From 0226585d4ea6010422934255602dc2e53c27cc64 Mon Sep 17 00:00:00 2001
From: Michael SCHAL <michaelschal@gmail.com>
Date: Wed, 25 Feb 2026 10:28:18 +0100
Subject: [PATCH] feat: Implement bulk AI product analysis, including prompt
 generation, insight processing, and a dedicated UI component.

---
 .../ai-copilot/business/analysis-engine.ts    |  4 +++-
 .../grid/components/bulk-ai-analyzer.tsx      | 20 ++++++++++++++++++-
 2 files changed, 22 insertions(+), 2 deletions(-)

diff --git a/src/features/ai-copilot/business/analysis-engine.ts b/src/features/ai-copilot/business/analysis-engine.ts
index 21229ea..0a870e2 100644
--- a/src/features/ai-copilot/business/analysis-engine.ts
+++ b/src/features/ai-copilot/business/analysis-engine.ts
@@ -19,7 +19,9 @@ Le score (0 à 100) est une mesure de performance RELATIVE au sein du rayon.
 4. CONCISE : 2 phrases maximum. Pas de blabla technique sur les percentiles, parle de "performance relative".
 
 --- FORMAT ATTENDU ---
-"[Recommandation] : [Justification factuelle incluant le Score et les axes clés]"`;
+"[Recommandation] : [Justification factuelle incluant le Score et les axes clés]"
+Exemple : "[A] : Score de 85/100 porté par une marge excellente de 45% et une forte croissance volume."
+Exemple : "[Z] : Score faible (12/100) en raison d'une baisse drastique du CA et d'une inactivité de 3 mois."`;
     }
 
     static generateUserMessage(p: ProductAnalysisInput): string {
diff --git a/src/features/grid/components/bulk-ai-analyzer.tsx b/src/features/grid/components/bulk-ai-analyzer.tsx
index 7f90c5e..6a28ec2 100644
--- a/src/features/grid/components/bulk-ai-analyzer.tsx
+++ b/src/features/grid/components/bulk-ai-analyzer.tsx
@@ -3,6 +3,7 @@
 import React, { useState, useRef } from "react";
 import { useGridStore } from "@/features/grid/store/use-grid-store";
 import { useAiCopilotStore } from "@/features/ai-copilot/store/use-ai-copilot-store";
+import { ScoringEngine } from "@/features/ai-copilot/business/scoring-engine";
 import { Sparkles, Loader2, CheckCircle2, XCircle } from "lucide-react";
 import { ProductRow, GammeCode } from "@/types/grid";
 import { ProductAnalysisInput } from "@/features/ai-copilot/models/ai-analysis.types";
@@ -55,7 +56,7 @@ export function BulkAiAnalyzer() {
             }
         });
 
-        const productPayloads: ProductAnalysisInput[] = rows.map((r) => {
+        const initialPayloads: ProductAnalysisInput[] = rows.map((r) => {
             const sc = r.workingStores?.length || 1;
             const weight = sc === 1 ? 2 : 1;
             const rb = rayonBenchmarks.get(r.libelleNiveau2 || "Général");
@@ -105,6 +106,23 @@ export function BulkAiAnalyzer() {
             };
         });
 
+        // 2. Calculer le scoring algorithmique pour chaque produit
+        const productPayloads = initialPayloads.map(p => {
+            const scoringRes = ScoringEngine.analyzeRayon(p, initialPayloads);
+            return {
+                ...p,
+                scoring: {
+                    compositeScore: scoringRes.compositeScore,
+                    decision: scoringRes.decision.recommendation,
+                    labelProfil: scoringRes.decision.labelProfil,
+                    isTop30Supplier: scoringRes.decision.isTop30Supplier,
+                    isRecent: scoringRes.decision.isRecent,
+                    isLastProduct: scoringRes.decision.isLastProduct,
+                    threshold: scoringRes.decision.threshold,
+                }
+            };
+        });
+
         setIsAnalyzing(true);
         let completed = 0;
         let errorsCount = 0;