1056,12 +1086,17 @@ function ExplanationScore({
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: globalScore >= 70 ? 'bg-emerald-500' : globalScore >= 40 ? 'bg-amber-500' : 'bg-red-500'
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const handleRefresh = async () => {
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setDebugInfo(null)
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setRefreshing(true)
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try {
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await api.post('/causal-lab/auto-analyze/refresh')
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const res = await api.post('/causal-lab/auto-analyze/refresh')
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const data = res.data
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setDebugInfo(data)
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setRefreshDone(true)
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onRefreshDone?.()
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setTimeout(() => setRefreshDone(false), 3000)
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setTimeout(() => setRefreshDone(false), 8000)
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} catch (err: any) {
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setDebugInfo({ error: String(err) })
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} finally {
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setRefreshing(false)
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}
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@@ -1070,28 +1105,57 @@ function ExplanationScore({
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const needsRefresh = totalLinked.length > 0 && scored.length === 0 && !refreshDone
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return (
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<div className="flex items-center gap-3 px-4 py-2.5 rounded-xl border border-slate-700/30 bg-dark-800/50">
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<span className="text-xs text-slate-500 whitespace-nowrap">Note globale</span>
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<div className="flex-1 h-1.5 bg-slate-800 rounded-full overflow-hidden">
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<div className={clsx('h-full rounded-full transition-all', barCls)} style={{ width: `${globalScore ?? 0}%` }} />
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<div className="space-y-2">
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<div className="flex items-center gap-3 px-4 py-2.5 rounded-xl border border-slate-700/30 bg-dark-800/50">
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<span className="text-xs text-slate-500 whitespace-nowrap">Note globale</span>
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<div className="flex-1 h-1.5 bg-slate-800 rounded-full overflow-hidden">
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<div className={clsx('h-full rounded-full transition-all', barCls)} style={{ width: `${globalScore ?? 0}%` }} />
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</div>
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<span className={clsx('text-xs font-semibold px-2 py-1 rounded-lg border whitespace-nowrap', badgeCls)}>
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{globalScore != null ? `${globalScore}% — ` : ''}{verdict}
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</span>
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<span className="text-[10px] text-slate-600 whitespace-nowrap">
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{scored.length}/{totalLinked.length} graphes
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</span>
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{(needsRefresh || scored.length === 0) && !refreshDone && totalLinked.length > 0 && (
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<button
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onClick={handleRefresh}
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disabled={refreshing}
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className="text-[10px] text-violet-400 hover:text-violet-200 bg-violet-900/20 hover:bg-violet-900/40 border border-violet-800/40 rounded px-2 py-1 whitespace-nowrap disabled:opacity-50 transition-colors"
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>
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{refreshing ? '…' : 'Recalculer'}
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</button>
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)}
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</div>
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<span className={clsx('text-xs font-semibold px-2 py-1 rounded-lg border whitespace-nowrap', badgeCls)}>
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{globalScore != null ? `${globalScore}% — ` : ''}{verdict}
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</span>
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<span className="text-[10px] text-slate-600 whitespace-nowrap">
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{scored.length}/{totalLinked.length} graphes
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</span>
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{needsRefresh && (
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<button
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onClick={handleRefresh}
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disabled={refreshing}
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className="text-[10px] text-violet-400 hover:text-violet-200 bg-violet-900/20 hover:bg-violet-900/40 border border-violet-800/40 rounded px-2 py-1 whitespace-nowrap disabled:opacity-50 transition-colors"
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>
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{refreshing ? '…' : 'Recalculer'}
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</button>
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)}
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{refreshDone && (
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<span className="text-[10px] text-emerald-500 whitespace-nowrap">✓ Rechargez la page</span>
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{/* Debug panel — score diagnostics per event */}
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{debugRows.length > 0 && scored.length === 0 && (
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<div className="rounded-lg border border-slate-700/30 bg-dark-900/60 p-3 text-[10px] font-mono">
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<div className="text-slate-500 mb-1.5 uppercase tracking-wide">Diagnostic scores ({debugRows.length} graphes)</div>
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{debugRows.map((r, i) => (
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<div key={i} className="flex gap-2 py-0.5 border-b border-slate-800/40 last:border-0">
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<span className={clsx('shrink-0 w-4', r.pred === '✓' ? 'text-emerald-600' : 'text-red-600')}>{r.pred}</span>
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<span className={clsx('shrink-0 w-4', r.actual === '✓' ? 'text-emerald-600' : 'text-red-600')}>{r.actual}</span>
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<span className="text-slate-400 w-36 shrink-0 truncate" title={r.name}>{r.name}</span>
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<span className={clsx('flex-1', r.reason === 'ok' ? 'text-emerald-600' : 'text-amber-600')}>{r.reason}</span>
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{r.score != null && <span className="text-violet-400">{r.score}%</span>}
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</div>
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))}
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{debugInfo && (
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<div className="mt-2 pt-2 border-t border-slate-800/40 text-slate-600">
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{debugInfo.error
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? <span className="text-red-500">Erreur: {debugInfo.error}</span>
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: <span>Refresh: {debugInfo.refreshed} ok / {debugInfo.failed} err / {debugInfo.total} total</span>
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}
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{debugInfo.details?.map((d: any, i: number) => (
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<div key={i} className="mt-0.5">
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#{d.event_id} {(d.event_name ?? '').slice(0, 25)} → <span className={d.result === 'ok' ? 'text-emerald-600' : 'text-red-500'}>{d.result}</span>
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{d.surprise_pct != null && <span className="text-slate-500 ml-1">surp:{d.surprise_pct}</span>}
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</div>
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))}
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</div>
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)}
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</div>
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)}
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</div>
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)
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