Merge pull request #4 from R0m1k3/feat/qlik-network

feat(grid): replace ranking/AI/score with Qlik network data
2026-10-11 17:26:32 +02:00 · 2026-06-20 22:54:04 +02:00
commit 5a4ce70695
@@ -39,3 +39,5 @@ yarn-error.log*
 # typescript
 *.tsbuildinfo
 next-env.d.ts
 .playwright-mcp/
@@ -0,0 +1,89 @@
 # Intégration Qlik Sense — données réseau (~270 magasins)
 Remplace les heuristiques (ranking / IA / score) par les vraies données réseau
 La Foir'Fouille : **CA réseau, Qté vendue réseau, Nb magasins** par produit.
 ## Architecture livrée
 | Élément | Fichier |
 |---------|---------|
 | Connecteur Qlik (NTLM + QIX websocket) | `src/lib/qlik-client.ts` |
 | Cache lecture/upsert | `src/lib/qlik-network-cache.ts` |
 | Table cache | `qlik_network_metrics` (`src/db/schema.ts`, créée par `scripts/db-init.js`) |
 | Route de sync (admin) | `POST /api/qlik/sync` (`src/app/api/qlik/sync/route.ts`) |
 | Bouton UI | `src/features/grid/components/sync-qlik-button.tsx` |
 | Jointure grille | `enrichWithNetworkMetrics()` dans `src/features/grid/api/get-product-rows.ts` (Phase 8) |
 | Colonnes grille | CA réseau / Qté réseau / Magasins (/270) / % présence (`heatmap-grid.tsx`) |
 Retirés : ranking (champs/query/colonnes), analyse IA (routes `/api/ai/*`, `bulk-ai-analyzer`,
 dossier `ai-copilot`), score (`score-engine.ts`, colonne score).
 ## Auth — NTLM + ticket SSO (✅ TESTÉ, marche)
 Flux implémenté dans `qlik-client.ts` / `scripts/qlik-discover.mjs` :
 1. `GET /hub/` (non authentifié) → 302, on extrait le `targetId`.
 2. **NTLM** (login `FFSCH`, **domaine vide**, pas `FOIRFOUILLE`) sur
   `/internal_windows_authentication/?targetId=…` → 302 vers `/hub/?qlikTicket=XXX`.
 3. `GET /hub/?qlikTicket=XXX` → Qlik pose le cookie **`X-Qlik-Session`**.
 4. Cookie + Xrfkey → QRS REST (✅) et Engine websocket.
 ⚠️ Domaine NTLM **vide** (comme `requests_ntlm("FFSCH", pwd)`). Forcer `FOIRFOUILLE` → 401.
 Testé depuis l'extérieur : auth + QRS OK, **147 apps** côté admin (2 visibles pour FFSCH).
 ## Discovery (✅ FAITE)
 **App réseau article-niveau = "Magasins Vision Consolidée"** (stream Magasin Big Data) :
 - `QLIK_APP_NETWORK = 9872ee6e-d64a-4b43-984a-076bf1f7f647`
 - dim `QLIK_DIM_CODE_ARTICLE_ID = fcd239e5-288b-4830-a047-0e3d7665d971` (**Article Code**)
 - CA `QLIK_MEAS_CA_ID = 43a76088-86fa-402e-a80e-0efd7701b3e1` (**CA N**)
 - Qté `QLIK_MEAS_QTE_ID = 7b40caf1-be4b-4811-8d45-50acde33e715` (**Quantité N**)
 - nb mag `QLIK_MEAS_NBMAG_ID = 8b63fae5-db2f-4e4c-8618-f3e9d60b6b3b` (**Magasin Ventes Nb N**)
 Ces GUID sont déjà les **défauts** dans `qlik-client.ts` (hypercube par `qLibraryId`).
 (App "CA Foirfouille" stream Réseau = `65b3ad21-…` : pas de dimension article → écartée.)
 ⚠️ **À confirmer par un échantillon de hypercube** (5 lignes) : que `Article Code` = code
 centrale `10000XXXXXX`, et que `Magasin Ventes Nb N` = nb magasins vendeurs. L'agent hermes
 (Playwright) peut le faire.
 ### Limite extraction depuis l'extérieur
 Le **websocket Engine renvoie 403** depuis un environnement externe (le proxy Qlik refuse
 l'upgrade ws hors contexte navigateur ; l'extraction hermes qui marche réutilise une session
 Playwright). Sur le **réseau corporate** (où tournera CollectFlow / où `/hub/` renvoie 401
 NTLM direct), le ws raw devrait passer. À valider en déployant `POST /api/qlik/sync` sur leur
 infra interne.
 ## Variables d'environnement (`.env.local`)
 ```
 QLIK_HOST=reporting-magasins.lafoirfouille.fr
 QLIK_USER=FFSCH
 QLIK_PWD=<mot de passe courant>
 QLIK_DOMAIN=          # VIDE (ne pas mettre FOIRFOUILLE — NTLM sans domaine)
 QLIK_TLS_INSECURE=true
 # Défauts déjà en dur dans qlik-client.ts (discovery 2026-06-20) :
 QLIK_APP_NETWORK=9872ee6e-d64a-4b43-984a-076bf1f7f647
 QLIK_DIM_CODE_ARTICLE_ID=fcd239e5-288b-4830-a047-0e3d7665d971
 QLIK_MEAS_CA_ID=43a76088-86fa-402e-a80e-0efd7701b3e1
 QLIK_MEAS_QTE_ID=7b40caf1-be4b-4811-8d45-50acde33e715
 QLIK_MEAS_NBMAG_ID=8b63fae5-db2f-4e4c-8618-f3e9d60b6b3b
 ```
 ## RESTE À FAIRE
 1. **Confirmer la sémantique des champs** (échantillon hypercube, via l'agent hermes/Playwright
   ou en déployant `/api/qlik/sync` en interne) : `Article Code` = code centrale `10000XXXXXX` ?
   `Magasin Ventes Nb N` = nb magasins vendeurs ? App bien réseau (270 magasins) ?
 2. **Exécuter le sync depuis le réseau interne** : le websocket Engine renvoie 403 depuis
   l'extérieur. Déployer `POST /api/qlik/sync` sur l'infra interne FF pour valider l'extraction.
 3. **Code centrale = `articles.artcentrale`** ✅ RÉSOLU. Confirmé via l'API FF
   `GET /api/articles/{no_id}` → champ `artcentrale` (ex `"10000167303"` = `10000`+6 chiffres).
   Ajouté au SELECT de `pgGetArticlesByFournisseur` (`a.artcentrale AS "codeCentrale"`) → propagé
   dans `ProductRow.codeCentrale` → jointure `enrichWithNetworkMetrics`. ⚠️ Vide pour la plupart
   des articles (seuls les référencés centralement en ont un). À valider que la valeur Qlik
   "Article Code" est bien au même format sur le premier vrai sync.
 Tant que le sync interne n'est pas exécuté, la grille fonctionne en **dégradation propre** :
 colonnes réseau vides, aucune erreur.
@@ -1,7 +1,7 @@
 /** @type {import('next').NextConfig} */
 const nextConfig = {
  output: "standalone",
-  serverExternalPackages: ["pg"],
+  serverExternalPackages: ["pg", "ws", "httpntlm"],
  experimental: {
    serverActions: {
      bodySizeLimit: "50mb",
@@ -22,6 +22,7 @@
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    "httpntlm": "^1.8.13",
    "jspdf": "^4.2.0",
    "jspdf-autotable": "^5.0.7",
    "lucide-react": "^0.575.0",
@@ -35,6 +36,7 @@
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    "zod": "^4.3.6",
    "zustand": "^5.0.11"
@@ -45,6 +47,7 @@
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    "@types/ws": "^8.18.1",
    "drizzle-kit": "^0.31.9",
    "eslint": "^9",
    "eslint-config-next": "16.1.6",
@@ -38,6 +38,9 @@ importers:
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        version: 4.4.0
      httpntlm:
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      jspdf:
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@@ -77,6 +80,9 @@ importers:
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      ws:
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@@ -102,6 +108,9 @@ importers:
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      '@types/ws':
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  detect-libc@2.1.2:
    resolution: {integrity: sha512-Btj2BOOO83o3WyH59e8MgXsxEQVcarkUOpEYrubB0urwnN10yQ364rsiByU11nZlqWYZm05i/of7io4mzihBtQ==}
    engines: {node: '>=8'}
@@ -3440,6 +3487,14 @@ packages:
    resolution: {integrity: sha512-4FbRdAX+bSdmo4AUFuS0WNiPz8NgFt+r8ThgNWmlrjQjt1Q7ZR9+zTlce2859x4KSXrwIsaeTqDoKQmtP8pLmQ==}
    engines: {node: '>= 0.8'}
  httpntlm@1.8.13:
    resolution: {integrity: sha512-2F2FDPiWT4rewPzNMg3uPhNkP3NExENlUGADRUDPQvuftuUTGW98nLZtGemCIW3G40VhWZYgkIDcQFAwZ3mf2Q==}
    engines: {node: '>=10.4.0'}
  httpreq@1.1.1:
    resolution: {integrity: sha512-uhSZLPPD2VXXOSN8Cni3kIsoFHaU2pT/nySEU/fHr/ePbqHYr0jeiQRmUKLEirC09SFPsdMoA7LU7UXMd/w0Kw==}
    engines: {node: '>= 6.15.1'}
  https-proxy-agent@7.0.6:
    resolution: {integrity: sha512-vK9P5/iUfdl95AI+JVyUuIcVtd4ofvtrOr3HNtM2yxC9bnMbEdp3x01OhQNnjb8IJYi38VlTE3mBXwcfvywuSw==}
    engines: {node: '>= 14'}
@@ -3705,6 +3760,9 @@ packages:
  jose@6.2.3:
    resolution: {integrity: sha512-YYVDInQKFJfR/xa3ojUTl8c2KoTwiL1R5Wg9YCydwH0x0B9grbzlg5HC7mMjCtUJjbQ/YnGEZIhI5tCgfTb4Hw==}
  js-md4@0.3.2:
    resolution: {integrity: sha512-/GDnfQYsltsjRswQhN9fhv3EMw2sCpUdrdxyWDOUK7eyD++r3gRhzgiQgc/x4MAv2i1iuQ4lxO5mvqM3vj4bwA==}
  js-tokens@4.0.0:
    resolution: {integrity: sha512-RdJUflcE3cUzKiMqQgsCu06FPu9UdIJO0beYbPhHN4k6apgJtifcoCtT9bcxOpYBtpD2kCM6Sbzg4CausW/PKQ==}
@@ -3838,24 +3896,28 @@ packages:
    engines: {node: '>= 12.0.0'}
    cpu: [arm64]
    os: [linux]
    libc: [glibc]
  lightningcss-linux-arm64-musl@1.32.0:
    resolution: {integrity: sha512-UpQkoenr4UJEzgVIYpI80lDFvRmPVg6oqboNHfoH4CQIfNA+HOrZ7Mo7KZP02dC6LjghPQJeBsvXhJod/wnIBg==}
    engines: {node: '>= 12.0.0'}
    cpu: [arm64]
    os: [linux]
    libc: [musl]
  lightningcss-linux-x64-gnu@1.32.0:
    resolution: {integrity: sha512-V7Qr52IhZmdKPVr+Vtw8o+WLsQJYCTd8loIfpDaMRWGUZfBOYEJeyJIkqGIDMZPwPx24pUMfwSxxI8phr/MbOA==}
    engines: {node: '>= 12.0.0'}
    cpu: [x64]
    os: [linux]
    libc: [glibc]
  lightningcss-linux-x64-musl@1.32.0:
    resolution: {integrity: sha512-bYcLp+Vb0awsiXg/80uCRezCYHNg1/l3mt0gzHnWV9XP1W5sKa5/TCdGWaR/zBM2PeF/HbsQv/j2URNOiVuxWg==}
    engines: {node: '>= 12.0.0'}
    cpu: [x64]
    os: [linux]
    libc: [musl]
  lightningcss-win32-arm64-msvc@1.32.0:
    resolution: {integrity: sha512-8SbC8BR40pS6baCM8sbtYDSwEVQd4JlFTOlaD3gWGHfThTcABnNDBda6eTZeqbofalIJhFx0qKzgHJmcPTnGdw==}
@@ -4122,6 +4184,9 @@ packages:
    resolution: {integrity: sha512-VP79XUPxV2CigYP3jWwAUFSku2aKqBH7uTAapFWCBqutsbmDo96KY5o8uh6U+/YSIn5OxJnXp73beVkpqMIGhA==}
    engines: {node: '>=18'}
  minimalistic-assert@1.0.1:
    resolution: {integrity: sha512-UtJcAD4yEaGtjPezWuO9wC4nwUnVH/8/Im3yEHQP4b67cXlD/Qr9hdITCU1xDbSEXg2XKNaP8jsReV7vQd00/A==}
  minimatch@10.2.5:
    resolution: {integrity: sha512-MULkVLfKGYDFYejP07QOurDLLQpcjk7Fw+7jXS2R2czRQzR56yHRveU5NDJEOviH+hETZKSkIk5c+T23GjFUMg==}
    engines: {node: 18 || 20 || >=22}
@@ -5072,6 +5137,9 @@ packages:
    resolution: {integrity: sha512-nWJ91DjeOkej/TA8pXQ3myruKpKEYgqvpw9lz4OPHj/NWFNluYrjbz9j01CJ8yKQd2g4jFoOkINCTW2I5LEEyw==}
    engines: {node: '>= 0.4'}
  underscore@1.12.1:
    resolution: {integrity: sha512-hEQt0+ZLDVUMhebKxL4x1BTtDY7bavVofhZ9KZ4aI26X9SRaE+Y3m83XUL1UP2jn8ynjndwCCpEHdUG+9pP1Tw==}
  undici-types@6.21.0:
    resolution: {integrity: sha512-iwDZqg0QAGrg9Rav5H4n0M64c3mkR59cJ6wQp+7C4nI0gsmExaedaYLNO44eT4AtBBwjbTiGPMlt2Md0T9H9JQ==}
@@ -5222,8 +5290,8 @@ packages:
  wrappy@1.0.2:
    resolution: {integrity: sha512-l4Sp/DRseor9wL6EvV2+TuQn63dMkPjZ/sp9XkghTEbV9KlPS1xUsZ3u7/IQO4wxtcFB4bgpQPRcR3QCvezPcQ==}
-  ws@8.20.1:
+  ws@8.21.0:
-    resolution: {integrity: sha512-It4dO0K5v//JtTXuPkfEOaI3uUN87iYPnqo/ZzqCoG3g8uhA66QUMs/SrM0YK7/NAu+r4LMh/9dq2A7k+rHs+w==}
+    resolution: {integrity: sha512-Vsp28b7DRcimFQvrqu2Wek3z1iYxDCWqHYB8Qsnk/S4RfaCQzPGPyBNuVjJV3cd6UiKtUtp6sNM77gWvzcCH+g==}
    engines: {node: '>=10.0.0'}
    peerDependencies:
      bufferutil: ^4.0.1
@@ -5898,7 +5966,7 @@ snapshots:
      google-auth-library: 10.6.2
      p-retry: 4.6.2
      protobufjs: 7.5.8
-      ws: 8.20.1
+      ws: 8.21.0
    optionalDependencies:
      '@modelcontextprotocol/sdk': 1.29.0(zod@4.4.3)
    transitivePeerDependencies:
@@ -7148,6 +7216,10 @@ snapshots:
  '@types/validate-npm-package-name@4.0.2': {}
  '@types/ws@8.18.1':
    dependencies:
      '@types/node': 20.19.41
  '@typescript-eslint/eslint-plugin@8.59.3(@typescript-eslint/parser@8.59.3(eslint@9.39.4(jiti@2.7.0))(typescript@5.9.3))(eslint@9.39.4(jiti@2.7.0))(typescript@5.9.3)':
    dependencies:
      '@eslint-community/regexpp': 4.12.2
@@ -7800,6 +7872,11 @@ snapshots:
  dequal@2.0.3: {}
  des.js@1.1.0:
    dependencies:
      inherits: 2.0.4
      minimalistic-assert: 1.0.1
  detect-libc@2.1.2: {}
  detect-node-es@1.1.0: {}
@@ -8699,6 +8776,15 @@ snapshots:
      statuses: 2.0.2
      toidentifier: 1.0.1
  httpntlm@1.8.13:
    dependencies:
      des.js: 1.1.0
      httpreq: 1.1.1
      js-md4: 0.3.2
      underscore: 1.12.1
  httpreq@1.1.1: {}
  https-proxy-agent@7.0.6:
    dependencies:
      agent-base: 7.1.4
@@ -8930,6 +9016,8 @@ snapshots:
  jose@6.2.3: {}
  js-md4@0.3.2: {}
  js-tokens@4.0.0: {}
  js-yaml@4.1.1:
@@ -9516,6 +9604,8 @@ snapshots:
  mimic-function@5.0.1: {}
  minimalistic-assert@1.0.1: {}
  minimatch@10.2.5:
    dependencies:
      brace-expansion: 5.0.6
@@ -10705,6 +10795,8 @@ snapshots:
      has-symbols: 1.1.0
      which-boxed-primitive: 1.1.1
  underscore@1.12.1: {}
  undici-types@6.21.0: {}
  unicorn-magic@0.3.0: {}
@@ -10902,7 +10994,7 @@ snapshots:
  wrappy@1.0.2: {}
-  ws@8.20.1: {}
+  ws@8.21.0: {}
  wsl-utils@0.3.1:
    dependencies:
@@ -96,6 +96,18 @@ async function main() {
        `);
        console.log("[DB Init] Table commande_cadences is verified/created.");
        await tempPool.query(`
            CREATE TABLE IF NOT EXISTS "qlik_network_metrics" (
                "code_centrale" varchar(20) PRIMARY KEY NOT NULL,
                "ca_reseau" numeric(16, 2),
                "qte_reseau" numeric(14, 2),
                "nb_magasins_reseau" integer,
                "periode" varchar(20),
                "fetched_at" timestamp DEFAULT now()
            );
        `);
        console.log("[DB Init] Table qlik_network_metrics is verified/created.");
        await tempPool.end();
        console.log("[DB Init] Initialization successful. Exiting.");
        process.exit(0);
@@ -0,0 +1,190 @@
 /**
 * Discovery Qlik Sense — autonome, à lancer à la main :
 *
 *   QLIK_PWD='<mot de passe>' node scripts/qlik-discover.mjs            # liste les apps
 *   QLIK_PWD='<mot de passe>' node scripts/qlik-discover.mjs <appGUID>  # + champs & mesures de l'app
 *
 * Env (défauts adaptés à La Foir'Fouille) :
 *   QLIK_HOST=reporting-magasins.lafoirfouille.fr
 *   QLIK_USER=FFSCH
 *   QLIK_DOMAIN=FOIRFOUILLE
 *   QLIK_PWD=<requis>
 *
 * But : récupérer le GUID de l'app réseau (~270 magasins) + les noms exacts du champ
 * "code article" et des mesures (CA / Qté / nb magasins) pour remplir .env.local :
 *   QLIK_APP_NETWORK / QLIK_DIM_CODE_ARTICLE / QLIK_MEAS_CA / QLIK_MEAS_QTE / QLIK_MEAS_NB_MAG
 */
 import httpntlm from "httpntlm";
 import { WebSocket } from "ws";
 import { randomBytes } from "node:crypto";
 process.env.NODE_TLS_REJECT_UNAUTHORIZED = "0"; // certif Qlik interne
 const HOST = process.env.QLIK_HOST || "reporting-magasins.lafoirfouille.fr";
 const USER = process.env.QLIK_USER || "FFSCH";
 // Domaine vide par défaut : requests_ntlm("FFSCH", pwd) marche sans domaine explicite.
 const DOMAIN = process.env.QLIK_DOMAIN || "";
 const PWD = process.env.QLIK_PWD || "";
 const APP = process.argv[2] || process.env.QLIK_APP_NETWORK || "";
 if (!PWD) {
    console.error("ERREUR: définis QLIK_PWD. Ex: QLIK_PWD='xxx' node scripts/qlik-discover.mjs");
    process.exit(1);
 }
 const xrfkey = randomBytes(12).toString("base64").replace(/[^a-zA-Z0-9]/g, "").slice(0, 16).padEnd(16, "0");
 function ntlmGet(path) {
    return new Promise((resolve, reject) => {
        httpntlm.get(
            {
                url: `https://${HOST}${path}`,
                username: USER,
                password: PWD,
                domain: DOMAIN,
                workstation: "",
                rejectUnauthorized: false,
                headers: { "X-Qlik-Xrfkey": xrfkey, "User-Agent": "Mozilla/5.0 CollectFlow" },
            },
            (err, res) => (err ? reject(err) : resolve(res)),
        );
    });
 }
 // Récupère un targetId en initiant une requête non authentifiée vers /hub/.
