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feat: Introduce AI copilot for bulk product analysis and integrate a new product scoring engine.
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@@ -33,19 +33,28 @@ export function BulkAiAnalyzer() {
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const avgQty1 = rowsGroup1.length > 0 ? rowsGroup1.reduce((s: number, r: any) => s + (r.totalQuantite || 0), 0) / rowsGroup1.length : 0;
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const avgQty2 = rowsGroup2.length > 0 ? rowsGroup2.reduce((s: number, r: any) => s + (r.totalQuantite || 0), 0) / rowsGroup2.length : 0;
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const productPayloads: ProductAnalysisInput[] = rows.map(r => ({
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codein: r.codein,
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libelle1: r.libelle1 || "",
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totalCa: r.totalCa || 0,
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tauxMarge: r.tauxMarge || 0,
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totalQuantite: r.totalQuantite || 0,
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avgTotalQuantite: avgQty,
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avgQtyGroup1: avgQty1,
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avgQtyGroup2: avgQty2,
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storeCount: r.workingStores?.length || 1,
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sales12m: r.sales12m || {},
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codeGamme: r.codeGamme || null,
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}));
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const productPayloads: ProductAnalysisInput[] = rows.map(r => {
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const sc = r.workingStores?.length || 1;
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const weight = sc === 1 ? 2 : 1; // On ramène tout sur une base 2 magasins
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return {
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codein: r.codein,
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libelle1: r.libelle1 || "",
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totalCa: r.totalCa || 0,
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tauxMarge: r.tauxMarge || 0,
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totalQuantite: r.totalQuantite || 0,
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weightedTotalQuantite: (r.totalQuantite || 0) * weight,
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weightedTotalCa: (r.totalCa || 0) * weight,
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avgTotalQuantite: avgQty,
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avgQtyGroup1: avgQty1,
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avgQtyGroup2: avgQty2,
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storeCount: sc,
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sales12m: Object.fromEntries(
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Object.entries(r.sales12m || {}).map(([month, val]) => [month, val * weight])
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),
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codeGamme: r.codeGamme || null,
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};
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});
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setIsAnalyzing(true);
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let completed = 0;
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