 async function getTargetId() {
    const res = await fetch(`https://${HOST}/hub/`, { redirect: "manual" });
    const loc = res.headers.get("location") || "";
    const m = loc.match(/targetId=([0-9a-f-]+)/i);
    return m ? m[1] : "";
 }
 // Flux SSO ticket Qlik :
 //   1. NTLM sur /internal_windows_authentication/?targetId=... -> 302 /hub/?qlikTicket=XXX
 //   2. GET /hub/?qlikTicket=XXX -> Qlik valide le ticket et pose le cookie X-Qlik-Session
 async function authCookie() {
    const tid = await getTargetId();
    const res = await ntlmGet(`/internal_windows_authentication/?targetId=${tid}&xrfkey=${xrfkey}`);
    const loc = res.headers.location || "";
    const ticket = (loc.match(/qlikTicket=([^&\s]+)/) || [])[1];
    console.log(`  [auth] NTLM HTTP ${res.statusCode}, ticket=${ticket ? "oui" : "non"}`);
    if (!ticket) throw new Error(`pas de qlikTicket (HTTP ${res.statusCode})`);
    // Échange ticket -> cookies de session (on garde TOUS les cookies posés)
    const r2 = await fetch(loc, { redirect: "manual" });
    const sc = typeof r2.headers.getSetCookie === "function"
        ? r2.headers.getSetCookie()
        : (r2.headers.get("set-cookie") ? [r2.headers.get("set-cookie")] : []);
    const pairs = sc.map((c) => c.split(";")[0]);
    const hasSession = pairs.some((c) => /X-Qlik-Session/i.test(c));
    console.log(`  [auth] échange ticket HTTP ${r2.status}, cookies=${JSON.stringify(pairs.map(p=>p.split("=")[0]))}`);
    if (!hasSession) throw new Error("ticket non échangé contre un cookie de session");
    return pairs.join("; ");
 }
 // QRS via cookie de session + Xrfkey.
 async function qrsGet(path, cookie) {
    const sep = path.includes("?") ? "&" : "?";
    const res = await fetch(`https://${HOST}${path}${sep}xrfkey=${xrfkey}`, {
        headers: { Cookie: cookie, "X-Qlik-Xrfkey": xrfkey, Accept: "application/json" },
    });
    if (res.status !== 200) throw new Error(`QRS ${path} HTTP ${res.status}`);
    return res.json();
 }
 async function qrsApps(cookie) {
    const apps = await qrsGet("/qrs/app", cookie);
    return apps.map((a) => ({ id: a.id, name: a.name, published: a.published, stream: a.stream?.name }));
 }
 function engine(appGuid, cookie) {
    const ident = randomBytes(8).toString("hex");
    const url = `wss://${HOST}/app/${appGuid}/identity/${ident}?Xrfkey=${xrfkey}`;
    const ws = new WebSocket(url, {
        headers: { Cookie: cookie, "X-Qlik-Xrfkey": xrfkey, "User-Agent": "Mozilla/5.0" },
        rejectUnauthorized: false,
    });
    let id = 1;
    const pending = new Map();
    const ready = new Promise((resolve, reject) => {
        ws.on("message", (raw) => {
            const m = JSON.parse(raw.toString());
            if (m.method === "OnConnected") return resolve();
            if (m.id != null && pending.has(m.id)) {
                const p = pending.get(m.id);
                pending.delete(m.id);
                m.error ? p.reject(new Error(JSON.stringify(m.error))) : p.resolve(m.result);
            }
        });
        ws.on("unexpected-response", (_req, res) => {
            let body = "";
            res.on("data", (d) => (body += d));
            res.on("end", () => reject(new Error(`ws ${res.statusCode} server=${res.headers.server} wwwauth=${res.headers["www-authenticate"]} body=${body.slice(0, 120)}`)));
        });
        ws.on("error", reject);
    });
    const rpc = (method, params, handle = -1) =>
        new Promise((resolve, reject) => {
            const i = id++;
            pending.set(i, { resolve, reject });
            ws.send(JSON.stringify({ jsonrpc: "2.0", id: i, handle, method, params }));
        });
    return { ready, rpc, close: () => ws.close() };
 }
 async function dumpFieldsMeasures(appGuid, cookie) {
    const e = engine(appGuid, cookie);
    await e.ready;
    const open = await e.rpc("OpenDoc", { qDocName: appGuid });
    const doc = open.qReturn.qHandle;
    // Liste des champs
    const fl = await e.rpc("CreateSessionObject", {
        qProp: { qInfo: { qType: "FieldList" }, qFieldListDef: { qShowSystem: false, qShowHidden: false, qShowSemantic: true, qShowSrcTables: true } },
    }, doc);
    const flLayout = await e.rpc("GetLayout", {}, fl.qReturn.qHandle);
    const fields = (flLayout.qLayout.qFieldList.qItems || []).map((f) => f.qName);
    // Liste des mesures (master items)
    const ml = await e.rpc("CreateSessionObject", {
        qProp: { qInfo: { qType: "MeasureList" }, qMeasureListDef: { qType: "measure", qData: { title: "/qMetaDef/title", expr: "/qMeasure/qDef" } } },
    }, doc);
    const mlLayout = await e.rpc("GetLayout", {}, ml.qReturn.qHandle);
    const measures = (mlLayout.qLayout.qMeasureList.qItems || []).map((m) => ({
        title: m.qMeta?.title ?? m.qData?.title,
        expr: m.qData?.expr,
    }));
    e.close();
    return { fields, measures };
 }
 (async () => {
    try {
        console.log(`Auth NTLM ${DOMAIN}\\${USER} @ ${HOST} ...`);
        const cookie = await authCookie();
        console.log("✓ Authentifié.\n");
        const apps = await qrsApps(cookie);
        console.log(`=== ${apps.length} apps ===`);
        for (const a of apps) console.log(`  ${a.id}  [${a.stream || "-"}]  ${a.name}`);
        if (APP) {
            console.log(`\n=== Champs & mesures de l'app ${APP} ===`);
            const { fields, measures } = await dumpFieldsMeasures(APP, cookie);
            console.log(`\n-- Champs (${fields.length}) --`);
            for (const f of fields) console.log(`  ${f}`);
            console.log(`\n-- Mesures master (${measures.length}) --`);
            for (const m of measures) console.log(`  ${m.title}  =  ${m.expr}`);
            console.log(`\n→ Repère le champ "code article", et les expressions CA / Qté / nb magasins,`);
            console.log(`  puis remplis QLIK_APP_NETWORK / QLIK_DIM_CODE_ARTICLE / QLIK_MEAS_* dans .env.local.`);
        } else {
            console.log(`\n→ Relance avec le GUID de l'app réseau pour lister ses champs & mesures :`);
            console.log(`  QLIK_PWD='...' node scripts/qlik-discover.mjs <appGUID>`);
        }
    } catch (e) {
        console.error("ERREUR:", e.message);
        process.exit(1);
    }
 })();
@@ -1,95 +0,0 @@
 import { NextRequest, NextResponse } from "next/server";
 import { getSavedDatabaseConfig } from "@/features/settings/actions";
 import { OpenRouterClient } from "@/features/ai-copilot/data/open-router-client";
 import { ProductAnalysisInput, SiteMonthlyData } from "@/features/ai-copilot/models/ai-analysis.types";
 import { getMensuelByArticles, buildLast12MonthsRange } from "@/lib/api-ff-client";
 // Limite max acceptable pour la route (Node.js self-hosted).
 // Evite que le process tourne indéfiniment en cas de deadlock.
 export const maxDuration = 55;
 const SITE_LABELS: Record<string, string> = { "292": "Frouard", "579": "Houdemont" };
 export async function POST(req: NextRequest) {
    const config = await getSavedDatabaseConfig();
    const apiKey = process.env.OPENROUTER_API_KEY || config?.openRouterKey;
    const model = config?.openRouterModel || "google/gemini-2.0-flash-001";
    if (!apiKey) {
        console.error("[AI] OPENROUTER_API_KEY is missing.");
        return NextResponse.json({ error: "OPENROUTER_API_KEY not configured. Please set it in Settings." }, { status: 503 });
    }
    try {
        const body: ProductAnalysisInput = await req.json();
        // Si noid est fourni, enrichir avec les données mensuelles per-site depuis FF Nancy
        let enrichedBody = body;
        if (body.noid) {
            try {
                const { dateDebut, dateFin } = buildLast12MonthsRange();
                const mensuelMap = await getMensuelByArticles(
                    [{ codein: body.codein, noid: body.noid, libelle1: body.libelle1, codefou: body.codeFournisseur ?? "" }],
                    dateDebut, dateFin, 1
                );
                const entries = mensuelMap.get(body.codein) ?? [];
                const siteMonthlyData: SiteMonthlyData[] = entries
                    .filter(e => e.site === "292" || e.site === "579")
                    .map(e => ({
                        site: SITE_LABELS[e.site] ?? e.site,
                        mois: e.mois,
                        ventes_qte: Math.abs(parseFloat(e.ventes?.qte_vendue ?? "0") || 0),
                        ventes_ca: Math.abs(parseFloat(e.ventes?.ca_ht ?? "0") || 0),
                        marge: parseFloat(e.ventes?.marge ?? "0") || 0,
                        stock_fin_mois: parseFloat(e.stock_fin_mois ?? "0") || 0,
                        receptions_qte: Math.abs(parseFloat(e.receptions?.qte_recue ?? "0") || 0),
                    }));
                if (siteMonthlyData.length > 0) {
                    enrichedBody = { ...body, siteMonthlyData };
                    console.log(`[AI] Enriched ${body.codein} with ${siteMonthlyData.length} site-monthly entries`);
                }
            } catch (err) {
                console.warn(`[AI] Failed to fetch mensuel for ${body.codein}:`, err);
                // Dégradation gracieuse — continuer sans données mensuelles
            }
        }
        const FALLBACK_MODEL = "google/gemini-2.0-flash-001";
        let client = new OpenRouterClient({ apiKey, model });
        let result;
        try {
            result = await client.analyzeProduct(enrichedBody);
        } catch (modelErr) {
            // If configured model fails (e.g., deprecated), retry with fallback
            const msg = modelErr instanceof Error ? modelErr.message : "";
            if (model !== FALLBACK_MODEL && (msg.includes("400") || msg.includes("404") || msg.includes("OpenRouter error"))) {
                console.warn(`[AI] Model "${model}" failed (${msg}), retrying with fallback ${FALLBACK_MODEL}`);
                client = new OpenRouterClient({ apiKey, model: FALLBACK_MODEL });
                result = await client.analyzeProduct(enrichedBody);
            } else {
                throw modelErr;
            }
        }
        return NextResponse.json(result);
    } catch (err) {
        if (err instanceof Error && err.message === "rate_limited") {
            return NextResponse.json({ error: "rate_limited", retryAfter: 30 }, { status: 429 });
        }
        // Timeout explicite déclenché par l'AbortController du client
        if (err instanceof Error && err.message === "timeout") {
            console.warn(`[AI] Timeout for product analysis — OpenRouter too slow.`);
            return NextResponse.json({ error: "timeout", retryAfter: 5 }, { status: 504 });
        }
        const msg = err instanceof Error ? err.message : "Unknown error";
        // Propager l'état de surcharge Open Router (502 Gateway, 503 Unavailable, 529 Overloaded)
        if (msg.includes("502") || msg.includes("503") || msg.includes("529") || msg.includes("Bad Gateway") || msg.includes("overloaded")) {
            console.warn(`[AI] External API overload detected: ${msg}`);
            return NextResponse.json({ error: "gateway_timeout", detail: msg }, { status: 502 });
        }
        return NextResponse.json({ error: msg }, { status: 500 });
    }
 }
@@ -1,176 +0,0 @@
 import { NextRequest, NextResponse } from "next/server";
 import { z } from "zod";
 import { getSavedDatabaseConfig } from "@/features/settings/actions";
 const BatchAnalyzeSchema = z.object({
    rayon: z.string(),
    supplierTotalCa: z.number().optional(),
    supplierTotalMarge: z.number().optional(),
    supplierStats: z.object({
        totalProducts: z.number(),
        medianScore: z.number(),
        scoreDistribution: z.object({
            above70: z.number(),
            between30and70: z.number(),
            below30: z.number(),
        }),
        maxStoreCount: z.number(),
        nomenclature2Count: z.number(),
    }).optional(),
    products: z.array(z.object({
        codein: z.string(),
        nom: z.string().nullable().optional(),
        ca: z.number().nullable().optional(),
        adjustedCaWeight: z.number().optional().default(0),
        weightInNomenclature2: z.number().optional().default(0),
        nomenclature2Weight: z.number().optional().default(0),
        ventes: z.number().nullable().optional(),
        marge: z.number().nullable().optional(),
        scorePercentile: z.number().optional().default(0),
        moisActifs: z.number().optional().default(0),
        storeCount: z.number().optional().default(1),
        nomenclature: z.string().nullable().optional(),
    })),
 });
 export async function POST(req: NextRequest) {
    const config = await getSavedDatabaseConfig();
    const apiKey = process.env.OPENROUTER_API_KEY || config?.openRouterKey;
    const model = config?.openRouterModel || "google/gemini-2.0-flash-001";
    if (!apiKey) {
        console.error("[batch-analyze] API key manquante.");
        return NextResponse.json({ error: "Clé API OpenRouter manquante. Configurez-la dans les Paramètres." }, { status: 503 });
    }
    try {
        const body = await req.json();
        const parsed = BatchAnalyzeSchema.safeParse(body);
        if (!parsed.success) {
            return NextResponse.json({ error: "Format de données invalide." }, { status: 400 });
        }
        const { rayon, products, supplierTotalCa, supplierTotalMarge, supplierStats } = parsed.data;
        const statsContext = supplierStats
            ? `Fournisseur : ${supplierStats.totalProducts} produits, ${supplierStats.nomenclature2Count} categories N2, ${supplierStats.maxStoreCount} magasins.
 CA total : ${supplierTotalCa?.toLocaleString('fr-FR') ?? '?'} EUR. Marge totale : ${supplierTotalMarge?.toLocaleString('fr-FR') ?? '?'} EUR.
 Score median du fournisseur : ${supplierStats.medianScore}/100.`
            : "";
        const systemPrompt = `Tu es un expert en assortiment retail. Categorise chaque produit : A (garder), C (saisonnier), Z (sortir).
 ${statsContext}
 DONNEES PAR PRODUIT :
 - weightInNomenclature2 : % du CA du produit DANS sa categorie N2. C'est le critere le plus important.
 - adjustedCaWeight : % du CA du produit dans le total fournisseur (extrapole au reseau).
 - nomenclature2Weight : % du CA de toute la categorie N2 dans le fournisseur.
 - scorePercentile : rang du produit parmi tous les produits du fournisseur (0-100, 50 = median).
 - moisActifs : nombre de mois avec des ventes sur les 12 derniers mois.
 - marge : taux de marge (%).
 REGLES DE DECISION (applique dans l'ordre) :
 REGLE 1 — PILIER DE CATEGORIE → A
 Si weightInNomenclature2 >= 5% → le produit est un pilier de sa categorie → A.
 REGLE 2 — ROTATION REGULIERE → A
 Si moisActifs >= 8 → produit de fond de rayon avec rotation reguliere → A.
 REGLE 3 — BON PERFORMEUR → A
 Si scorePercentile >= 50 ET moisActifs >= 4 → au-dessus de la moyenne → A.
 REGLE 4 — SAISONNIER → C
 Si moisActifs entre 2 et 4 ET les ventes sont concentrees sur des mois specifiques → C.
 REGLE 5 — SORTIE → Z
 Si le produit ne remplit AUCUNE des regles 1-4, c'est un candidat Z.
 Un produit ne doit etre Z que s'il cumule : weightInNomenclature2 faible + moisActifs < 5 + scorePercentile < 30.
 REGLE DE COHERENCE OBLIGATOIRE :
 Compare les produits ENTRE EUX dans ce lot. Si le produit X a un meilleur scorePercentile ET un meilleur weightInNomenclature2 que le produit Y, alors X doit avoir une recommandation >= Y. Ne mets JAMAIS en Z un produit meilleur qu'un autre en A.
 REPONDS EN JSON VALIDE uniquement :
 {
  "results": [
    {
      "codein": "ID",
      "recommandationGamme": "A|C|Z",
      "isDuplicate": false,
      "justificationCourte": "N2: X%, Perc: Y, Mois: Z -> Regle N"
    }
  ]
 }`;
        const userPrompt = `${products.length} produits du rayon "${rayon}" (sur ${supplierStats?.totalProducts ?? products.length} au total).
 ${JSON.stringify(products, null, 2)}`;
        const FALLBACK_MODEL = "google/gemini-2.0-flash-001";
        const tryModel = async (modelToTry: string) => fetch("https://openrouter.ai/api/v1/chat/completions", {
            method: "POST",
            headers: { "Authorization": `Bearer ${apiKey}`, "Content-Type": "application/json" },
            body: JSON.stringify({
                model: modelToTry,
                messages: [
                    { role: "system", content: systemPrompt },
                    { role: "user", content: userPrompt }
                ],
                response_format: { type: "json_object" },
                temperature: 0.1,
            }),
        });
        let response = await tryModel(model);
        // Fallback if configured model is deprecated/not found
        if (!response.ok && response.status === 400 && model !== FALLBACK_MODEL) {
            console.warn(`[batch-analyze] Model "${model}" returned 400, retrying with fallback ${FALLBACK_MODEL}`);
            response = await tryModel(FALLBACK_MODEL);
        }
        if (response.status === 429) {
            const retryAfter = response.headers.get("Retry-After") || response.headers.get("x-ratelimit-reset-requests");
            const waitSeconds = retryAfter ? parseInt(retryAfter, 10) : 60;
            console.warn(`[batch-analyze] Rate limited. Retry after ${waitSeconds}s.`);
            return NextResponse.json({ error: "rate_limited", retryAfter: waitSeconds }, { status: 429 });
        }
        if (!response.ok) {
            const err = await response.text();
            console.error("OpenRouter API Error:", response.status, err);
            return NextResponse.json({ error: "Erreur lors de l'appel à OpenRouter.", status: response.status }, { status: response.status });
        }
        const data = await response.json();
        const content: string = data.choices?.[0]?.message?.content ?? "";
        console.log("[batch-analyze] Raw LLM response:", content.slice(0, 500));
        if (!content) {
            return NextResponse.json({ error: "Réponse vide du modèle." }, { status: 500 });
        }
        let jsonStr = content;
        const jsonBlock = content.match(/```json\s*([\s\S]*?)\s*```/);
        if (jsonBlock) {
            jsonStr = jsonBlock[1];
        } else {
            const start = content.indexOf("{");
            const end = content.lastIndexOf("}");
            if (start !== -1 && end !== -1) {
                jsonStr = content.slice(start, end + 1);
            }
        }
        const resultJson = JSON.parse(jsonStr);
        console.log("[batch-analyze] Parsed results count:", resultJson?.results?.length ?? "N/A");
        return NextResponse.json(resultJson);
    } catch (error) {
        console.error("Batch Analyze Error:", error);
        return NextResponse.json({ error: "Erreur interne du serveur." }, { status: 500 });
    }
 }
@@ -1,96 +0,0 @@
 import { NextResponse } from "next/server";
 import { db } from "@/db";
 import { aiSupplierContext } from "@/db/schema";
 import { eq } from "drizzle-orm";
 import fs from "fs";
 import path from "path";
 // File system fallback for environments without PostgreSQL
 const DATA_DIR = path.join(process.cwd(), "data");
 const FALLBACK_FILE_PATH = path.join(DATA_DIR, "ai-context.json");
 function ensureFallbackFileExists() {
    if (!fs.existsSync(DATA_DIR)) {
        fs.mkdirSync(DATA_DIR, { recursive: true });
    }
    if (!fs.existsSync(FALLBACK_FILE_PATH)) {
        fs.writeFileSync(FALLBACK_FILE_PATH, JSON.stringify({}), "utf-8");
    }
 }
 function getFallbackContext(codeFournisseur: string): string {
    ensureFallbackFileExists();
    try {
        const data = JSON.parse(fs.readFileSync(FALLBACK_FILE_PATH, "utf-8"));
        return data[codeFournisseur] || "";
    } catch {
        return "";
    }
 }
 function saveFallbackContext(codeFournisseur: string, contextText: string) {
    ensureFallbackFileExists();
    try {
        const data = JSON.parse(fs.readFileSync(FALLBACK_FILE_PATH, "utf-8"));
        data[codeFournisseur] = contextText;
        fs.writeFileSync(FALLBACK_FILE_PATH, JSON.stringify(data, null, 2), "utf-8");
    } catch (err) {
        console.error("Error saving fallback context:", err);
    }
 }
 export async function GET(request: Request) {
    const { searchParams } = new URL(request.url);
    const codeFournisseur = searchParams.get("fournisseur");
    if (!codeFournisseur) {
        return NextResponse.json({ error: "Fournisseur manquant" }, { status: 400 });
    }
    try {
        const result = await db.select()
            .from(aiSupplierContext)
            .where(eq(aiSupplierContext.codeFournisseur, codeFournisseur))
            .limit(1);
        return NextResponse.json({ context: result[0]?.context || "" });
    } catch (error) {
        console.warn("DB fetch failed, using fallback JSON for AI context.");
        return NextResponse.json({ context: getFallbackContext(codeFournisseur) });
    }
 }
 export async function POST(request: Request) {
    try {
        const body = await request.json();
        const { codeFournisseur, context } = body;
        if (!codeFournisseur) {
            return NextResponse.json({ error: "Fournisseur manquant" }, { status: 400 });
        }
        try {
            await db.insert(aiSupplierContext)
                .values({
                    codeFournisseur,
                    context: context || "",
                    updatedAt: new Date()
                })
                .onConflictDoUpdate({
                    target: aiSupplierContext.codeFournisseur,
                    set: {
                        context: context || "",
                        updatedAt: new Date()
                    }
                });
        } catch (dbError) {
            console.warn("DB insert failed, saving to fallback JSON.", dbError);
            saveFallbackContext(codeFournisseur, context || "");
        }
        return NextResponse.json({ success: true });
    } catch (error) {
        console.error("Error in AI context API:", error);
        return NextResponse.json({ error: "Erreur lors de la sauvegarde" }, { status: 500 });
    }
 }
@@ -0,0 +1,62 @@
 import { NextRequest, NextResponse } from "next/server";
 import { auth } from "@/lib/auth";
 import { fetchNetworkMetrics } from "@/lib/qlik-client";
 import { upsertNetworkMetrics } from "@/lib/qlik-network-cache";
 import { pgGetArticlesByFournisseur } from "@/lib/pg-ff-client";
 // Synchro potentiellement longue (extraction hypercube paginee).
 export const maxDuration = 300;
 /**
 * POST /api/qlik/sync?fournisseur=XXX
 * Tire de Qlik les metriques reseau des articles du fournisseur (par code centrale)
 * et met a jour le cache local. Admin uniquement.
 */
 export async function POST(req: NextRequest) {
    const session = await auth();
    if (!session || (session.user as { role?: string } | undefined)?.role !== "admin") {
        return NextResponse.json({ error: "Unauthorized" }, { status: 403 });
    }
    const fournisseur = req.nextUrl.searchParams.get("fournisseur");
    if (!fournisseur) {
        return NextResponse.json({ error: "Param 'fournisseur' requis" }, { status: 400 });
    }
    try {
        // Codes centraux des articles de ce fournisseur
        const articles = await pgGetArticlesByFournisseur(fournisseur);
        const codes = [
            ...new Set(
                articles
                    .map((a) => (a.codeCentrale ? String(a.codeCentrale).trim() : ""))
                    .filter(Boolean),
            ),
        ];
        if (codes.length === 0) {
            return NextResponse.json({
                success: true,
                fournisseur,
                fetched: 0,
                upserted: 0,
                message: "Aucun article avec code centrale pour ce fournisseur",
                fetchedAt: new Date().toISOString(),
            });
        }
        const metrics = await fetchNetworkMetrics(codes);
        const count = await upsertNetworkMetrics([...metrics.values()]);
        return NextResponse.json({
            success: true,
            fournisseur,
            requested: codes.length,
            fetched: metrics.size,
            upserted: count,
            fetchedAt: new Date().toISOString(),
        });
    } catch (e) {
        const msg = e instanceof Error ? e.message : String(e);
        console.error("[api/qlik/sync]", msg);
        return NextResponse.json({ success: false, error: msg }, { status: 500 });
    }
 }
@@ -104,6 +104,25 @@ export const commandeCadences = pgTable("commande_cadences", {
  ];
 });
 /**
 * Cache des métriques réseau Qlik Sense (~270 magasins La Foir'Fouille).
 * Clé = code centrale (format 10000XXXXXX). Rafraîchi par /api/qlik/sync.
 */
 export const qlikNetworkMetrics = pgTable("qlik_network_metrics", {
  /** Code centrale article (clé jointure Qlik ↔ FF) */
  codeCentrale: varchar("code_centrale", { length: 20 }).primaryKey(),
  /** CA réseau total du produit */
  caReseau: numeric("ca_reseau", { precision: 16, scale: 2 }),
  /** Quantité vendue réseau */
  qteReseau: numeric("qte_reseau", { precision: 14, scale: 2 }),
  /** Nombre de magasins travaillant le produit (sur ~270) */
  nbMagasinsReseau: integer("nb_magasins_reseau"),
  /** Période couverte (libre, ex "12m" ou "2025") */
  periode: varchar("periode", { length: 20 }),
  /** Dernière synchro depuis Qlik */
  fetchedAt: timestamp("fetched_at").defaultNow(),
 });
 /** AI Context rules per supplier (Epic: AI Context) */
 export const aiSupplierContext = pgTable("ai_supplier_context", {
  /** Supplier code serving as the primary key */
@@ -1,343 +0,0 @@
 /**
 * CollectFlow — Analysis Engine v6
 *
 * TypeScript fait le calcul, l'IA fait le jugement.
 * Les cas déterministes (stock mort, 0 ventes) sont traités AVANT l'IA.
 * L'IA reçoit un verdict pré-calculé et des signaux pré-calculés.
 */
 import type { ProductAnalysisInput, SiteMonthlyData } from "../models/ai-analysis.types";
 import type { ProductContextProfile } from "./context-profiler";
 export class AnalysisEngine {
    // -----------------------------------------------------------------------
    // SYSTEM PROMPT v6
    // -----------------------------------------------------------------------
    static generateSystemPrompt(): string {
        return `Tu es Mary, Senior Retail Strategist pour une enseigne discount d'équipement de la maison (type La Foir'Fouille).
 Tu analyses des produits d'un même fournisseur pour recommander A (garder) ou Z (sortir).
 ⚠️ IMPORTANT : Les produits sans vente et ceux avec CA < 100€ ET quantité < 30 ont DÉJÀ été
 classés Z automatiquement et ne te sont PAS soumis. N'applique PAS de règle de stock mort.
 📦 STOCK NÉGATIF : Un stock négatif = commande validée après mise en vente (normal en retail).
 Ne pas pénaliser.
 --- RÈGLE 1 : RÈGLE MANAGER (PRIORITÉ ABSOLUE) ---
 Si une section "RÈGLE MANAGER" est présente dans le message :
 → Détermine si CE produit est concerné par la règle
 → Si OUI : rule_applies = true, applique EXACTEMENT la consigne (A, B, C, D ou Z)
 → Si NON : rule_applies = false, passe à la Règle 2
 → IMPORTANT : Si la règle demande explicitement une Gamme B, C ou D, tu DOIS recommander B, C ou D (pas A ni Z).
 Si AUCUNE règle manager n'est fournie → Passer directement à la Règle 2.
 --- RÈGLE 2 : CONFIRMATION OU AJUSTEMENT DU VERDICT ---
 Chaque produit arrive avec un SCORE (0-100) et un VERDICT pré-calculé (A ou Z).
 Ce verdict est ta base de départ. Tu peux l'ajuster UNIQUEMENT dans ces cas :
 PROMOUVOIR (Z → A) : Le verdict pré-calculé est Z, MAIS :
  • Tendance en forte accélération (H2/H1 > 2.0)
  • ET réapprovisionnement récent (réceptions 3 derniers mois > 0)
  • ET score ≥ 35
  → Les 3 conditions doivent être remplies SIMULTANÉMENT.
 DÉGRADER (A → Z) : Le verdict pré-calculé est A, MAIS :
  • Tendance en effondrement (H2/H1 < 0.4)
  • ET aucune réception récente
  • ET score < 55 ⚠️ SI LE SCORE EST ≥ 55, TU NE PEUX JAMAIS DÉGRADER EN Z
  → Les 3 conditions doivent être remplies SIMULTANÉMENT.
  → Un score élevé (≥ 55) INTERDIT toute dégradation, quelle que soit la tendance.
 Si AUCUNE condition d'ajustement n'est remplie → CONFIRME le verdict pré-calculé.
 --- RÈGLE 3 : INFORMATIONS CONTEXTUELLES ---
 Note dans la justification (sans changer la décision) :
 • Si un magasin représente ≥ 80% des ventes → "porté par [magasin]"
 • Si produit protégé (nouveauté, dernière ref fournisseur) → le mentionner
 • Si un RANKING est fourni, mentionne la position et le percentile du produit (ex: "classé 45e / 5 000 produits, top 1%")
  → Le ranking est un signal contextuel qui RENFORCE le verdict :
    - Top 5% du réseau → signal fort pour garder en A
    - Top 20% du réseau → signal modéré pour garder en A
    - Bottom 30% du réseau → signal défavorable, cohérent avec Z
  → Le ranking seul ne change PAS le verdict, mais combiné avec d'autres signaux il peut justifier un ajustement
 --- FORMAT OBLIGATOIRE ---
 JSON uniquement, sans markdown.
 {
  "rule_applies": boolean,
  "recommendation": "A" | "B" | "C" | "D" | "Z",
  "justification": "2-3 phrases max. Cite le score et le signal clé."
 }
 IMPORTANT — Gammes disponibles :
 - A : Garder (performance correcte)
 - B : Gamme secondaire (uniquement si RÈGLE MANAGER l'ordonne)
 - C : Gamme saisonnière (uniquement si RÈGLE MANAGER l'ordonne)
 - D : Gamme à surveiller (uniquement si RÈGLE MANAGER l'ordonne)
 - Z : Sortir (sous-performance)
 SI AUCUNE RÈGLE MANAGER n'est définie, tu recommandes UNIQUEMENT A ou Z (jamais B, C, D spontanément).`;
    }
    // -----------------------------------------------------------------------
    // USER MESSAGE
    // -----------------------------------------------------------------------
    static generateUserMessage(p: ProductAnalysisInput): string {
        if (p.contextProfile) {
            return AnalysisEngine.buildContextualMessage(p, p.contextProfile);
        }
        return AnalysisEngine.buildLegacyMessage(p);
    }
    // -----------------------------------------------------------------------
    // Message contextuel enrichi (v6 — verdict pré-calculé)
    // -----------------------------------------------------------------------
    private static buildContextualMessage(
        p: ProductAnalysisInput,
        ctx: ProductContextProfile
    ): string {
        const lines: string[] = [];
        const storeLabel = ctx.storeCount > 1 ? `${ctx.storeCount} magasins` : `1 magasin`;
        // En-tête produit
        lines.push(`PRODUIT : ${ctx.libelle1} (${ctx.codein})`);
        lines.push(`CATÉGORIE : ${ctx.libelleNiveau2}`);
        lines.push(`DISTRIBUTION : ${storeLabel}`);
        if (p.prixVente) {
            lines.push(`PRIX VENTE : ${p.prixVente.toFixed(2)}€`);
        }
        lines.push("");
        // ⚠️ RÈGLE MANAGER EN PRIORITÉ 1
        if (p.supplierContext) {
            lines.push(`🎯 ═══════════════════════════════════════════════════════════════`);
            lines.push(`🎯 🎯 🎯      RÈGLE MANAGER (PRIORITÉ ABSOLUE)      🎯 🎯 🎯`);
            lines.push(`═══════════════════════════════════════════════════════════════`);
            lines.push(``);
            lines.push(`RÈGLE DÉFINIE PAR LE MANAGER :`);
            lines.push(`"${p.supplierContext}"`);
            lines.push(``);
            lines.push(`PRODUIT ANALYSÉ : "${ctx.libelle1}"`);
            lines.push(`CATÉGORIE : ${ctx.libelleNiveau2}`);
            lines.push(``);
            lines.push(`⚠️ INSTRUCTION CRITIQUE :`);
            lines.push(`1. Analyse si CE produit est concerné par la règle ci-dessus`);
            lines.push(`2. Si OUI :`);
            lines.push(`   - rule_applies = true`);
            lines.push(`   - Applique EXACTEMENT la consigne (si la règle dit "Gamme B", tu DOIS mettre "B")`);
            lines.push(`   - IGNORE complètement la Règle 2`);
            lines.push(`3. Si NON :`);
            lines.push(`   - rule_applies = false`);
            lines.push(`   - Applique la Règle 2 normalement`);
            lines.push(`═══════════════════════════════════════════════════════════════`);
            lines.push("");
        }
        // Verdict pré-calculé
        const score = p.scoring?.score ?? p.score ?? 0;
        const verdict = p.scoring?.verdict ?? (score >= 45 ? "A" : "Z");
        const quadrant = ctx.quadrantLabel || p.scoring?.quadrant || "N/A";
        lines.push(`--- VERDICT PRÉ-CALCULÉ ---`);
        lines.push(`• Score : ${score}/100`);
        lines.push(`• Verdict : ${verdict}`);
        lines.push(`• Quadrant : ${ctx.quadrantEmoji} ${quadrant}`);
        if (ctx.isProtected) {
            lines.push(`• ⚠️ Protection : ${ctx.protectionReason}`);
        }
        lines.push("");
        // Performance
        const upsm = p.unitsPerStorePerMonth ?? (ctx.qtyPerStore / Math.max(ctx.regularityScore, 3));
        const cpsm = (ctx.caPerStore / 12);
        lines.push(`--- PERFORMANCE ---`);
        lines.push(`• CA réseau : ${ctx.totalCaRaw.toLocaleString('fr-FR')}€ (${cpsm.toFixed(1)}€/mag/mois)`);
        lines.push(`• Quantité : ${ctx.totalQtyRaw} unités (${upsm.toFixed(2)} uté/mag/mois)`);
        lines.push(`• Marge : ${ctx.tauxMarge.toFixed(1)}%`);
        lines.push(`• Régularité : ${ctx.regularityScore}/12 mois actifs`);
        lines.push("");
        // Position dans le lot
        lines.push(`--- POSITION DANS LE LOT (${ctx.lotSize} produits) ---`);
        lines.push(`• Percentile CA : ${ctx.percentileCa}e`);
        lines.push(`• Percentile Volume : ${ctx.percentileQty}e`);
        lines.push(`• Poids CA fournisseur : ${ctx.weightCaFournisseur.toFixed(1)}%`);
        lines.push("");
        // Ranking réseau & magasin (avec percentile contextuel)
        if (p.rankingCa != null || p.rankingQte != null || p.rankingMagCa != null || p.rankingMagQte != null) {
            const total = p.totalRankedProducts ?? 0;
            const totalLabel = total > 0 ? ` / ${total.toLocaleString('fr-FR')} produits` : "";
            lines.push(`--- RANKING RÉSEAU (${total > 0 ? total.toLocaleString('fr-FR') : "?"} produits vendus sur la période) ---`);
            if (p.rankingCa != null) {
                const pctCa = total > 0 ? ((p.rankingCa / total) * 100).toFixed(1) : "?";
                lines.push(`• Classement CA réseau : ${p.rankingCa}e${totalLabel} (top ${pctCa}%)`);
            }
            if (p.rankingQte != null) {
                const pctQte = total > 0 ? ((p.rankingQte / total) * 100).toFixed(1) : "?";
                lines.push(`• Classement Qté réseau : ${p.rankingQte}e${totalLabel} (top ${pctQte}%)`);
            }
            if (p.rankingMagCa != null) lines.push(`• Classement CA magasin : ${p.rankingMagCa}e`);
            if (p.rankingMagQte != null) lines.push(`• Classement Qté magasin : ${p.rankingMagQte}e`);
            lines.push(`• Contexte : ce fournisseur a ${ctx.lotSize} produits dans le lot analysé`);
            lines.push("");
        }
        // Signaux pré-calculés (si données mensuelles disponibles)
        if (p.siteMonthlyData && p.siteMonthlyData.length > 0) {
            const signals = AnalysisEngine.computeSignals(p.siteMonthlyData);
            lines.push(`--- SIGNAUX ---`);
            lines.push(`• Tendance : ${signals.tendanceLabel}`);
            lines.push(`• Réapprovisionnement : ${signals.reappLabel}`);
            if (signals.asymLabel) {
                lines.push(`• Asymétrie magasins : ${signals.asymLabel}`);
            }
            lines.push(`• Inactivité : ${ctx.inactivityMonths} mois sans vente en fin de fenêtre`);
            lines.push("");
        }
        // Stock & approvisionnement
        const hasStockData = ctx.stockCoverage !== undefined || ctx.isLowStock || ctx.isDeadInventory || ctx.isCommandeEnCours;
        if (hasStockData) {
            lines.push(`--- STOCK & APPROVISIONNEMENT ---`);
            if (ctx.stockCoverage > 0) {
                lines.push(`• Couverture stock : ${ctx.stockCoverage.toFixed(1)} mois de ventes en stock`);
            }
            if (ctx.isLowStock) {
                lines.push(`• ⚠️ Stock faible : moins d'un PCB disponible`);
            }
            if (ctx.isDeadInventory) {
                lines.push(`• ⚠️ Stock dormant : pas de vente depuis > 90 jours`);
            }
            if (ctx.isCommandeEnCours) {
                lines.push(`• Commande en cours : réapprovisionnement prévu`);
            }
            lines.push("");
        }
        lines.push(`Génère UNIQUEMENT le JSON :`);
        return lines.join("\n");
    }
    // -----------------------------------------------------------------------
    // Calcul des signaux à partir des données mensuelles
    // -----------------------------------------------------------------------
    private static computeSignals(siteMonthlyData: SiteMonthlyData[]): {
        tendanceLabel: string;
        reappLabel: string;
        asymLabel: string;
    } {
        const sortedMonths = [...new Set(siteMonthlyData.map(r => r.mois))].sort();
        const midIdx = Math.floor(sortedMonths.length / 2);
        const h1Months = new Set(sortedMonths.slice(0, midIdx));
        const h2Months = new Set(sortedMonths.slice(midIdx));
        const last3Months = new Set(sortedMonths.slice(-3));
        let h1Qty = 0, h2Qty = 0;
        const qteBySite: Record<string, number> = {};
        let recentReceptions = 0;
        let recentSales = 0;
        for (const r of siteMonthlyData) {
            if (h1Months.has(r.mois)) h1Qty += r.ventes_qte;
            if (h2Months.has(r.mois)) h2Qty += r.ventes_qte;
            qteBySite[r.site] = (qteBySite[r.site] ?? 0) + r.ventes_qte;
            if (last3Months.has(r.mois)) {
                recentReceptions += r.receptions_qte;
                recentSales += r.ventes_qte;
            }
        }
        const tendanceRatio = h1Qty > 0 ? h2Qty / h1Qty : (h2Qty > 0 ? Infinity : 1);
        // Signal tendance
        let tendanceLabel: string;
        if (h1Qty === 0 && h2Qty > 0) {
            tendanceLabel = `Produit entrant (H1: 0 → H2: ${h2Qty} uté) — premières ventes récentes`;
        } else if (tendanceRatio < 0.4) {
            tendanceLabel = `Effondrement (H1: ${h1Qty} uté → H2: ${h2Qty} uté, ratio ${tendanceRatio.toFixed(2)})`;
        } else if (tendanceRatio > 2.0) {
            tendanceLabel = `Accélération forte (H1: ${h1Qty} uté → H2: ${h2Qty} uté, ratio ${tendanceRatio.toFixed(2)})`;
        } else {
            tendanceLabel = `Stable (H1: ${h1Qty} uté → H2: ${h2Qty} uté, ratio ${tendanceRatio.toFixed(2)})`;
        }
        // Signal réapprovisionnement
        const reappLabel = recentReceptions > 0
            ? `Réceptions récentes : ${recentReceptions} uté reçues sur les 3 derniers mois`
            : (recentSales === 0
                ? "Aucune réception ni vente sur les 3 derniers mois"
                : "Aucune réception récente (ventes encore actives)");
        // Signal asymétrie
        const totalQte = Object.values(qteBySite).reduce((a, b) => a + b, 0);
        const sites = Object.entries(qteBySite);
        let asymLabel = "";
        if (sites.length >= 2 && totalQte > 0) {
            const dominant = sites.sort((a, b) => b[1] - a[1])[0];
            const pct = Math.round((dominant[1] / totalQte) * 100);
            if (pct >= 80) {
                asymLabel = `Porté par ${dominant[0]} (${pct}% des ventes)`;
            }
        }
        return { tendanceLabel, reappLabel, asymLabel };
    }
    // -----------------------------------------------------------------------
    // Fallback legacy (sans contextProfile)
    // -----------------------------------------------------------------------
    private static buildLegacyMessage(p: ProductAnalysisInput): string {
        const score = p.scoring?.score ?? p.score ?? 0;
        const verdict = p.scoring?.verdict ?? (score >= 45 ? "A" : "Z");
        const pmv = p.totalQuantite > 0 ? p.totalCa / p.totalQuantite : 0;
        const contextRules = p.supplierContext
            ? `\n--- RÈGLE MANAGER ---\n"${p.supplierContext}"\n→ Évalue si le produit ("${p.libelle1}") est concerné. rule_applies = true/false.\n`
            : "";
        return `PRODUIT : ${p.libelle1} (${p.codein})
 Famille / Rayon : ${p.libelleNiveau2 ?? "N/A"}
 --- VERDICT PRÉ-CALCULÉ ---
 • Score : ${score}/100
 • Verdict : ${verdict}
 --- PERFORMANCE ---
 • CA réseau : ${p.totalCa.toFixed(2)}€
 • Quantité : ${p.totalQuantite} unités
 • Marge : ${p.tauxMarge.toFixed(1)}%
 • PMV : ${pmv.toFixed(2)}€
 ${p.shareCa !== undefined ? `• Poids CA Fournisseur : ${p.shareCa.toFixed(1)}%` : ""}
 ${p.rankingCa != null || p.rankingQte != null ? `\n--- RANKING ---\n${p.rankingCa != null ? `• Classement CA réseau : ${p.rankingCa}e${p.totalRankedProducts ? ` / ${p.totalRankedProducts} produits (top ${((p.rankingCa / p.totalRankedProducts) * 100).toFixed(1)}%)` : ""}\n` : ""}${p.rankingQte != null ? `• Classement Qté réseau : ${p.rankingQte}e${p.totalRankedProducts ? ` / ${p.totalRankedProducts} produits (top ${((p.rankingQte / p.totalRankedProducts) * 100).toFixed(1)}%)` : ""}\n` : ""}${p.rankingMagCa != null ? `• Classement CA magasin : ${p.rankingMagCa}e\n` : ""}${p.rankingMagQte != null ? `• Classement Qté magasin : ${p.rankingMagQte}e` : ""}` : ""}${contextRules}
 Génère UNIQUEMENT le JSON :`;
    }
    // -----------------------------------------------------------------------
    // Utilitaires de parsing
    // -----------------------------------------------------------------------
    static extractRecommendation(content: string): "A" | "B" | "C" | "D" | "Z" | null {
        const match = content.match(/\b([ABCDZ])\b/i);
        if (match) return match[1].toUpperCase() as "A" | "B" | "C" | "D" | "Z";
        return null;
    }
    static cleanInsight(content: string): string {
        let cleaned = content;
        cleaned = cleaned.replace(/^\[?[ABCDZ]\]?\s*[:\s-]+\s*/i, "");
        cleaned = cleaned.replace(
            /^(justification|explication|pourquoi|justification courte|raison|avis)\s*[:\s-]+\s*/i,
            ""
        );
        return cleaned.trim();
    }
 }
@@ -1,453 +0,0 @@
 /**
 * CollectFlow — Context Profiler (v3 — Normalisation multi-magasin)
 *
 * Génère une fiche de contexte normalisée et adaptative pour chaque produit
 * AVANT de le soumettre à l'IA.
 *
 * v3 — Correctifs :
 *  - Normalisation par `storeCount` : tous les calculs de percentile, poids
 *    et quadrant utilisent les valeurs PAR MAGASIN (CA/store, QTÉ/store).
 *    Cela évite qu'un produit en 2 magasins soit mécaniquement favorisé
 *    dans les comparaisons par rapport à un produit en 1 seul magasin.
 *  - Le profil expose caPerStore et qtyPerStore pour que Mary voie les
 *    deux dimensions : réeau brut ET performance par magasin.
 */
 import type { ProductAnalysisInput } from "../models/ai-analysis.types";
 // ---------------------------------------------------------------------------
 // Constante : seuil minimal de produits dans un rayon pour activer les signaux
 // Trafic/Marge. En dessous = statistiques non significatives.
 // ---------------------------------------------------------------------------
 const MIN_RAYON_SIZE = 6;
 // ---------------------------------------------------------------------------
 // Types
 // ---------------------------------------------------------------------------
 export type Quadrant = "STAR" | "TRAFIC" | "MARGE" | "WATCH";
 export interface ContextProfilerCache {
    allCaPerStoreSorted: number[];
    allQtyPerStoreSorted: number[];
    allMargeValuesSorted: number[];
    totalCaFournisseur: number;
    totalQtyFournisseur: number;
    top20CaThreshold: number;
    top20QtyThreshold: number;
    medianQtyPerStore: number;
    medianMarge: number;
    marge40: number;
    qty60PerStore: number;
    rayonStats: Map<string, { totalCa: number; totalQty: number; count: number }>;
 }
 export interface ProductContextProfile {
    // Identité
    codein: string;
    libelle1: string;
    libelleNiveau2: string;
    // Profil Quadrant (basé sur valeurs PAR MAGASIN pour comparaison équitable)
    quadrant: Quadrant;
    quadrantLabel: string;
    quadrantEmoji: string;
    // Nombre de magasins référençant le produit
    storeCount: number;
    // Valeurs brutes réseau
    totalCaRaw: number;
    totalQtyRaw: number;
    // Valeurs normalisées PAR MAGASIN (pour comparaisons justes)
    caPerStore: number;
    qtyPerStore: number;
    // Percentiles dans le lot fournisseur (0 = plus faible, 100 = meilleur)
    // Calculés sur les valeurs normalisées par magasin
    percentileCa: number;
    percentileQty: number;
    percentileMarge: number;
    percentileComposite: number;
    // Poids réels dans le lot fournisseur
    // Calculés sur les valeurs brutes réseau (représentativité réelle du chiffre)
    weightCaFournisseur: number;   // % du CA total fournisseur
    weightQtyFournisseur: number;  // % des QTÉ totales fournisseur
    // Poids réels dans le rayon (Niveau 2 de nomenclature)
    weightCaRayon: number;
    weightQtyRayon: number;
    // Santé temporelle
    tauxMarge: number;
    inactivityMonths: number;
    regularityScore: number;
    // Contexte du lot
    lotSize: number;
    rayonSize: number;
    // Signaux positifs (calculés sur la distribution réelle)
    isAboveMedianComposite: boolean;
    isTop20Ca: boolean;     // Top 20% sur valeur PAR MAGASIN
    isTop20Qty: boolean;    // Top 20% sur valeur PAR MAGASIN
    /**
     * Fort volume ET marge < P40 du lot → rôle de "locomotive".
     * Désactivé si rayonSize < MIN_RAYON_SIZE.
     */
    isHighVolumeWithLowMargin: boolean;
    /**
     * Marge > P70 du lot même si volume faible → capital rentabilité.
     * Désactivé si rayonSize < MIN_RAYON_SIZE.
     */
    isMargePure: boolean;
    // Signal négatif fort
    /**
     * Le produit appartient aux 30% les moins performants en CA et Quantité.
     */
    isLowContribution: boolean;
    /**
     * Produit avec des statistiques absolues dérisoires (ex: < 100€ CA ou < 20 unités au réseau)
     */
    isDeadStock: boolean;
    // Signal positif fort — Locomotive de rayon
    /**
     * Le produit est une "locomotive" de sa nomenclature (poids CA rayon > 15% OU poids QTÉ rayon > 15%)
     * → Pilier structurant de l'offre dans sa catégorie
     */
    isLocomotiveRayon: boolean;
    // Signaux stock & approvisionnement (API FF Nancy)
    /** Stock actuel ≤ PCB → moins d'un conditionnement disponible */
    isLowStock: boolean;
    /** Commande fournisseur en cours */
    isCommandeEnCours: boolean;
    /** Stock > 0 mais pas de vente depuis > 90 jours */
    isDeadInventory: boolean;
    /** Couverture en mois : stockActuel / (totalQuantite / 12) */
    stockCoverage: number;
    // Gardes-fous (issus du ScoringEngine)
    isProtected: boolean;
    protectionReason: string;
    // Règle absolue
    scoreCritique: boolean;
 }
 // ---------------------------------------------------------------------------
 // Helpers statistiques (purs)
 // ---------------------------------------------------------------------------
 function computePercentileFromSorted(value: number, sortedDistribution: number[]): number {
    if (sortedDistribution.length <= 1) return 100;
    let first = -1;
    let last = -1;
    for (let i = 0; i < sortedDistribution.length; i++) {
        const current = sortedDistribution[i];
        if (Math.abs(current - value) < 0.00001) { // Floating point protection
            if (first === -1) first = i;
            last = i;
        } else if (current > value) {
            if (first === -1) return Math.round((i / Math.max(1, sortedDistribution.length - 1)) * 100);
            break;
        }
    }
    if (first !== -1) {
        const avgRank = (first + last) / 2;
        return Math.round((avgRank / (sortedDistribution.length - 1)) * 100);
    }
    return 100;
 }
 function computeMedianFromSorted(sorted: number[]): number {
    if (sorted.length === 0) return 0;
    const mid = Math.floor(sorted.length / 2);
    return sorted.length % 2 !== 0
        ? sorted[mid]
        : (sorted[mid - 1] + sorted[mid]) / 2;
 }
 function valueAtPercentileFromSorted(sorted: number[], p: number): number {
    if (sorted.length === 0) return 0;
    const idx = Math.max(0, Math.ceil((p / 100) * sorted.length) - 1);
    return sorted[idx];
 }
 /**
 * Extrait la clé de groupement pour le rayon au niveau 2 de nomenclature.
 * Priorité : `codeNomenclatureN2` (4 premiers chiffres) > extraction numérique
 * depuis libelleNiveau2 > valeur brute de libelleNiveau2.
 */
 function getRayonKey(p: ProductAnalysisInput): string {
    if (p.codeNomenclatureN2) {
        return p.codeNomenclatureN2;
    }
    // Fallback : extraire les 4 premiers chiffres si le libellé commence par un code numérique
    const numericPrefix = p.libelleNiveau2?.match(/^(\d{4})/);
    if (numericPrefix) {
        return numericPrefix[1];
    }
    return p.libelleNiveau2 ?? "default";
 }
 const getNormStoreCount = (p: ProductAnalysisInput) => Math.max(1, p.storeCount ?? 1);
 const normCa = (p: ProductAnalysisInput) => (p.totalCa ?? 0) / getNormStoreCount(p);
 const normQty = (p: ProductAnalysisInput) => (p.totalQuantite ?? 0) / getNormStoreCount(p);
 const getWeightedCa = (p: ProductAnalysisInput) => p.weightedTotalCa ?? p.totalCa ?? 0;
 const getWeightedQty = (p: ProductAnalysisInput) => p.weightedTotalQuantite ?? p.totalQuantite ?? 0;
 // ---------------------------------------------------------------------------
 // Profiler principal
 // ---------------------------------------------------------------------------
 export class ContextProfiler {
    /**
     * Prépare un cache contextuel basé sur tous les produits pour éviter des tris 
     * répétés en mode "Bulk Analyze". Réduit la latence de manière dramatique (O(N) au lieu de O(N^2)).
     */
    static prepareCache(allProds: ProductAnalysisInput[]): ContextProfilerCache {
        const allCaPerStore = allProds.map(normCa);
        const allQtyPerStore = allProds.map(normQty);
        const allMargeValues = allProds.map(p => p.tauxMarge ?? 0);
        // On trie une seule et unique fois
        const allCaPerStoreSorted = [...allCaPerStore].sort((a, b) => a - b);
        const allQtyPerStoreSorted = [...allQtyPerStore].sort((a, b) => a - b);
        const allMargeValuesSorted = [...allMargeValues].sort((a, b) => a - b);
        const totalCaFournisseur = allProds.reduce((s, p) => s + getWeightedCa(p), 0);
        const totalQtyFournisseur = allProds.reduce((s, p) => s + getWeightedQty(p), 0);
        const rayonStats = new Map<string, { totalCa: number; totalQty: number; count: number }>();
        allProds.forEach(p => {
            const key = getRayonKey(p);
            if (!rayonStats.has(key)) rayonStats.set(key, { totalCa: 0, totalQty: 0, count: 0 });
            const s = rayonStats.get(key)!;
            s.totalCa += getWeightedCa(p);
            s.totalQty += getWeightedQty(p);
            s.count += 1;
        });
        return {
            allCaPerStoreSorted,
            allQtyPerStoreSorted,
            allMargeValuesSorted,
            totalCaFournisseur,
            totalQtyFournisseur,
            top20CaThreshold: valueAtPercentileFromSorted(allCaPerStoreSorted, 80),
            top20QtyThreshold: valueAtPercentileFromSorted(allQtyPerStoreSorted, 80),
            medianQtyPerStore: computeMedianFromSorted(allQtyPerStoreSorted),
            medianMarge: computeMedianFromSorted(allMargeValuesSorted),
            marge40: valueAtPercentileFromSorted(allMargeValuesSorted, 40),
            qty60PerStore: valueAtPercentileFromSorted(allQtyPerStoreSorted, 60),
            rayonStats,
        };
    }
    /**
     * Génère le profil contextuel d'un produit au sein de son lot fournisseur.
     */
    static buildProfile(
        target: ProductAnalysisInput,
        allProds: ProductAnalysisInput[],
        score: number,
        cache?: ContextProfilerCache
    ): ProductContextProfile {
        if (allProds.length === 0) {
            throw new Error("[ContextProfiler] Le lot de produits est vide.");
        }
        // Utiliser le cache s'il est fourni (mode Bulk) pour éviter de recalculer, 
        // sinon le générer à la volée (mode single item)
        const ctx: ContextProfilerCache = cache ?? ContextProfiler.prepareCache(allProds);
        // ---------------------------------------------------------------------------
        // Normalisation par magasin — cœur de la v3
        // ---------------------------------------------------------------------------
        const targetStoreCount = getNormStoreCount(target);
        const targetCaPerStore = normCa(target);
        const targetQtyPerStore = normQty(target);
        // 1. Totaux fournisseur
        const { totalCaFournisseur, totalQtyFournisseur } = ctx;
        // 2. Totaux du rayon (Niveau 2 de nomenclature)
        const targetRayonKey = getRayonKey(target);
        const rayonStat = ctx.rayonStats.get(targetRayonKey) ?? { totalCa: 0, totalQty: 0, count: 0 };
        const totalCaRayon = rayonStat.totalCa;
        const totalQtyRayon = rayonStat.totalQty;
        const rayonSizeForSignals = rayonStat.count;
        // 3. Percentiles (0-100) — sur distribution PAR MAGASIN
        const pCa = computePercentileFromSorted(targetCaPerStore, ctx.allCaPerStoreSorted);
        const pQty = computePercentileFromSorted(targetQtyPerStore, ctx.allQtyPerStoreSorted);
        const pMarge = computePercentileFromSorted(target.tauxMarge ?? 0, ctx.allMargeValuesSorted);
        const pComposite = score;
        // 4. Tops 20%
        const isTop20Ca = targetCaPerStore >= ctx.top20CaThreshold;
        const isTop20Qty = targetQtyPerStore >= ctx.top20QtyThreshold;
        const isAboveMedianComposite = pComposite >= 50;
        // 5. Poids pondérés
        const weightCaFournisseur =
            totalCaFournisseur > 0
                ? Math.round((getWeightedCa(target) / totalCaFournisseur) * 1000) / 10
                : 0;
        const weightQtyFournisseur =
            totalQtyFournisseur > 0
                ? Math.round((getWeightedQty(target) / totalQtyFournisseur) * 1000) / 10
                : 0;
        const isLowContribution = pCa <= 30 && pQty <= 30 && pMarge <= 70;
        const isDeadStock = (target.totalCa ?? 0) < 150 && (target.totalQuantite ?? 0) < 30;
        // 5b. Locomotive de rayon — poids significatif dans la nomenclature
        const weightCaRayonNum = totalCaRayon > 0
            ? (getWeightedCa(target) / totalCaRayon) * 100
            : 0;
        const weightQtyRayonNum = totalQtyRayon > 0
            ? (getWeightedQty(target) / totalQtyRayon) * 100
            : 0;
        const isLocomotiveRayon = weightCaRayonNum > 15 || weightQtyRayonNum > 15;
        // 6. Signaux Trafic / Marge + Quadrant
        const signalsActive = rayonSizeForSignals >= MIN_RAYON_SIZE;
        let isHighVolumeWithLowMargin = false;
        let isMargePure = false;
        {
            if (signalsActive) {
                isHighVolumeWithLowMargin =
                    targetQtyPerStore >= ctx.qty60PerStore &&
                    (target.tauxMarge ?? 0) < ctx.marge40;
            }
            isMargePure =
                (target.tauxMarge ?? 0) > ctx.medianMarge &&
                targetQtyPerStore < ctx.medianQtyPerStore;
        }
        // 7. Quadrant
        const { quadrant, quadrantLabel, quadrantEmoji } = ContextProfiler.resolveQuadrant(
            targetQtyPerStore,
            target.tauxMarge ?? 0,
            ctx.medianQtyPerStore,
            ctx.medianMarge
        );
        // 8. Gardes-fous (signaux, pas des verdicts — Mary décide au final)
        // Les flags isRecent/isTop30Supplier/isLastProduct sont désormais
        // injectés directement sur ProductRow par score-engine.ts.
        // On les lit depuis le scoring payload transmis par le bulk analyzer.
        const targetExt = target as ProductAnalysisInput & { isRecent?: boolean; isTop30Supplier?: boolean; isLastProduct?: boolean };
        const isRecentFlag = targetExt.isRecent ?? false;
        const isTop30Flag = targetExt.isTop30Supplier ?? false;
        const isLastFlag = targetExt.isLastProduct ?? false;
        const isProtected = isRecentFlag || isTop30Flag || isLastFlag;
        let protectionReason = "";
        if (isRecentFlag) protectionReason = "Nouveauté (< 3 mois de données)";
        else if (isTop30Flag) protectionReason = "Top 30% CA Fournisseur";
        else if (isLastFlag) protectionReason = "Dernière référence du fournisseur";
        // 9. Règle absolue
        const scoreCritique = score < 20;
        return {
            codein: target.codein,
            libelle1: target.libelle1,
            libelleNiveau2: target.libelleNiveau2 ?? "Général",
            quadrant, quadrantLabel, quadrantEmoji,
            storeCount: targetStoreCount,
            totalCaRaw: target.totalCa ?? 0,
            totalQtyRaw: target.totalQuantite ?? 0,
            caPerStore: targetCaPerStore,
            qtyPerStore: targetQtyPerStore,
            percentileCa: pCa,
            percentileQty: pQty,
            percentileMarge: pMarge,
            percentileComposite: pComposite,
            weightCaFournisseur,
            weightQtyFournisseur,
            weightCaRayon:
                totalCaRayon > 0
                    ? Math.round((getWeightedCa(target) / totalCaRayon) * 1000) / 10
                    : 0,
            weightQtyRayon:
                totalQtyRayon > 0
                    ? Math.round((getWeightedQty(target) / totalQtyRayon) * 1000) / 10
                    : 0,
            tauxMarge: target.tauxMarge ?? 0,
            inactivityMonths: target.inactivityMonths ?? 0,
            regularityScore: target.regularityScore ?? 0,
            lotSize: allProds.length,
            rayonSize: rayonSizeForSignals,
            isAboveMedianComposite,
            isTop20Ca,
            isTop20Qty,
            isHighVolumeWithLowMargin,
            isMargePure,
            isLowContribution,
            isDeadStock,
            isLocomotiveRayon,
            isProtected,
            protectionReason,
            scoreCritique,
            // Stock & approvisionnement
            isLowStock: (target.stockActuel !== undefined && target.pcb !== undefined && target.pcb > 0)
                ? target.stockActuel <= target.pcb
                : false,
            isCommandeEnCours: (target.commandesEnCours ?? 0) > 0,
            isDeadInventory: (target.stockTotal ?? 0) > 0 && (target.nbJoursDerniereVente ?? 0) > 90,
            stockCoverage: (() => {
                const avgMonthlyQty = (target.totalQuantite ?? 0) / 12;
                return avgMonthlyQty > 0 ? (target.stockActuel ?? 0) / avgMonthlyQty : 0;
            })(),
        };
    }
    private static resolveQuadrant(
        qty: number,
        marge: number,
        medianQty: number,
        medianMarge: number
    ): { quadrant: Quadrant; quadrantLabel: string; quadrantEmoji: string } {
        if (qty > medianQty && marge > medianMarge) {
            return { quadrant: "STAR", quadrantLabel: "Star (Vol élevé, Marge élevée)", quadrantEmoji: "⭐" };
        }
        if (qty > medianQty && marge <= medianMarge) {
            return { quadrant: "TRAFIC", quadrantLabel: "Générateur de Trafic (Vol élevé, Marge faible)", quadrantEmoji: "🚶" };
        }
        if (qty <= medianQty && marge > medianMarge) {
            return { quadrant: "MARGE", quadrantLabel: "Contributeur de Marge (Vol faible, Marge élevée)", quadrantEmoji: "💎" };
        }
        return { quadrant: "WATCH", quadrantLabel: "Sous-performant (Vol faible, Marge faible)", quadrantEmoji: "⚠️" };
    }
 }
@@ -1,149 +0,0 @@
 "use client";
 import { useEffect, useState } from "react";
 import { createPortal } from "react-dom";
 import { X, Bot, Sparkles, TrendingUp, ShieldAlert, History } from "lucide-react";
 interface AiExplanationModalProps {
    isOpen: boolean;
    onClose: () => void;
    productName: string;
    productCode: string;
    explanation: string;
    recommandation?: "A" | "C" | "Z" | null;
 }
 export function AiExplanationModal({
    isOpen,
    onClose,
    productName,
    productCode,
    explanation,
    recommandation
 }: AiExplanationModalProps) {
    const [isVisible, setIsVisible] = useState(false);
    const [mounted, setMounted] = useState(false);
    useEffect(() => {
        setMounted(true);
        if (isOpen) {
            setIsVisible(true);
        } else {
            setIsVisible(false);
        }
    }, [isOpen]);
    const handleClose = () => {
        setIsVisible(false);
        setTimeout(onClose, 200);
    };
    if (!isOpen && !isVisible) return null;
    if (!mounted) return null;
    const getGammeStyles = (g?: string | null) => {
        switch (g) {
            case "A": return "text-[var(--accent-success)] border-[var(--accent-success-bg)] bg-[var(--accent-success-bg)]";
            case "C": return "text-[var(--accent-warning)] border-[var(--accent-warning-bg)] bg-[var(--accent-warning-bg)]";
            case "Z": return "text-[var(--accent-error)] border-[var(--accent-error-bg)] bg-[var(--accent-error-bg)]";
            default: return "text-[var(--text-muted)] border-[var(--border)] bg-[var(--bg-elevated)]";
        }
    };
    const modalContent = (
        <div
            className={`fixed inset-0 z-[9999] flex items-center justify-center p-6 transition-all duration-200 ${isVisible ? "opacity-100 backdrop-blur-sm" : "opacity-0 backdrop-blur-0"}`}
        >
            {/* Backdrop - consistent with Apple overlay */}
            <div
                className="fixed inset-0 bg-black/40"
                onClick={handleClose}
            />
            {/* Panel - Using var(--bg-surface) and strict spacing */}
            <div
                className={`relative w-full max-w-xl rounded-2xl overflow-hidden shadow-2xl border border-[var(--border-strong)] transition-all duration-200 ${isVisible ? "scale-100 translate-y-0" : "scale-[0.98] translate-y-4"}`}
                style={{
                    background: "var(--bg-surface)",
                }}
            >
                {/* Header - Clean & Monochromatic */}
                <div className="px-6 py-5 border-b border-[var(--border)] flex items-center justify-between">
                    <div className="flex items-center gap-3">
                        <div className="w-8 h-8 rounded-lg bg-[var(--bg-elevated)] border border-[var(--border)] flex items-center justify-center shrink-0">
                            <Bot className="w-5 h-5 text-[var(--text-secondary)]" />
                        </div>
                        <div>
                            <h2 className="text-sm font-bold tracking-tight text-[var(--text-primary)]">
                                Analyse Décisionnelle IA
                            </h2>
                            <p className="text-[11px] font-medium text-[var(--text-muted)] truncate max-w-[300px]">
                                {productName} <span className="opacity-60 tabular-numbers">({productCode})</span>
                            </p>
                        </div>
                    </div>
                    <button
                        onClick={handleClose}
                        className="p-1.5 rounded-md hover:bg-[var(--bg-elevated)] text-[var(--text-muted)] transition-colors"
                    >
                        <X className="w-4 h-4" />
                    </button>
                </div>
                {/* Body */}
                <div className="p-6 space-y-6">
                    {/* Recommendation Row */}
                    <div className="flex items-center justify-between px-1">
                        <span className="text-[11px] font-bold uppercase tracking-wider text-[var(--text-muted)]">Arbitrage suggéré</span>
                        <div className={`px-2.5 py-1 rounded-md border text-[11px] font-bold flex items-center gap-1.5 ${getGammeStyles(recommandation)}`}>
                            {recommandation === "A" && <Sparkles className="w-3 h-3" />}
                            {recommandation === "C" && <TrendingUp className="w-3 h-3" />}
                            {recommandation === "Z" && <ShieldAlert className="w-3 h-3" />}
                            {recommandation ? `GAMME ${recommandation}` : "NON DÉFINI"}
                        </div>
                    </div>
                    {/* Explanation Box - Monospace for figures */}
                    <div
                        className="p-5 rounded-xl border border-[var(--border)] bg-[var(--bg-base)]/50 relative overflow-hidden"
                    >
                        <div className="flex gap-4">
                            <History className="w-4 h-4 mt-0.5 text-[var(--accent)] shrink-0 opacity-80" />
                            <div className="text-[13px] leading-relaxed text-[var(--text-secondary)] font-medium">
                                <span className="font-mono-nums leading-relaxed whitespace-pre-wrap">
                                    {explanation}
                                </span>
                            </div>
                        </div>
                    </div>
                    {/* Meta Info */}
                    <div className="flex items-center justify-center gap-4 py-2 border-t border-[var(--border)]">
                        <div className="flex items-center gap-2 text-[10px] text-[var(--text-muted)] font-medium italic">
                            <span>Basé sur CA, Marge & Volumes réels</span>
                        </div>
                    </div>
                </div>
                {/* Footer Action */}
                <div className="px-6 py-4 bg-[var(--bg-elevated)]/50 border-t border-[var(--border)] flex justify-end">
                    <button
                        onClick={handleClose}
                        className="apple-btn-secondary px-6"
                    >
                        Fermer l'Analyse
                    </button>
                </div>
            </div>
            <style jsx>{`
                .font-mono-nums {
                    font-family: inherit;
                    font-variant-numeric: tabular-nums;
                }
            `}</style>
        </div>
    );
    return createPortal(modalContent, document.body);
 }
@@ -1,199 +0,0 @@
 "use client";
 import React, { useState } from "react";
 import { Loader2, AlertCircle, Sparkles, Maximize2 } from "lucide-react";
 import { AiExplanationModal } from "./ai-explanation-modal";
 import { useAiCopilotStore } from "../store/use-ai-copilot-store";
 import { useGridStore } from "@/features/grid/store/use-grid-store";
 import { useSession } from "next-auth/react";
 import type { ProductRow } from "@/types/grid";
 interface AiInsightBlockProps {
    row: ProductRow;
 }
 export function AiInsightBlock({ row }: AiInsightBlockProps) {
    const { data: session } = useSession();
    const isAdmin = (session?.user as any)?.role === "admin";
    const insight = useAiCopilotStore((s: any) => s.insights[row.codein]);
    const analyzeProduct = useAiCopilotStore((s: any) => s.analyzeProduct);
    const setLoading = useAiCopilotStore((s: any) => s.setLoading);
    const setDraftGamme = useGridStore((s: any) => s.setDraftGamme);
    const [isModalOpen, setIsModalOpen] = useState(false);
    const status = insight?.status ?? "idle";
    const handleAnalyze = async () => {
        if (status === "loading") return;
        // Produit sans aucune vente sur 12 mois → Z direct, pas d'appel IA
        if (row.totalQuantite === 0) {
            setDraftGamme(row.codein, "Z");
            useAiCopilotStore.getState().setInsight(row.codein, "Aucune vente sur 12 mois — produit classé Z automatiquement.");
            return;
        }
        // Stock mort absolu : CA < 100€ ET quantité < 30 → Z direct, aucune analyse IA
        if ((row.totalCa ?? 0) < 100 && (row.totalQuantite ?? 0) < 30) {
            setDraftGamme(row.codein, "Z");
            useAiCopilotStore.getState().setInsight(row.codein, `CA < 100€ (${(row.totalCa ?? 0).toFixed(0)}€) et quantité < 30 (${row.totalQuantite} uté) — stock mort absolu, classé Z automatiquement.`);
            return;
        }
        // Reset Visuel Immédiat
        setLoading(row.codein);
        setDraftGamme(row.codein, "Aucune");
        // Fetch supplier context
        let supplierContext = "";
        if (row.codeFournisseur) {
            try {
                const ctxRes = await fetch(`/api/ai/context?fournisseur=${row.codeFournisseur}`);
                if (ctxRes.ok) {
                    const data = await ctxRes.json();
                    supplierContext = data.context || "";
                }
            } catch (err) {
                console.error("Failed to load supplier context for AI", err);
            }
        }
        // Calcul régularité et inactivité
        const regScore = Object.values(row.sales12m || {}).filter((v: any) => v > 0).length;
        const allMonths = Object.keys(row.sales12m || {});
        const referenceMonth = allMonths.length > 0 ? Math.max(...allMonths.map(m => parseInt(m))).toString() : "";
        const salesMonths = Object.entries(row.sales12m || {}).filter(([_, qty]: [string, any]) => qty > 0).map(([m]) => parseInt(m)).sort((a, b) => b - a);
        const lastMonth = salesMonths.length > 0 ? salesMonths[0].toString() : "";
        let inactivity = 0;
        if (referenceMonth && lastMonth) {
            const refY = parseInt(referenceMonth.substring(0, 4));
            const refM = parseInt(referenceMonth.substring(4, 6));
            const lastY = parseInt(lastMonth.substring(0, 4));
            const lastM = parseInt(lastMonth.substring(4, 6));
            inactivity = (refY - lastY) * 12 + (refM - lastM);
        }
        // Score et verdict pré-calculés par score-engine.ts
        const score = row.score ?? 0;
        const verdict: "A" | "Z" = score >= 45 ? "A" : "Z";
        const sc = row.workingStores?.length || 1;
        const weight = sc === 1 ? 2 : 1;
        analyzeProduct({
            codein: row.codein,
            noid: row.noid,
            libelle1: row.libelle1,
            libelleNiveau2: row.libelleNiveau2,
            totalCa: row.totalCa,
            tauxMarge: row.tauxMarge,
            totalQuantite: row.totalQuantite,
            storeCount: sc,
            sales12m: row.sales12m,
            codeGamme: row.codeGamme,
            score: score,
            regularityScore: regScore,
            lastMonthWithSale: lastMonth,
            inactivityMonths: inactivity,
            weightedTotalQuantite: (row.totalQuantite || 0) * weight,
            weightedTotalCa: (row.totalCa || 0) * weight,
            avgQtyFournisseur: row.avgQtyFournisseur,
            avgQtyRayon: row.avgQtyRayon,
            shareCa: row.shareCa,
            shareMarge: row.shareMarge,
            shareQty: row.shareQty,
            totalFournisseurCa: row.totalFournisseurCa,
            codeFournisseur: row.codeFournisseur,
            totalMagasins: 2,
            prixVente: row.prixVente,
            unitsPerStorePerMonth: row.unitsPerStorePerMonth,
            caPerStorePerYear: row.caPerStorePerYear,
            stockActuel: row.stockActuel,
            stockTotal: row.stockTotal,
            pcb: row.pcb,
            commandesEnCours: row.commandesEnCours,
            nbJoursDerniereVente: row.nbJoursDerniereVente,
            derniereVente: row.derniereVente,
            supplierContext: supplierContext,
            scoring: {
                score,
                verdict,
                isRecent: row.isRecent ?? false,
                isLastProduct: row.isLastProduct ?? false,
                isTop30Supplier: row.isTop30Supplier ?? false,
            }
        });
    };
    if (status === "idle") {
        if (!isAdmin) return null;
        return (
            <button
                onClick={handleAnalyze}
                className="flex items-center gap-1.5 text-[11px] font-medium transition-colors group"
                style={{ color: "var(--text-secondary)" }}
            >
                <Sparkles className="w-3 h-3 text-indigo-500 dark:text-indigo-400 group-hover:text-indigo-600 dark:group-hover:text-indigo-300 transition-colors" />
                <span className="group-hover:text-indigo-600 dark:group-hover:text-indigo-300 transition-colors">Analyser</span>
            </button>
        );
    }
    if (status === "loading") {
        return (
            <div className="flex items-center gap-1.5 text-[11px]" style={{ color: "var(--text-muted)" }}>
                <Loader2 className="w-3 h-3 animate-spin" />
                <span className="italic">Analyse IA...</span>
            </div>
        );
    }
    if (status === "error") {
        return (
            <div
                className="flex items-center gap-1.5 text-[11px] text-rose-600 dark:text-rose-500 cursor-help"
                title={insight?.insight || "Une erreur inconnue est survenue"}
            >
                <AlertCircle className="w-3 h-3" />
                <span>Erreur</span>
            </div>
        );
    }
    return (
        <>
            <div className="flex flex-col gap-1 group/insight" title="Cliquer pour re-analyser">
                <div className="flex-1 min-w-0 pr-1 group">
                    <p
                        className="text-[11px] leading-snug font-medium text-[var(--text-secondary)] line-clamp-3 cursor-pointer hover:text-[var(--text-primary)] transition-colors relative"
                        onClick={(e) => {
                            e.stopPropagation();
                            setIsModalOpen(true);
                        }}
                    >
                        {insight.insight}
                        <span className="inline-flex ml-1 opacity-0 group-hover:opacity-100 transition-opacity">
                            <Maximize2 className="w-2.5 h-2.5 text-[var(--accent)]" />
                        </span>
                    </p>
                </div>
                {insight?.isDuplicate && (
                    <span className="inline-flex items-center gap-1 text-[10px] font-bold text-amber-700 dark:text-amber-400 bg-amber-100 dark:bg-amber-900/30 border border-amber-300 dark:border-amber-700 px-1.5 py-0.5 rounded-full w-fit">
                        Doublon probable
                    </span>
                )}
            </div>
            <AiExplanationModal
                isOpen={isModalOpen}
                onClose={() => setIsModalOpen(false)}
                productName={row.libelle1}
                productCode={row.codein}
                explanation={insight?.insight || ""}
                recommandation={insight?.recommandation}
            />
        </>
    );
 }
@@ -1,113 +0,0 @@
 import { AnalysisEngine } from "../business/analysis-engine";
 import { ProductAnalysisInput, AnalysisResult } from "../models/ai-analysis.types";
 const OPENROUTER_URL = "https://openrouter.ai/api/v1/chat/completions";
 export interface OpenRouterConfig {
    apiKey: string;
    model: string;
 }
 export class OpenRouterClient {
    constructor(private config: OpenRouterConfig) { }
    async analyzeProduct(p: ProductAnalysisInput): Promise<AnalysisResult> {
        // Timeout de 50 secondes : évite le blocage indéfini si OpenRouter est lent,
        // tout en laissant assez de temps aux modèles complexes pour répondre (maxDuration serveur = 55s).
        const controller = new AbortController();
        const timeoutId = setTimeout(() => controller.abort(), 50_000);
        let response: Response;
        try {
            response = await fetch(OPENROUTER_URL, {
                method: "POST",
                signal: controller.signal,
                headers: {
                    Authorization: `Bearer ${this.config.apiKey}`,
                    "Content-Type": "application/json",
                    "HTTP-Referer": "https://collectflow.app",
                    "X-Title": "CollectFlow AI Copilot",
                },
                body: JSON.stringify({
                    model: this.config.model,
                    messages: [
                        { role: "system", content: AnalysisEngine.generateSystemPrompt() },
                        { role: "user", content: AnalysisEngine.generateUserMessage(p) },
                    ],
                    response_format: { type: "json_object" },
                    max_tokens: 150,
                    temperature: 0.1,
                }),
            });
        } catch (err: unknown) {
            if (err instanceof Error && err.name === "AbortError") {
                throw new Error("timeout"); // Géré proprement plus haut
            }
            throw err;
        } finally {
            clearTimeout(timeoutId);
        }
        if (response.status === 429) {
            throw new Error("rate_limited");
        }
        if (!response.ok) {
            const err = await response.text();
            throw new Error(`OpenRouter error: ${err}`);
        }
        const data = await response.json();
        const content = data.choices?.[0]?.message?.content ?? "";
        let reco: "A" | "B" | "C" | "D" | "Z" | null = null;
        let cleanInsight = "Erreur de génération.";
        try {
            // Some models might wrap JSON in markdown blocks despite instructions
            const jsonMatch = content.match(/\{[\s\S]*\}/);
            const jsonText = jsonMatch ? jsonMatch[0] : content;
            const parsed = JSON.parse(jsonText);
            reco = parsed.recommendation as "A" | "B" | "C" | "D" | "Z";
            cleanInsight = parsed.justification || "";
            const ruleApplies = parsed.rule_applies === true;
            // Garde-fou de sécurité : On n'autorise B, C ou D QUE si une règle manager s'applique.
            if (!ruleApplies && (reco === "B" || reco === "C" || reco === "D")) {
                reco = "A";
            }
            // Override recommendation if it doesn't match extracted reco for safety
            if (!reco || !["A", "B", "C", "D", "Z"].includes(reco)) {
                reco = AnalysisEngine.extractRecommendation(cleanInsight) || "A";
                // Ré-appliquer le garde-fou pour la reco extraite du texte.
                if (!ruleApplies && (reco === "B" || reco === "C" || reco === "D")) reco = "A";
            }
            // Garde-fou anti-dégradation : l'IA ne peut PAS dégrader A → Z
            // si le score pré-calculé est ≥ 55 (sauf si règle manager).
            // Corrige les hallucinations du LLM qui ignore la condition "score < 55".
            const preScore = p.scoring?.score ?? p.score ?? 0;
            const preVerdict = p.scoring?.verdict ?? (preScore >= 45 ? "A" : "Z");
            if (!ruleApplies && preVerdict === "A" && reco === "Z" && preScore >= 55) {
                console.warn(`[AI Guardrail] Blocked A→Z degradation for ${p.codein} (score ${preScore} ≥ 55)`);
                reco = "A";
                cleanInsight += " [Garde-fou : score élevé, dégradation bloquée]";
            }
        } catch (e) {
            console.error("Failed to parse AI JSON response:", content, e);
            // Fallback to text parsing
            reco = AnalysisEngine.extractRecommendation(content);
            cleanInsight = AnalysisEngine.cleanInsight(content);
        }
        return {
            insight: reco ? `[${reco}] ${cleanInsight}` : cleanInsight,
            codein: p.codein,
            recommandation: reco
        };
    }
 }
@@ -1,102 +0,0 @@
 import type { ProductContextProfile } from "../business/context-profiler";
 export interface SiteMonthlyData {
    site: string;           // "Frouard" ou "Houdemont"
    mois: string;           // "YYYY-MM"
    ventes_qte: number;
    ventes_ca: number;
    marge: number;
    stock_fin_mois: number; // peut être négatif (validation tardive de commande)
    receptions_qte: number;
 }
 export interface ProductAnalysisInput {
    codein: string;
    libelle1: string;
    libelleNiveau2?: string;
    /**
     * Code de nomenclature au niveau 2 (4 premiers chiffres du code à 6 chiffres).
     * Utilisé pour calculer les poids rayon sur le bon périmètre (pas trop fin = niveau 3).
     * Correspond à `code2` dans ProductRow.
     */
    codeNomenclatureN2?: string;
    totalCa: number;
    tauxMarge: number;
    totalQuantite: number;
    weightedTotalQuantite?: number;
    weightedTotalCa?: number;
    avgTotalQuantite?: number;
    avgQtyRayon?: number;
    avgQtyFournisseur?: number;
    /** Poids relatifs (%) */
    shareCa?: number;
    shareMarge?: number;
    shareQty?: number;
    /** Référentiels */
    totalFournisseurCa?: number;
    storeCount: number;
    sales12m: Record<string, number>;
    codeGamme: string | null;
    score: number;
    regularityScore: number;
    /** Projection sur 12 mois si le produit est récent (Run Rate) */
    projectedTotalQuantite?: number;
    projectedTotalCa?: number;
    /** Analyse de saisonnalité */
    lastMonthWithSale?: string;
    inactivityMonths?: number;
    /** Contexte Fournisseur */
    codeFournisseur?: string;
    totalMagasins?: number;
    isLastProductOfSupplier?: boolean;
    /** Scoring metadata (unifié v4) */
    scoring?: {
        score: number;         // 0-100, score hybride unifié
        verdict: "A" | "Z";   // pré-calculé par TypeScript
        quadrant?: string;     // STAR/TRAFIC/MARGE/WATCH
        isRecent: boolean;
        isLastProduct: boolean;
        isTop30Supplier: boolean;
    };
    /** Prix de vente unitaire */
    prixVente?: number;
    /** Rotation normalisée : unités / magasin / mois */
    unitsPerStorePerMonth?: number;
    /** CA normalisé : € / magasin / an */
    caPerStorePerYear?: number;
    /** Optional context rules for the supplier */
    supplierContext?: string;
    /** SQL Server internal ID — pour fetch mensuel per-site */
    noid?: number;
    /** Données mensuelles per-site (ventes, stock, réceptions) */
    siteMonthlyData?: SiteMonthlyData[];
    /** Données stock & approvisionnement (API FF Nancy) */
    stockActuel?: number;
    stockTotal?: number;
    pcb?: number;
    commandesEnCours?: number;
    nbJoursDerniereVente?: number;
    derniereVente?: string;
    /** Ranking réseau (classement global tous magasins) */
    rankingCa?: number;
    rankingQte?: number;
    /** Ranking magasin (classement local) */
    rankingMagCa?: number;
    rankingMagQte?: number;
    /** Nombre total de produits classés (avec ventes sur la période) */
    totalRankedProducts?: number;
    /**
     * Fiche de contexte enrichie générée par le ContextProfiler.
     * Transmise au prompt de l'IA pour une analyse multi-dimensionnelle.
     */
    contextProfile?: ProductContextProfile;
 }
 export interface AnalysisResult {
    insight: string;
    codein: string;
    recommandation: "A" | "B" | "C" | "D" | "Z" | null;
    scoring?: any; // On peut typer plus finement si nécessaire
 }
@@ -1,160 +0,0 @@
 "use client";
 import { create } from "zustand";
 import { persist } from "zustand/middleware";
 interface AiInsight {
    codein: string;
    insight: string;
    status: "idle" | "loading" | "done" | "error";
    isDuplicate?: boolean;
 }
 interface AiCopilotState {
    insights: Record<string, AiInsight>;
    setInsight: (codein: string, insight: string, isDuplicate?: boolean) => void;
    batchSetInsights: (entries: { codein: string; insight: string }[]) => void;
    setLoading: (codein: string) => void;
    batchSetLoading: (codeins: string[]) => void;
    setError: (codein: string, error: string) => void;
    analyzeProduct: (payload: {
        codein: string;
        noid?: number;
        libelle1: string;
        libelleNiveau2?: string;
        totalCa: number;
        tauxMarge: number;
        totalQuantite: number;
        storeCount: number;
        sales12m: Record<string, number>;
        codeGamme: string | null;
        score?: number | null;
        regularityScore?: number;
        lastMonthWithSale?: string;
        inactivityMonths?: number;
        weightedTotalQuantite?: number;
        weightedTotalCa?: number;
        avgQtyFournisseur?: number;
        avgQtyRayon?: number;
        shareCa?: number;
        shareMarge?: number;
        shareQty?: number;
        totalFournisseurCa?: number;
        codeFournisseur?: string;
        totalMagasins?: number;
        prixVente?: number;
        unitsPerStorePerMonth?: number;
        caPerStorePerYear?: number;
        stockActuel?: number;
        stockTotal?: number;
        pcb?: number;
        commandesEnCours?: number;
        nbJoursDerniereVente?: number;
        derniereVente?: string;
        supplierContext?: string;
        scoring?: {
            score: number;
            verdict: "A" | "Z";
            isRecent: boolean;
            isLastProduct: boolean;
            isTop30Supplier: boolean;
        };
    }) => Promise<void>;
    resetInsights: () => void;
 }
 export const useAiCopilotStore = create<AiCopilotState>()(
    persist(
        (set, get) => ({
            insights: {},
            setInsight: (codein, insight, isDuplicate = false) => {
                set((s) => ({
                    insights: {
                        ...s.insights,
                        [codein]: { codein, insight, status: "done", isDuplicate },
                    },
                }));
            },
            batchSetInsights: (entries) => {
                set((s) => {
                    const nextInsights = { ...s.insights };
                    entries.forEach(({ codein, insight }) => {
                        nextInsights[codein] = { codein, insight, status: "done" };
                    });
                    return { insights: nextInsights };
                });
            },
            setLoading: (codein) => {
                set((s) => ({
                    insights: {
                        ...s.insights,
                        [codein]: { codein, insight: "", status: "loading" },
                    },
                }));
            },
            batchSetLoading: (codeins) => {
                set((s) => {
                    const nextInsights = { ...s.insights };
                    codeins.forEach(codein => {
                        nextInsights[codein] = { codein, insight: "", status: "loading" };
                    });
                    return { insights: nextInsights };
                });
            },
            setError: (codein, error) => {
                set((s) => ({
                    insights: {
                        ...s.insights,
                        [codein]: { codein, insight: error, status: "error" },
                    },
                }));
            },
            resetInsights: () => {
                set({ insights: {} });
            },
            analyzeProduct: async (payload) => {
                const { codein } = payload;
                // Mark as loading
                set((s) => ({
                    insights: { ...s.insights, [codein]: { codein, insight: "", status: "loading" } },
                }));
                try {
                    const res = await fetch("/api/ai/analyze", {
                        method: "POST",
                        headers: { "Content-Type": "application/json" },
                        body: JSON.stringify(payload),
                    });
                    if (!res.ok) throw new Error(`HTTP ${res.status}`);
                    const data = await res.json();
                    set((s) => ({
                        insights: {
                            ...s.insights,
                            [codein]: { codein, insight: data.insight, status: "done" },
                        },
                    }));
                } catch {
                    set((s) => ({
                        insights: {
                            ...s.insights,
                            [codein]: { codein, insight: "Erreur lors de l'analyse.", status: "error" },
                        },
                    }));
                }
            },
        }),
        {
            name: "collectflow-ai-storage",
        }
    )
 );
@@ -1,7 +1,6 @@
 import "server-only";
 import type { ProductRow, GammeCode, GridFilters } from "@/types/grid";
 import { computeProductScores } from "@/lib/score-engine";
 import { buildLast12MonthsRange, getMensuelByArticles } from "@/lib/api-ff-client";
 import {
    pgGetArticlesByFournisseur,
@@ -9,13 +8,15 @@ import {
    pgGetGammesByFournisseur,
    pgGetNomenclatureByFournisseur,
    pgGetStockByFournisseur,
    pgGetRankingByFournisseur,
    pgGetCommandesByFournisseur,
    type PgStockRow,
 } from "@/lib/pg-ff-client";
 import { db } from "@/db";
 import { sessionSnapshots } from "@/db/schema";
 import { eq, desc } from "drizzle-orm";
 import { getNetworkMetricsByCodeCentrale } from "@/lib/qlik-network-cache";
 const NB_MAGASINS_RESEAU = 270;
 interface GetProductRowsInput {
    codeFournisseur: string;
@@ -86,7 +87,6 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
            gammeMap,
            nomMap,
            stockMap,
            rankingResult,
            commandesMap,
        ] = await Promise.all([
            pgGetArticlesByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetArticlesByFournisseur ERROR:", e); return []; }),
@@ -94,12 +94,10 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
            pgGetGammesByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetGammesByFournisseur ERROR:", e); return new Map<string, string>(); }),
            pgGetNomenclatureByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetNomenclatureByFournisseur ERROR:", e); return new Map(); }),
            pgGetStockByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetStockByFournisseur ERROR:", e); return new Map<string, PgStockRow[]>(); }),
            pgGetRankingByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetRankingByFournisseur ERROR:", e); return { rankings: new Map(), totalRankedProducts: 0 }; }),
            pgGetCommandesByFournisseur(codeFournisseur).catch(e => { console.error("[getProductRows] pgGetCommandesByFournisseur ERROR:", e); return new Map<string, number>(); }),
        ]);
-        const { rankings: rankingMap, totalRankedProducts } = rankingResult;
+        console.log(`[getProductRows] ${articles.length} articles, ${mensuelRows.length} mensuel rows, ${gammeMap.size} gammes`);
        console.log(`[getProductRows] ${articles.length} articles, ${mensuelRows.length} mensuel rows, ${gammeMap.size} gammes, ${rankingMap.size} rankings`);
        // ─── Phase 2 : Fenêtre temporelle 12 mois complets ───────────────────
        const now = new Date();
@@ -123,6 +121,7 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
                libelle1: art.libelle1 ?? "",
                gtin: art.gtin ?? "",
                reference: art.reference ?? "",
                codeCentrale: art.codeCentrale ? String(art.codeCentrale).trim() : undefined,
                code1: "", libelleNiveau1: "",
                code2: "", libelleNiveau2: "",
                code3: "", libelle3: "",
@@ -136,9 +135,7 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
                totalCa: 0,
                totalMarge: 0,
                tauxMarge: 0,
                score: 0,
                workingStores: [],
                aiRecommendation: null,
                noid: art.no_id ? Number(art.no_id) : undefined,
                pcb: art.pcb ? Number(art.pcb) : undefined,
                prixVente: art.pv_central ? Number(art.pv_central) : undefined,
@@ -313,16 +310,8 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
            }
        }
-        // ─── Phase 8 : Ranking réseau ────────────────────────────────────────
+        // ─── Phase 8 : Données réseau Qlik (CA / Qté / nb magasins par code centrale) ──
-        for (const [codein, ranking] of rankingMap.entries()) {
+        await enrichWithNetworkMetrics(productMap);
            const product = productMap.get(codein);
            if (!product) continue;
            product.rankingCa           = ranking.ranking_ca    ? Number(ranking.ranking_ca)    : undefined;
            product.rankingQte          = ranking.ranking_qte   ? Number(ranking.ranking_qte)   : undefined;
            product.rankingMagCa        = ranking.ranking_mag_ca  ? Number(ranking.ranking_mag_ca)  : undefined;
            product.rankingMagQte       = ranking.ranking_mag_qte ? Number(ranking.ranking_mag_qte) : undefined;
            product.totalRankedProducts = totalRankedProducts;
        }
        // ─── Phase 9 : Restaurer gammes depuis dernier snapshot ──────────────
        try {
@@ -348,14 +337,14 @@ async function buildProductRows(input: GetProductRowsInput): Promise<ProductRow[
            console.error("[getProductRows] Snapshot restore error:", snapErr);
        }
-        // ─── Phase 10 : Filtrer gamme Y sans ventes + compute scores ─────────
+        // ─── Phase 10 : Filtrer gamme Y sans ventes ──────────────────────────
        const allRows = Array.from(productMap.values());
        const rows = allRows.filter(p => p.codeGamme !== "Y" || p.totalQuantite > 0);
        await reconcileSelectedStoreFromMensuelApi(rows, magasin, dateDebut, dateFin, sortedPeriods);
        const excludedY = allRows.length - rows.length;
        console.log(`[getProductRows] ${rows.length} produits (${excludedY} gamme Y sans ventes exclus), ${mensuelByCodein.size} avec ventes`);
-        return computeProductScores(rows);
+        return rows;
    } catch (error) {
        console.error(`[getProductRows] Error for ${codeFournisseur}:`, error);
@@ -467,3 +456,36 @@ async function reconcileSelectedStoreFromMensuelApi(
        console.error("[getProductRows] Mensuel API reconciliation error:", error);
    }
 }
 /**
 * Enrichit les produits avec les metriques reseau Qlik (cache qlik_network_metrics),
 * jointes par code centrale. Degradation propre si la sync Qlik n'a jamais tourne
 * ou si le code centrale n'est pas encore disponible.
 */
 async function enrichWithNetworkMetrics(productMap: Map<string, ProductRow>): Promise<void> {
    try {
        const byCodeCentrale = new Map<string, ProductRow[]>();
        for (const product of productMap.values()) {
            const cc = product.codeCentrale;
            if (!cc) continue;
            if (!byCodeCentrale.has(cc)) byCodeCentrale.set(cc, []);
            byCodeCentrale.get(cc)!.push(product);
        }
        if (byCodeCentrale.size === 0) return;
        const metrics = await getNetworkMetricsByCodeCentrale([...byCodeCentrale.keys()]);
        for (const [cc, products] of byCodeCentrale.entries()) {
            const m = metrics.get(cc);
            if (!m) continue;
            for (const product of products) {
                product.caReseau = m.caReseau;
                product.qteReseau = m.qteReseau;
                product.nbMagasinsReseau = m.nbMagasinsReseau;
                product.tauxPresenceReseau = m.nbMagasinsReseau / NB_MAGASINS_RESEAU;
                product.networkFetchedAt = m.fetchedAt ?? undefined;
            }
        }
    } catch (error) {
        console.error("[getProductRows] enrichWithNetworkMetrics error:", error);
    }
 }
@@ -1,402 +0,0 @@
 "use client";
 import React, { useState, useRef, useEffect } from "react";
 import { useGridStore } from "@/features/grid/store/use-grid-store";
 import { useAiCopilotStore } from "@/features/ai-copilot/store/use-ai-copilot-store";
 import { ContextProfiler } from "@/features/ai-copilot/business/context-profiler";
 import { Sparkles, Loader2, CheckCircle2, XCircle } from "lucide-react";
 import { GammeCode } from "@/types/grid";
 import { ProductAnalysisInput } from "@/features/ai-copilot/models/ai-analysis.types";
 import { SupplierAiContextModal } from "./supplier-ai-context-modal";
 export function BulkAiAnalyzer() {
    const rows = useGridStore((s) => s.rows);
    const supplierCode = rows.length > 0 ? rows[0].codeFournisseur : null;
    const supplierName = rows.length > 0 ? rows[0].nomFournisseur : null;
    const [isAnalyzing, setIsAnalyzing] = useState(false);
    const [progress, setProgress] = useState({ current: 0, total: 0, message: "", errors: 0 });
    const isCancelledRef = useRef(false);
    const batchSetDraftGamme = useGridStore((s) => s.batchSetDraftGamme);
    const setDraftGamme = useGridStore((s) => s.setDraftGamme);
    const { setInsight, batchSetInsights, batchSetLoading, setError } = useAiCopilotStore();
    const prevSupplierRef = useRef(supplierCode);
    useEffect(() => {
        if (supplierCode !== prevSupplierRef.current) {
            if (!isAnalyzing) {
                setProgress({ current: 0, total: 0, message: "", errors: 0 });
            }
            prevSupplierRef.current = supplierCode;
        }
    }, [supplierCode, isAnalyzing]);
    const handleStop = () => {
        isCancelledRef.current = true;
        setProgress((prev) => ({ ...prev, message: "Arrêt en cours..." }));
    };
    const handleAnalyze = async () => {
        const { rows } = useGridStore.getState();
        isCancelledRef.current = false;
        // Show immediate visual feedback before any async work
        setIsAnalyzing(true);
        setProgress({ current: 0, total: 0, message: "Chargement du contexte...", errors: 0 });
        // 1. Fetch AI Context for the Supplier
        let supplierContext = "";
        if (supplierCode) {
            try {
                const ctxRes = await fetch(`/api/ai/context?fournisseur=${supplierCode}`);
                if (ctxRes.ok) {
                    const data = await ctxRes.json();
                    supplierContext = data.context || "";
                }
            } catch (err) {
                console.error("Failed to load supplier context for AI", err);
            }
        }
        // 2a. Produits sans aucune vente → Z direct, sans appel IA (avant de construire les payloads)
        const zeroSalesRows = rows.filter((r) => (r.totalQuantite || 0) === 0);
        if (zeroSalesRows.length > 0) {
            const zChanges: Record<string, GammeCode> = {};
            zeroSalesRows.forEach(r => { zChanges[r.codein] = "Z"; });
            batchSetDraftGamme(zChanges);
            batchSetInsights(zeroSalesRows.map(r => ({
                codein: r.codein,
                insight: "Aucune vente sur 12 mois — produit classé Z automatiquement.",
            })));
        }
        // Construire les payloads uniquement pour les produits avec ventes
        const rowsWithSales = rows.filter((r) => (r.totalQuantite || 0) > 0);
        const initialPayloads: ProductAnalysisInput[] = rowsWithSales.map((r) => {
            const sc = r.workingStores?.length || 1;
            const weight = sc === 1 ? 2 : 1;
            const allMonths = Object.keys(r.sales12m || {});
            const referenceMonth = allMonths.length > 0 ? Math.max(...allMonths.map((m) => parseInt(m))).toString() : "";
            const salesMonths = Object.entries(r.sales12m || {})
                .filter(([_, qty]) => qty > 0)
                .map(([m]) => parseInt(m))
                .sort((a, b) => b - a);
            const lastMonth = salesMonths.length > 0 ? salesMonths[0].toString() : "";
            let inactivity = 0;
            if (referenceMonth && lastMonth) {
                const refY = parseInt(referenceMonth.substring(0, 4));
                const refM = parseInt(referenceMonth.substring(4, 6));
                const lastY = parseInt(lastMonth.substring(0, 4));
                const lastM = parseInt(lastMonth.substring(4, 6));
                inactivity = (refY - lastY) * 12 + (refM - lastM);
            }
            const regScore = Object.values(r.sales12m || {}).filter((v) => v > 0).length;
            return {
                codein: r.codein,
                noid: r.noid,
                libelle1: r.libelle1 || "",
                libelleNiveau2: r.libelleNiveau2 || "Général",
                codeNomenclatureN2: r.code2 || undefined,
                totalCa: r.totalCa || 0,
                tauxMarge: r.tauxMarge || 0,
                totalQuantite: r.totalQuantite || 0,
                weightedTotalQuantite: (r.totalQuantite || 0) * weight,
                weightedTotalCa: (r.totalCa || 0) * weight,
                storeCount: sc,
                sales12m: Object.fromEntries(Object.entries(r.sales12m || {}).map(([month, val]) => [month, (val as number) * weight])),
                codeGamme: r.codeGamme || null,
                score: r.score || 0,
                regularityScore: regScore,
                lastMonthWithSale: lastMonth,
                inactivityMonths: inactivity,
                codeFournisseur: r.codeFournisseur || undefined,
                avgQtyFournisseur: r.avgQtyFournisseur,
                avgQtyRayon: r.avgQtyRayon,
                shareCa: r.shareCa,
                shareMarge: r.shareMarge,
                shareQty: r.shareQty,
                totalFournisseurCa: r.totalFournisseurCa,
                supplierContext: supplierContext,
            };
        });
        // 2b. Stock mort absolu : CA < 100€ ET quantité < 30 → Z direct, sans appel IA
        const deadStockRows = rows.filter(r =>
            (r.totalQuantite || 0) > 0 &&
            (r.totalCa ?? 0) < 100 && (r.totalQuantite ?? 0) < 30
        );
        if (deadStockRows.length > 0) {
            const zChanges: Record<string, GammeCode> = {};
            deadStockRows.forEach(r => { zChanges[r.codein] = "Z"; });
            batchSetDraftGamme(zChanges);
            batchSetInsights(deadStockRows.map(r => ({
                codein: r.codein,
                insight: `CA < 100€ (${(r.totalCa ?? 0).toFixed(0)}€) et quantité < 30 (${r.totalQuantite} uté) — stock mort absolu, classé Z automatiquement.`,
            })));
        }
        const deadStockCodes = new Set(deadStockRows.map(r => r.codein));
        // 2c. Top 20 réseau → A direct, sans appel IA
        const top20Rows = rows.filter(r =>
            (r.totalQuantite || 0) > 0 &&
            !deadStockCodes.has(r.codein) &&
            ((r.rankingCa != null && r.rankingCa <= 20) || (r.rankingQte != null && r.rankingQte <= 20))
        );
        if (top20Rows.length > 0) {
            const aChanges: Record<string, GammeCode> = {};
            top20Rows.forEach(r => { aChanges[r.codein] = "A"; });
            batchSetDraftGamme(aChanges);
            batchSetInsights(top20Rows.map(r => {
                const rkCa = r.rankingCa != null ? `${r.rankingCa}e CA` : "";
                const rkQte = r.rankingQte != null ? `${r.rankingQte}e Qté` : "";
                const total = r.totalRankedProducts ? ` / ${r.totalRankedProducts.toLocaleString("fr-FR")} produits` : "";
                return {
                    codein: r.codein,
                    insight: `Top 20 réseau (${[rkCa, rkQte].filter(Boolean).join(", ")}${total}) — classé A automatiquement.`,
                };
            }));
        }
        const top20Codes = new Set(top20Rows.map(r => r.codein));
        // Filtrer : ne soumettre à l'IA que les produits avec au moins 1 vente et CA/quantité suffisants
        const payloadsWithSales = initialPayloads.filter(p =>
            (p.totalQuantite || 0) > 0 && !deadStockCodes.has(p.codein) && !top20Codes.has(p.codein)
        );
        // 2c. Context profiling en micro-batches asynchrones
        //    Le score est déjà calculé par score-engine.ts (champ row.score sur chaque ProductRow).
        setProgress({ current: 0, total: payloadsWithSales.length, message: "Calcul du contexte...", errors: 0 });
        const SCORING_BATCH_SIZE = 25;
        const productPayloads: ProductAnalysisInput[] = [];
        // Pre-compute context thresholds to prevent O(N^2) and O(N^2 log N) performance freezes
        const contextCache = ContextProfiler.prepareCache(payloadsWithSales);
        // Map codein → row pour récupérer le score et les flags depuis score-engine
        const rowByCodein = new Map(rows.map(r => [r.codein, r]));
        for (let i = 0; i < payloadsWithSales.length; i += SCORING_BATCH_SIZE) {
            if (isCancelledRef.current) break;
            const batch = payloadsWithSales.slice(i, i + SCORING_BATCH_SIZE);
            for (const p of batch) {
                const row = rowByCodein.get(p.codein);
                const score = row?.score ?? p.score ?? 0;
                const verdict: "A" | "Z" = score >= 45 ? "A" : "Z";
                let contextProfile: ProductAnalysisInput["contextProfile"];
                try {
                    contextProfile = ContextProfiler.buildProfile(p, payloadsWithSales, score, contextCache);
                } catch (err) {
                    console.warn(`[BulkAnalyzer] ContextProfiler failed for ${p.codein}:`, err);
                    contextProfile = undefined;
                }
                productPayloads.push({
                    ...p,
                    prixVente: row?.prixVente,
                    unitsPerStorePerMonth: row?.unitsPerStorePerMonth,
                    caPerStorePerYear: row?.caPerStorePerYear,
                    stockActuel: row?.stockActuel,
                    stockTotal: row?.stockTotal,
                    pcb: row?.pcb,
                    commandesEnCours: row?.commandesEnCours,
                    nbJoursDerniereVente: row?.nbJoursDerniereVente,
                    derniereVente: row?.derniereVente,
                    rankingCa: row?.rankingCa,
                    rankingQte: row?.rankingQte,
                    rankingMagCa: row?.rankingMagCa,
                    rankingMagQte: row?.rankingMagQte,
                    totalRankedProducts: row?.totalRankedProducts,
                    contextProfile,
                    scoring: {
                        score,
                        verdict,
                        quadrant: contextProfile?.quadrant,
                        isRecent: row?.isRecent ?? false,
                        isLastProduct: row?.isLastProduct ?? false,
                        isTop30Supplier: row?.isTop30Supplier ?? false,
                    },
                });
            }
            // Yield au navigateur entre chaque batch pour éviter le freeze
            setProgress(prev => ({
                ...prev,
                current: Math.min(i + SCORING_BATCH_SIZE, payloadsWithSales.length),
                message: `Contexte : ${Math.min(i + SCORING_BATCH_SIZE, payloadsWithSales.length)}/${payloadsWithSales.length}`,
            }));
            await new Promise(r => setTimeout(r, 0));
        }
        if (isCancelledRef.current) {
            setIsAnalyzing(false);
            return;
        }
        let completed = 0;
        let errorsCount = 0;
        const totalItems = productPayloads.length;
        setProgress({ current: 0, total: totalItems, message: "Envoi aux modèles IA...", errors: 0 });
        // Reset global ATOMIQUE et IMMÉDIAT
        const codeins = productPayloads.map(p => p.codein);
        batchSetLoading(codeins);
        const gammeChanges: Record<string, GammeCode> = {};
        codeins.forEach(c => gammeChanges[c] = "Aucune");
        batchSetDraftGamme(gammeChanges);
        const CONCURRENCY = 2;
        const remaining = [...productPayloads];
        const processBatch = async () => {
            const workers = Array.from({ length: Math.min(CONCURRENCY, remaining.length) }, async () => {
                while (remaining.length > 0 && !isCancelledRef.current) {
                    const payload = remaining.shift();
                    if (!payload) break;
                    try {
                        let res: Response | null = null;
                        // Jusqu'à 3 tentatives par produit
                        for (let attempt = 0; attempt < 3; attempt++) {
                            if (isCancelledRef.current) break;
                            try {
                                res = await fetch("/api/ai/analyze", {
                                    method: "POST",
                                    headers: { "Content-Type": "application/json" },
                                    body: JSON.stringify(payload),
                                });
                                if (res.ok) break; // Succès → sortie de boucle
                                if (res.status === 429) {
                                    // Rate-limit : on attend avant de réessayer
                                    const retryData = await res.json().catch(() => ({}));
                                    const wait = (retryData.retryAfter ?? 30) * 1000;
                                    console.warn(`[BulkAI] Rate limited, retry in ${wait / 1000}s`);
                                    await new Promise((r) => setTimeout(r, Math.min(wait, 15_000)));
                                } else if (res.status === 504 || res.status === 502 || res.status === 503 || res.status === 529) {
                                    // Timeout ou réseau surchargé : on tente de réessayer de suite
                                    console.warn(`[BulkAI] Network issue (${res.status}) for ${payload.codein}, retry #${attempt + 1}`);
                                    await new Promise((r) => setTimeout(r, 2_000 * (attempt + 1))); // Exponential backoff (2s, 4s, 6s)
                                } else {
                                    // Autre erreur (500 local, auth, etc.) : ne pas réessayer inutilement
                                    break;
                                }
                            } catch (fetchErr) {
                                console.error(`[BulkAI] Fetch error (attempt ${attempt + 1}) for ${payload.codein}`, fetchErr);
                                await new Promise((r) => setTimeout(r, 1_000)); // Petite pause avant retry réseau
                            }
                        }
                        if (!res || !res.ok) {
                            let errorMsg = res?.status === 504 ? "Timeout IA" : (res?.status === 502 ? "API Surchargée" : `Erreur HTTP ${res?.status}`);
                            // On tente d'extraire le message original s'il y en a un
                            if (res && res.headers.get("content-type")?.includes("application/json")) {
                                try {
                                    const errData = await res.json();
                                    if (errData.error) errorMsg += ` - ${errData.error}`;
                                    if (errData.detail) errorMsg += ` (${errData.detail})`;
                                } catch (e) { /* ignore JSON parse error on error */ }
                            }
                            setError(payload.codein, errorMsg);
                            errorsCount++;
                        } else {
                            const data = await res.json();
                            setInsight(payload.codein, data.insight, data.isDuplicate);
                            if (data.recommandation) {
                                setDraftGamme(payload.codein, data.recommandation as GammeCode);
                            }
                        }
                    } catch (err) {
                        console.error(`[BulkAI] Error processing ${payload.codein}`, err);
                        setError(payload.codein, "Erreur");
                        errorsCount++;
                    } finally {
                        completed++;
                        setProgress((prev) => ({
                            ...prev,
                            current: completed,
                            message: `Analyse: ${completed}/${totalItems}`,
                            errors: errorsCount,
                        }));
                    }
                }
            });
            await Promise.all(workers);
        };
        await processBatch();
        // Nettoyer les drafts "Aucune" restants (produits en erreur dont l'IA n'a pas retourné A/Z)
        // Pour éviter que "Valider" ne sauvegarde "Aucune" comme gamme réelle
        const currentDrafts = useGridStore.getState().draftChanges;
        const aucuneCodeins = codeins.filter(c => currentDrafts[c] === "Aucune");
        if (aucuneCodeins.length > 0) {
            const { clearDrafts } = useGridStore.getState();
            clearDrafts(aucuneCodeins);
        }
        setProgress((prev) => ({
            ...prev,
            message: isCancelledRef.current ? `Analyse interrompue (${completed}/${totalItems})` : `Analyse terminée ! (${errorsCount > 0 ? errorsCount + " erreurs" : "succès"})`,
        }));
        setTimeout(() => setIsAnalyzing(false), 3000);
    };
    return (
        <div className="flex items-center gap-3">
            <SupplierAiContextModal codeFournisseur={supplierCode} nomFournisseur={supplierName} />
            {isAnalyzing ? (
                <div className="flex items-center gap-4 h-10 px-4 rounded-xl bg-[var(--accent-bg)] border border-[var(--accent-border)] shadow-sm">
                    <Loader2 className="w-4 h-4 text-[var(--accent)] animate-spin" />
                    <div className="flex flex-col min-w-[150px]">
                        <span className="text-[10px] font-bold text-[var(--accent)] leading-none">
                            {progress.message}
                        </span>
                        <div className="w-full bg-[var(--bg-elevated)] rounded-full h-1 mt-1 overflow-hidden">
                            <div
                                className="bg-[var(--accent)] h-1 rounded-full transition-all duration-300"
                                style={{ width: `${Math.max(5, (progress.current / progress.total) * 100)}%` }}
                            ></div>
                        </div>
                    </div>
                    <button
                        onClick={handleStop}
                        className="p-1 hover:bg-[var(--bg-elevated)] rounded-lg transition-colors text-[var(--text-muted)] hover:text-[var(--accent-error)]"
                        title="Arrêter l'analyse"
                    >
                        <XCircle className="w-4 h-4" />
                    </button>
                </div>
            ) : progress.current > 0 ? (
                <div className="apple-btn-primary opacity-80 cursor-default">
                    <CheckCircle2 className="w-4 h-4" />
                    <span>
                        {progress.errors > 0 ? `Terminé (${progress.current - progress.errors}/${progress.total})` : `Analyse Terminée`}
                    </span>
                </div>
            ) : (
                <button
                    onClick={handleAnalyze}
                    className="apple-btn-secondary"
                >
                    <Sparkles className="w-4 h-4" style={{ color: "var(--accent)" }} />
                    Analyse IA
                </button>
            )}
        </div>
    );
 }
@@ -118,7 +118,7 @@ export function ExportDropdown({ nomFournisseur }: { nomFournisseur?: string })
        doc.text(`Export généré le : ${new Date().toLocaleDateString("fr-FR")}`, 14, 30);
        const head = [
-            ["Gencode", "Code In", "Réf.", "Libellé", "Score", "Vol.", "CA", "Marge", "Gamme"]
+            ["Gencode", "Code In", "Réf.", "Libellé", "Mag. Rés.", "Vol.", "CA", "Marge", "Gamme"]
        ];
        const body = rows.map(r => {
@@ -128,7 +128,7 @@ export function ExportDropdown({ nomFournisseur }: { nomFournisseur?: string })
                r.codein,
                r.reference || "-",
                r.libelle1 ? r.libelle1.substring(0, 60) + (r.libelle1.length > 60 ? "..." : "") : "",
-                r.score.toString(),
+                r.nbMagasinsReseau != null ? r.nbMagasinsReseau.toString() : "-",
                Math.round(r.totalQuantite).toLocaleString("fr-FR"),
                `${Math.round(r.totalCa).toLocaleString("fr-FR")} €`,
                `${Math.round(r.totalMarge).toLocaleString("fr-FR")} €\n(${r.tauxMarge.toFixed(1)}%)`,
@@ -1,8 +1,7 @@
 import { useGridStore } from "@/features/grid/store/use-grid-store";
 import { useAiCopilotStore } from "@/features/ai-copilot/store/use-ai-copilot-store";
 import { useSession } from "next-auth/react";
-import { BulkAiAnalyzer } from "./bulk-ai-analyzer";
+import { SyncQlikButton } from "./sync-qlik-button";
 import { useSaveDrafts } from "@/features/grid/hooks/use-save-drafts";
 import { Loader2, CheckCircle, AlertCircle, RotateCcw, Camera, ChevronDown } from "lucide-react";
 import { useMemo, useState, useTransition } from "react";
@@ -35,7 +34,6 @@ export function FloatingSummaryBar() {
    const rows = useGridStore((s) => s.rows);
    const filters = useGridStore((s) => s.filters);
    const draftChanges = useGridStore((s) => s.draftChanges);
    const { resetInsights } = useAiCopilotStore();
    const [isPending, startTransition] = useTransition();
    const [isSavingSnapshot, setIsSavingSnapshot] = useState(false);
    const [saveStatus, setSaveStatus] = useState<"idle" | "success" | "error">("idle");
@@ -48,6 +46,15 @@ export function FloatingSummaryBar() {
    const visibleCodeins = useMemo(() => rows.map(r => r.codein), [rows]);
    const { save, hasDrafts, count } = useSaveDrafts(filters.magasin || "TOTAL", visibleCodeins);
    const supplierCode = filters.codeFournisseur || rows[0]?.codeFournisseur;
    const lastQlikUpdate = useMemo(() => {
        let max: string | null = null;
        for (const r of rows) {
            if (r.networkFetchedAt && (!max || r.networkFetchedAt > max)) max = r.networkFetchedAt;
        }
        return max;
    }, [rows]);
    const handleSave = () => {
        startTransition(async () => {
            const result = await save();
@@ -57,9 +64,8 @@ export function FloatingSummaryBar() {
    };
    const handleReset = () => {
-        if (window.confirm("Es-tu sûr de vouloir annuler tous les changements non enregistrés (gammes et analyses IA) ?")) {
+        if (window.confirm("Es-tu sûr de vouloir annuler tous les changements non enregistrés (gammes) ?")) {
            resetDrafts();
            resetInsights();
        }
    };
@@ -182,7 +188,7 @@ export function FloatingSummaryBar() {
            </div>
            <div className="flex space-x-3 items-center">
-                {isAdmin && <BulkAiAnalyzer />}
+                {isAdmin && <SyncQlikButton codeFournisseur={supplierCode} lastUpdate={lastQlikUpdate} />}
                <DropdownMenu>
                    <DropdownMenuTrigger asChild>
@@ -26,7 +26,6 @@ import { GammeSelect } from "@/features/grid/components/gamme-select";
 import { HeatmapCell } from "@/features/grid/components/heatmap-cell";
 import type { ProductRow, GammeCode } from "@/types/grid";
 import { cn } from "@/lib/utils";
 import { AiInsightBlock } from "@/features/ai-copilot/components/ai-insight-block";
 function getLast12Months(): string[] {
    const months: string[] = [];
@@ -178,8 +177,8 @@ const GridRow = React.memo(({ virtualRow, row, rowHeight, isSelected, columnVisi
            }}
        >
            {row.getVisibleCells().map((cell: Cell<ProductRow, unknown>) => {
-                const isFlexible = cell.column.id === "libelle1" || cell.column.id === "ai" || cell.column.id === "libelle3";
+                const isFlexible = cell.column.id === "libelle1" || cell.column.id === "libelle3";
-                const isCenter = cell.column.id === "totalQuantite" || cell.column.id === "totalCa" || cell.column.id === "totalMarge" || cell.column.id.startsWith("month_") || cell.column.id === "gammeInitial" || cell.column.id === "score" || cell.column.id === "gamme";
+                const isCenter = cell.column.id === "totalQuantite" || cell.column.id === "totalCa" || cell.column.id === "totalMarge" || cell.column.id.startsWith("month_") || cell.column.id === "gammeInitial" || cell.column.id === "caReseau" || cell.column.id === "qteReseau" || cell.column.id === "nbMagasinsReseau" || cell.column.id === "tauxPresenceReseau" || cell.column.id === "gamme";
                const size = cell.column.getSize();
                return (
                    <td
@@ -507,67 +506,56 @@ export function HeatmapGrid({ onSelectionChange, isAdmin }: HeatmapGridProps) {
            },
        },
        {
-            accessorKey: "score",
+            accessorKey: "caReseau",
-            header: "Score",
+            header: () => <div className="text-center w-full">CA<br/><span className="text-[9px] opacity-60">Réseau</span></div>,
-            size: 60,
+            size: 90,
            cell: ({ getValue }) => {
-                const val = getValue<number>();
+                const val = getValue<number | undefined>();
-                const color = val >= 80 ? "text-emerald-500" : val >= 50 ? "text-amber-500" : "text-rose-500";
+                return (
                    <div className="text-center tabular-nums text-[12px] font-bold text-emerald-600 dark:text-emerald-400">
                        {val != null ? val.toLocaleString("fr-FR", { style: "currency", currency: "EUR", maximumFractionDigits: 0 }) : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "qteReseau",
            header: () => <div className="text-center w-full">Qté<br/><span className="text-[9px] opacity-60">Réseau</span></div>,
            size: 80,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? Math.round(val).toLocaleString("fr-FR") : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "nbMagasinsReseau",
            header: () => <div className="text-center w-full">Magasins<br/><span className="text-[9px] opacity-60">/ 270</span></div>,
            size: 80,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? val : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "tauxPresenceReseau",
            header: () => <div className="text-center w-full">% Prés.<br/><span className="text-[9px] opacity-60">Réseau</span></div>,
            size: 70,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                if (val == null) return <div className="text-center text-[12px]" style={{ color: "var(--text-secondary)" }}>-</div>;
                const pct = Math.round(val * 100);
                const color = pct >= 66 ? "text-emerald-500" : pct >= 33 ? "text-amber-500" : "text-rose-500";
                return (
                    <div className={cn("text-center font-black text-[13px] tabular-nums", color)}>
-                        {val}
+                        {pct}%
                    </div>
                );
            },
        },
        {
            accessorKey: "rankingCa",
            header: () => <div className="text-center w-full">Rk CA<br/><span className="text-[9px] opacity-60">Réseau</span></div>,
            size: 70,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? val : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "rankingQte",
            header: () => <div className="text-center w-full">Rk Qté<br/><span className="text-[9px] opacity-60">Réseau</span></div>,
            size: 70,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? val : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "rankingMagCa",
            header: () => <div className="text-center w-full">Rk CA<br/><span className="text-[9px] opacity-60">Mag.</span></div>,
            size: 70,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? val : "-"}
                    </div>
                );
            },
        },
        {
            accessorKey: "rankingMagQte",
            header: () => <div className="text-center w-full">Rk Qté<br/><span className="text-[9px] opacity-60">Mag.</span></div>,
            size: 70,
            cell: ({ getValue }) => {
                const val = getValue<number | undefined>();
                return (
                    <div className="text-center tabular-nums text-[12px] font-bold" style={{ color: "var(--text-secondary)" }}>
                        {val != null ? val : "-"}
                    </div>
                );
            },
@@ -679,17 +667,6 @@ export function HeatmapGrid({ onSelectionChange, isAdmin }: HeatmapGridProps) {
            size: 110,
            cell: ({ row }) => <GammeCell row={row.original} isAdmin={isAdmin} />,
        },
        {
            id: "ai",
            header: () => <div className="print:hidden">Recommandation IA</div>,
            size: 230,
            enableSorting: false,
            cell: ({ row }) => (
                <div className="print:hidden w-full h-full">
                    <AiInsightBlock row={row.original} />
                </div>
            ),
        },
    ], [MONTHS_12, activeMagasin, isAdmin]); // activeMagasin déclenche re-render des cellules mensuelles et totaux
    const table = useReactTable({
@@ -800,8 +777,8 @@ export function HeatmapGrid({ onSelectionChange, isAdmin }: HeatmapGridProps) {
                        {table.getHeaderGroups().map((headerGroup) => (
                            <tr key={headerGroup.id} className="flex w-full">
                                {headerGroup.headers.map((header) => {
-                                    const isFlexible = header.column.id === "libelle1" || header.column.id === "ai" || header.column.id === "libelle3";
+                                    const isFlexible = header.column.id === "libelle1" || header.column.id === "libelle3";
-                                    const isCenter = header.column.id === "totalQuantite" || header.column.id === "totalCa" || header.column.id === "totalMarge" || header.column.id.startsWith("month_") || header.column.id === "gammeInitial" || header.column.id === "score" || header.column.id === "gamme";
+                                    const isCenter = header.column.id === "totalQuantite" || header.column.id === "totalCa" || header.column.id === "totalMarge" || header.column.id.startsWith("month_") || header.column.id === "gammeInitial" || header.column.id === "caReseau" || header.column.id === "qteReseau" || header.column.id === "nbMagasinsReseau" || header.column.id === "tauxPresenceReseau" || header.column.id === "gamme";
                                    const size = header.getSize();
                                    return (
                                        <th
@@ -110,7 +110,7 @@ export function NoSalesTab() {
                    <div className="sticky top-0 z-10 grid grid-cols-[90px_minmax(220px,1fr)_120px_76px_130px_70px_90px_110px_70px]"
                        style={{ background: "var(--bg-elevated)", borderBottom: "1px solid var(--border)" }}
                    >
-                        {["Code", "Libellé", "Réf.", "Gamme", "Dernière vente", "Jours", "Stock", "CA 12m", "Score"].map(col => (
+                        {["Code", "Libellé", "Réf.", "Gamme", "Dernière vente", "Jours", "Stock", "CA 12m", "Mag."].map(col => (
                            <div key={col}
                                className="px-3 py-2 text-left font-semibold whitespace-nowrap"
                                style={{ color: "var(--text-muted)" }}
@@ -159,8 +159,8 @@ export function NoSalesTab() {
                                        {row.totalCa > 0 ? formatCa(row.totalCa) : "—"}
                                    </div>
                                    <div className="px-3 py-1.5 text-right tabular-nums font-semibold"
-                                        style={{ color: row.score >= 50 ? "var(--color-amber, #f59e0b)" : "var(--text-muted)" }}>
+                                        style={{ color: "var(--text-secondary)" }}>
-                                        {row.score > 0 ? row.score : "—"}
+                                        {row.nbMagasinsReseau != null ? row.nbMagasinsReseau : "—"}
                                    </div>
                                </div>
                            );
@@ -1,104 +0,0 @@
 "use client";
 import { useState, useEffect } from "react";
 import { Button } from "@/components/ui/button";
 import { Dialog, DialogContent, DialogHeader, DialogTitle, DialogDescription, DialogFooter, DialogTrigger } from "@/components/ui/dialog";
 import { Textarea } from "@/components/ui/textarea";
 import { Brain } from "lucide-react";
 interface SupplierAiContextModalProps {
    codeFournisseur: string | null;
    nomFournisseur: string | null;
 }
 export function SupplierAiContextModal({ codeFournisseur, nomFournisseur }: SupplierAiContextModalProps) {
    const [open, setOpen] = useState(false);
    const [context, setContext] = useState("");
    const [isLoading, setIsLoading] = useState(false);
    const [isSaving, setIsSaving] = useState(false);
    useEffect(() => {
        if (open && codeFournisseur) {
            fetchContext();
        }
    }, [open, codeFournisseur]);
    const fetchContext = async () => {
        setIsLoading(true);
        try {
            const res = await fetch(`/api/ai/context?fournisseur=${codeFournisseur}`);
            if (res.ok) {
                const data = await res.json();
                setContext(data.context || "");
            }
        } catch (error) {
            console.error("Failed to load AI context", error);
        } finally {
            setIsLoading(false);
        }
    };
    const handleSave = async () => {
        if (!codeFournisseur) return;
        setIsSaving(true);
        try {
            const res = await fetch("/api/ai/context", {
                method: "POST",
                headers: { "Content-Type": "application/json" },
                body: JSON.stringify({ codeFournisseur, context }),
            });
            if (res.ok) {
                setOpen(false);
            } else {
                console.error("Failed to save AI context");
            }
        } catch (error) {
            console.error("Failed to save AI context", error);
        } finally {
            setIsSaving(false);
        }
    };
    if (!codeFournisseur) return null;
    return (
        <Dialog open={open} onOpenChange={setOpen}>
            <DialogTrigger asChild>
                <button className="apple-btn-rules">
                    <Brain className="w-4 h-4" />
                    Règles IA
                </button>
            </DialogTrigger>
            <DialogContent className="sm:max-w-[500px] bg-white dark:bg-slate-900 border border-slate-200 dark:border-slate-800 shadow-xl">
                <DialogHeader>
                    <DialogTitle>Contexte IA - {nomFournisseur || codeFournisseur}</DialogTitle>
                    <DialogDescription>
                        Définissez ici les règles métier absolues pour ce fournisseur.
                        Mary (l'IA) respectera ces consignes en priorité lors de ses recommandations (ex: "Les calendriers vont en gamme C").
                    </DialogDescription>
                </DialogHeader>
                <div className="py-4">
                    <Textarea
                        placeholder="Ex: Les produits dont le nom contient 'Agenda' doivent toujours être classés en [A]..."
                        value={context}
                        onChange={(e: React.ChangeEvent<HTMLTextAreaElement>) => setContext(e.target.value)}
                        disabled={isLoading}
                        className="min-h-[150px]"
                    />
                </div>
                <DialogFooter>
                    <button className="apple-btn-secondary" onClick={() => setOpen(false)} disabled={isSaving}>
                        Annuler
                    </button>
                    <button onClick={handleSave} disabled={isSaving || isLoading} className="apple-btn-primary">
                        {isSaving ? "Enregistrement..." : "Enregistrer les règles"}
                    </button>
                </DialogFooter>
            </DialogContent>
        </Dialog>
    );
 }
@@ -0,0 +1,82 @@
 "use client";
 import { useState } from "react";
 import { useRouter, usePathname, useSearchParams } from "next/navigation";
 import { Loader2, RefreshCw, CheckCircle, AlertCircle } from "lucide-react";
 interface SyncQlikButtonProps {
    /** Code fournisseur affiché (pour sync ciblée) */
    codeFournisseur?: string;
    /** Date ISO de dernière maj Qlik pour ce fournisseur (max des lignes) */
    lastUpdate?: string | null;
 }
 function formatDate(iso?: string | null): string {
    if (!iso) return "jamais";
    const d = new Date(iso);
    if (isNaN(d.getTime())) return "jamais";
    return d.toLocaleString("fr-FR", { day: "2-digit", month: "2-digit", year: "numeric", hour: "2-digit", minute: "2-digit" });
 }
 /**
 * Bouton admin : synchronise depuis Qlik les métriques réseau du fournisseur affiché
 * (POST /api/qlik/sync?fournisseur=…) puis recharge la grille. Affiche la dernière maj.
 */
 export function SyncQlikButton({ codeFournisseur, lastUpdate }: SyncQlikButtonProps) {
    const [status, setStatus] = useState<"idle" | "loading" | "success" | "error">("idle");
    const [message, setMessage] = useState<string>("");
    const router = useRouter();
    const pathname = usePathname();
    const searchParams = useSearchParams();
    const handleSync = async () => {
        if (!codeFournisseur) {
            setStatus("error");
            setMessage("Aucun fournisseur sélectionné");
            return;
        }
        setStatus("loading");
        setMessage("");
        try {
            const res = await fetch(`/api/qlik/sync?fournisseur=${encodeURIComponent(codeFournisseur)}`, { method: "POST" });
            const data = await res.json();
            if (!res.ok || !data.success) throw new Error(data.error || `HTTP ${res.status}`);
            setStatus("success");
            setMessage(`${data.upserted} produits réseau synchronisés`);
            // Recharge la grille pour afficher les nouvelles données réseau
            const params = new URLSearchParams(searchParams.toString());
            params.set("_refresh", String(Date.now()));
            router.replace(`${pathname}?${params.toString()}`);
            setTimeout(() => setStatus("idle"), 4000);
        } catch (e) {
            setStatus("error");
            setMessage(e instanceof Error ? e.message : String(e));
            setTimeout(() => setStatus("idle"), 6000);
        }
    };
    return (
        <div className="flex flex-col items-end">
            <button
                onClick={handleSync}
                disabled={status === "loading"}
                className="btn-action btn-action-secondary flex items-center gap-1.5 disabled:opacity-60"
                title={message || "Synchroniser les données réseau Qlik pour ce fournisseur"}
            >
                {status === "loading" ? (
                    <Loader2 className="w-3.5 h-3.5 animate-spin" />
                ) : status === "success" ? (
                    <CheckCircle className="w-3.5 h-3.5 text-emerald-500" />
                ) : status === "error" ? (
                    <AlertCircle className="w-3.5 h-3.5 text-rose-500" />
                ) : (
                    <RefreshCw className="w-3.5 h-3.5" />
                )}
                Sync Qlik
            </button>
            <span className="text-[10px] text-slate-500 mt-0.5">
                {status === "error" ? message : `MAJ Qlik : ${formatDate(lastUpdate)}`}
            </span>
        </div>
    );
 }
@@ -496,102 +496,6 @@ export async function getCommandesByFournisseur(
    return result;
 }
 // ---------------------------------------------------------------------------
 // Ranking — classement réseau et magasin
 // GET /api/ranking?codein=<codein>
 // Réponse : { count: number, ranking: RankingEntry[] }
 // Les valeurs ranking sont des string|null, à parser en number.
 // ---------------------------------------------------------------------------
 export interface FfRanking {
    ranking_ca?: number;
    ranking_qte?: number;
    ranking_mag_ca?: number;
    ranking_mag_qte?: number;
    ranking_mag_marge?: number;
    pv_calcule?: number;
    pv_mag?: number;
    pv_cen?: number;
 }
 /** Parse une valeur string|null en number|undefined */
 function parseRankNum(val: string | null | undefined): number | undefined {
    if (val == null || val === "") return undefined;
    const n = Number(val);
    return isNaN(n) ? undefined : n;
 }
 export interface RankingResult {
    rankings: Map<string, FfRanking>;
    /** Nombre total de produits dans le classement (produits avec ventes sur la période) */
    totalRankedProducts: number;
 }
 /**
 * Récupère le ranking réseau pour les articles en 1 seul appel :
 * GET /api/ranking?limit=<N> — récupère tout le classement réseau, puis filtre par codein.
 *
 * Fallback par article individuel si le bulk échoue.
 */
 /**
 * Récupère le ranking par article individuel (GET /api/ranking?codein=<codein>).
 * Appelé seulement pour les articles AVEC ventes — taille raisonnable même pour grands fournisseurs.
 * Le bulk endpoint est capé à 500 résultats par l'API → inutilisable pour matching complet.
 */
 export async function getRankingByArticles(
    articles: { codein: string; gtin?: string }[],
    _codeFournisseur?: string,
 ): Promise<RankingResult> {
    const rankings = new Map<string, FfRanking>();
    if (articles.length === 0) return { rankings, totalRankedProducts: 0 };
    const batchSize = 50;
    for (let i = 0; i < articles.length; i += batchSize) {
        const batch = articles.slice(i, i + batchSize);
        await Promise.all(
            batch.map(async (art) => {
                try {
                    const url = `${FF_API_BASE}/api/ranking?codein=${encodeURIComponent(art.codein)}`;
                    const res = await fetch(url, { cache: "no-store" });
                    if (!res.ok) return;
                    const data = await res.json();
                    const rankingList = data?.ranking;
                    if (!Array.isArray(rankingList) || rankingList.length === 0) return;
                    const entry = rankingList[0] as Record<string, string | null>;
                    rankings.set(art.codein, {
                        ranking_ca: parseRankNum(entry.ranking_ca),
                        ranking_qte: parseRankNum(entry.ranking_qte),
                        ranking_mag_ca: parseRankNum(entry.ranking_mag_ca),
                        ranking_mag_qte: parseRankNum(entry.ranking_mag_qte),
                        ranking_mag_marge: parseRankNum(entry.ranking_mag_marge),
                        pv_calcule: parseRankNum(entry.pv_calcule),
                        pv_mag: parseRankNum(entry.pv_mag),
                        pv_cen: parseRankNum(entry.pv_cen),
                    });
                } catch (err) {
                    console.error(`[api-ff] getRanking error for ${art.codein}:`, err);
                }
            })
        );
    }
    // totalRankedProducts = nombre d'articles ayant un classement réseau
    const totalRankedProducts = rankings.size > 0
        ? await fetchTotalRankedProducts()
        : 0;
    console.log(`[api-ff] Ranking: ${rankings.size}/${articles.length} articles classés (réseau: ${totalRankedProducts})`);
    return { rankings, totalRankedProducts };
 }
 async function fetchTotalRankedProducts(): Promise<number> {
    try {
        const res = await fetch(`${FF_API_BASE}/api/ranking?limit=500`, { cache: "no-store" });
        if (!res.ok) return 0;
        const data = await res.json();
        return (data?.ranking as unknown[])?.length ?? 0;
    } catch { return 0; }
 }
 // ---------------------------------------------------------------------------
 // Statut de synchronisation
 // ---------------------------------------------------------------------------
@@ -39,6 +39,8 @@ async function pgNoParallel(query: SQL): Promise<{ rows: unknown[] }> {
 export interface PgArticle {
    no_id: number;
    codein: string;
    /** Code centrale = articles.artcentrale (format 10000XXXXXX) — clé jointure Qlik "Article Code". Vide pour les articles non référencés centralement. */
    codeCentrale?: string;
    codefou: string;
    nomfou?: string;
    libelle1?: string;
@@ -74,15 +76,6 @@ export interface PgStockRow {
    dernierereception?: string;
 }
 export interface PgRankingRow {
    codein: string;
    site: string;
    ranking_ca?: number;
    ranking_qte?: number;
    ranking_mag_ca?: number;
    ranking_mag_qte?: number;
 }
 // ---------------------------------------------------------------------------
 // 0. Liste des fournisseurs
 // ---------------------------------------------------------------------------
@@ -127,6 +120,7 @@ export async function pgGetArticlesByFournisseur(codefou: string): Promise<PgArt
        SELECT DISTINCT ON (a.no_id)
            a.no_id,
            a.codein,
            a.artcentrale               AS "codeCentrale",
            af.code                     AS codefou,
            fi.nom                      AS nomfou,
            a.libelle1,
@@ -378,79 +372,6 @@ export async function pgGetStockByFournisseur(codefou: string): Promise<Map<stri
    return map;
 }
 // ---------------------------------------------------------------------------
 // 5. Ranking réseau
 // ---------------------------------------------------------------------------
 /**
 * Retourne le classement réseau pour chaque article du fournisseur.
 * 1 requête SQL — remplace getRankingByArticles() (N appels HTTP per-article,
 * capés à 500 par l'API).
 */
 export async function pgGetRankingByFournisseur(codefou: string): Promise<{
    rankings: Map<string, PgRankingRow>;
    totalRankedProducts: number;
 }> {
    // D'abord, découvrir quels sites existent dans la table ranking (réseau vs magasin)
    const [rankResult, totalResult, sitesSample] = await Promise.all([
        pgNoParallel(sql`
            SELECT DISTINCT ON (a.codein)
                a.codein,
                r.site,
                r.ranking_ca,
                r.ranking_qte,
                r.ranking_mag_ca,
                r.ranking_mag_qte
            FROM ranking r
            JOIN art_gtin ag
                ON ag.gtin = r.gencod
            JOIN articles a
                ON a.no_id = ag.idarticle
            JOIN artfou1 af
                ON af.art_no_id = a.no_id AND af.code = ${codefou}
            ORDER BY a.codein,
                CASE
                    WHEN r.site IN ('000', 'ALL', 'TOTAL', 'NET', 'RES') THEN 0
                    ELSE 1
                END,
                r.site
        `),
        pgNoParallel(sql`
            SELECT COUNT(DISTINCT gencod)::int AS total FROM ranking
        `),
        pgNoParallel(sql`
            SELECT DISTINCT site FROM ranking ORDER BY site LIMIT 10
        `),
    ]);
    // Log sites disponibles pour diagnostic ranking
    const sitesDispos = (sitesSample.rows as { site: string }[]).map(r => r.site);
    console.log(`[pg-ff] Ranking sites disponibles:`, sitesDispos.join(", "));
    const rankings = new Map<string, PgRankingRow>();
    for (const row of rankResult.rows as unknown as PgRankingRow[]) {
        if (row.codein) rankings.set(row.codein, row);
    }
    // Log doublons de rank pour diagnostic
    const rankCount = new Map<number, number>();
    for (const r of rankings.values()) {
        if (r.ranking_ca) {
            const v = Number(r.ranking_ca);
            rankCount.set(v, (rankCount.get(v) ?? 0) + 1);
        }
    }
    const dupes = [...rankCount.entries()].filter(([, c]) => c > 1).slice(0, 5);
    if (dupes.length > 0) {
        console.log(`[pg-ff] Ranking doublons détectés (rank → nb articles):`, dupes.map(([r, c]) => `rank${r}×${c}`).join(", "));
    }
    const totalRankedProducts = Number((totalResult.rows[0] as unknown as { total: number })?.total ?? 0);
    console.log(`[pg-ff] Ranking: ${rankings.size} articles classés, réseau total: ${totalRankedProducts}`);
    return { rankings, totalRankedProducts };
 }
 // ---------------------------------------------------------------------------
 // 6. Commandes en cours
 // ---------------------------------------------------------------------------
@@ -0,0 +1,262 @@
 /**
 * CollectFlow — Client Qlik Sense (donnees reseau ~270 magasins)
 *
 * Recupere par produit (cle = code centrale via la dimension "Article Code") :
 *   - CA reseau, Qte vendue reseau, Nb magasins travaillant le produit.
 *
 * Auth = NTLM (Qlik Sense Enterprise on Windows) via flux ticket SSO :
 *   1. GET /hub/ (non authentifie) -> 302 vers le proxy forms, on extrait le targetId
 *   2. NTLM sur /internal_windows_authentication/?targetId=... -> 302 /hub/?qlikTicket=XXX
 *   3. GET /hub/?qlikTicket=XXX -> Qlik pose le cookie X-Qlik-Session
 * Le cookie + Xrfkey servent ensuite pour QRS (REST) et l'Engine API (websocket).
 *
 * Extraction = Engine API (QIX) sur websocket, hypercube generique reference par
 * master items (qLibraryId) -> pas besoin des expressions brutes.
 *
 * Tout est parametrable par variables d'environnement (defauts = discovery 2026-06-20).
 */
 import httpntlm from "httpntlm";
 import { WebSocket } from "ws";
 import { randomBytes } from "node:crypto";
 // ---------------------------------------------------------------------------
 // Config (env) — defauts issus de la discovery
 // ---------------------------------------------------------------------------
 export interface QlikConfig {
    host: string;
    user: string;
    password: string;
    domain: string;        // vide par defaut (NTLM sans domaine, comme requests_ntlm)
    workstation: string;
    appNetwork: string;    // GUID app "Magasins Vision Consolidee" (article x reseau)
    dimCodeArticleId: string; // master dimension "Article Code"
    measCaId: string;         // master measure "CA N"
    measQteId: string;        // master measure "Quantite N"
    measNbMagId: string;      // master measure "Magasin Ventes Nb N"
    tlsInsecure: boolean;
    timeoutMs: number;
 }
 export function getQlikConfig(): QlikConfig {
    return {
        host: process.env.QLIK_HOST ?? "reporting-magasins.lafoirfouille.fr",
        user: process.env.QLIK_USER ?? "FFSCH",
        password: process.env.QLIK_PWD ?? "",
        domain: process.env.QLIK_DOMAIN ?? "",
        workstation: process.env.QLIK_WORKSTATION ?? "",
        appNetwork: process.env.QLIK_APP_NETWORK ?? "9872ee6e-d64a-4b43-984a-076bf1f7f647",
        dimCodeArticleId: process.env.QLIK_DIM_CODE_ARTICLE_ID ?? "fcd239e5-288b-4830-a047-0e3d7665d971",
        measCaId: process.env.QLIK_MEAS_CA_ID ?? "43a76088-86fa-402e-a80e-0efd7701b3e1",
        measQteId: process.env.QLIK_MEAS_QTE_ID ?? "7b40caf1-be4b-4811-8d45-50acde33e715",
        measNbMagId: process.env.QLIK_MEAS_NBMAG_ID ?? "8b63fae5-db2f-4e4c-8618-f3e9d60b6b3b",
        tlsInsecure: (process.env.QLIK_TLS_INSECURE ?? "true") === "true",
        timeoutMs: Number(process.env.QLIK_TIMEOUT_MS ?? "60000"),
    };
 }
 export interface NetworkMetric {
    codeCentrale: string;
    caReseau: number;
    qteReseau: number;
    nbMagasinsReseau: number;
    periode?: string;
 }
 function makeXrfkey(): string {
    return randomBytes(12).toString("base64").replace(/[^a-zA-Z0-9]/g, "").slice(0, 16).padEnd(16, "0");
 }
 // ---------------------------------------------------------------------------
 // 1. Auth NTLM -> ticket SSO -> cookie de session
 // ---------------------------------------------------------------------------
 interface QlikSession {
    cookie: string;
    xrfkey: string;
 }
 function ntlmGet(cfg: QlikConfig, path: string): Promise<{ statusCode: number; headers: Record<string, unknown>; body: string }> {
    return new Promise((resolve, reject) => {
        httpntlm.get(
            {
                url: `https://${cfg.host}${path}`,
                username: cfg.user,
                password: cfg.password,
                domain: cfg.domain,
                workstation: cfg.workstation,
                rejectUnauthorized: !cfg.tlsInsecure,
                headers: { "User-Agent": "Mozilla/5.0 CollectFlow", "X-Qlik-Xrfkey": "" },
            } as unknown as Parameters<typeof httpntlm.get>[0],
            (err: Error | null, res: { statusCode: number; headers: Record<string, unknown>; body: string }) =>
                err ? reject(err) : resolve(res),
        );
    });
 }
 export async function qlikNtlmSession(cfg = getQlikConfig()): Promise<QlikSession> {
    if (!cfg.user || !cfg.password) {
        throw new Error("[qlik] QLIK_USER / QLIK_PWD manquants dans l'environnement");
    }
    const xrfkey = makeXrfkey();
    const tlsRestore = process.env.NODE_TLS_REJECT_UNAUTHORIZED;
    if (cfg.tlsInsecure) process.env.NODE_TLS_REJECT_UNAUTHORIZED = "0";
    try {
        // 1. targetId
        const hub = await fetch(`https://${cfg.host}/hub/`, { redirect: "manual" });
        const loc1 = hub.headers.get("location") ?? "";
        const targetId = (loc1.match(/targetId=([0-9a-f-]+)/i) ?? [])[1] ?? "";
        // 2. NTLM -> ticket. Interne (reseau corp), /hub/ peut deja renvoyer 401 NTLM
        //    et poser le cookie directement ; on gere les 2 cas.
        const winPath = targetId
            ? `/internal_windows_authentication/?targetId=${targetId}&xrfkey=${xrfkey}`
            : `/hub/?xrfkey=${xrfkey}`;
        const ntlm = await ntlmGet(cfg, winPath);
        // Cookie posé directement (cas interne) ?
        const directCookie = extractSessionCookie(ntlm.headers["set-cookie"]);
        if (directCookie) return { cookie: directCookie, xrfkey };
        // 3. Échange ticket -> cookie
        const ticketLoc = String(ntlm.headers["location"] ?? "");
        if (!/qlikTicket=/.test(ticketLoc)) {
            throw new Error(`[qlik] Auth NTLM sans ticket (HTTP ${ntlm.statusCode}) — verifier mot de passe`);
        }
        const exch = await fetch(ticketLoc, { redirect: "manual" });
        const sc = typeof exch.headers.getSetCookie === "function" ? exch.headers.getSetCookie() : [];
        const cookie = sc.map((c) => c.split(";")[0]).filter((c) => /X-Qlik-Session/i.test(c)).join("; ");
        if (!cookie) throw new Error("[qlik] ticket non echange contre un cookie de session");
        return { cookie, xrfkey };
    } finally {
        if (cfg.tlsInsecure) process.env.NODE_TLS_REJECT_UNAUTHORIZED = tlsRestore;
    }
 }
 function extractSessionCookie(setCookie: unknown): string | null {
    const arr = Array.isArray(setCookie) ? setCookie : setCookie ? [String(setCookie)] : [];
    const c = arr.map((x) => String(x).split(";")[0]).find((x) => /X-Qlik-Session/i.test(x));
    return c ?? null;
 }
 // ---------------------------------------------------------------------------
 // 2. Websocket Engine API (QIX) + JSON-RPC minimal
 // ---------------------------------------------------------------------------
 interface RpcConn {
    rpc: (method: string, params: unknown, handle?: number) => Promise<Record<string, unknown>>;
    close: () => void;
 }
 function openEngine(appGuid: string, sess: QlikSession, cfg: QlikConfig): Promise<RpcConn> {
    const url = `wss://${cfg.host}/app/${encodeURIComponent(appGuid)}?Xrfkey=${sess.xrfkey}`;
    return new Promise((resolve, reject) => {
        const ws = new WebSocket(url, {
            headers: { Cookie: sess.cookie, "X-Qlik-Xrfkey": sess.xrfkey },
            rejectUnauthorized: !cfg.tlsInsecure,
            handshakeTimeout: cfg.timeoutMs,
        });
        let nextId = 1;
        const pending = new Map<number, { resolve: (v: Record<string, unknown>) => void; reject: (e: Error) => void }>();
        const timer = setTimeout(() => { ws.terminate(); reject(new Error("[qlik] timeout engine")); }, cfg.timeoutMs);
        ws.on("message", (raw: Buffer) => {
            let msg: Record<string, unknown>;
            try { msg = JSON.parse(raw.toString()); } catch { return; }
            if (msg.method === "OnConnected") { clearTimeout(timer); resolve(conn); return; }
            const id = msg.id as number | undefined;
            if (id != null && pending.has(id)) {
                const p = pending.get(id)!;
                pending.delete(id);
                if (msg.error) p.reject(new Error(`[qlik] RPC ${JSON.stringify(msg.error)}`));
                else p.resolve(msg.result as Record<string, unknown>);
            }
        });
        ws.on("unexpected-response", (_req, res) => { clearTimeout(timer); reject(new Error(`[qlik] ws HTTP ${res.statusCode}`)); });
        ws.on("error", (e: Error) => { clearTimeout(timer); reject(e); });
        ws.on("close", () => { for (const p of pending.values()) p.reject(new Error("[qlik] ws ferme")); pending.clear(); });
        const rpc = (method: string, params: unknown, handle = -1) =>
            new Promise<Record<string, unknown>>((res, rej) => {
                const id = nextId++;
                pending.set(id, { resolve: res, reject: rej });
                ws.send(JSON.stringify({ jsonrpc: "2.0", id, handle, method, params }));
            });
        const conn: RpcConn = { rpc, close: () => ws.close() };
    });
 }
 // ---------------------------------------------------------------------------
 // 3. Extraction hypercube (master items) -> NetworkMetric[]
 // ---------------------------------------------------------------------------
 function hyperCubeDef(cfg: QlikConfig, height: number) {
    return {
        qInfo: { qType: "collectflow-network" },
        qHyperCubeDef: {
            qDimensions: [{ qLibraryId: cfg.dimCodeArticleId, qNullSuppression: true }],
            qMeasures: [
                { qLibraryId: cfg.measCaId },
                { qLibraryId: cfg.measQteId },
                { qLibraryId: cfg.measNbMagId },
            ],
            qInitialDataFetch: [{ qTop: 0, qLeft: 0, qWidth: 4, qHeight: height }],
            qSuppressZero: false,
            qSuppressMissing: true,
        },
    };
 }
 type Matrix = Array<Array<{ qText?: string; qNum?: number }>>;
 export async function fetchNetworkMetrics(
    codeCentraux?: string[],
    cfg = getQlikConfig(),
 ): Promise<Map<string, NetworkMetric>> {
    if (!cfg.appNetwork) throw new Error("[qlik] QLIK_APP_NETWORK manquant");
    const wanted = codeCentraux ? new Set(codeCentraux) : null;
    const out = new Map<string, NetworkMetric>();
    const sess = await qlikNtlmSession(cfg);
    const conn = await openEngine(cfg.appNetwork, sess, cfg);
    try {
        const openRes = await conn.rpc("OpenDoc", { qDocName: cfg.appNetwork });
        const docHandle = (((openRes.qReturn as Record<string, unknown>) ?? {}).qHandle as number) ?? 1;
        const pageHeight = 2500; // 4 colonnes * 2500 = 10000 cellules max
        const createRes = await conn.rpc("CreateSessionObject", { qProp: hyperCubeDef(cfg, pageHeight) }, docHandle);
        const objHandle = (((createRes.qReturn as Record<string, unknown>) ?? {}).qHandle as number);
        let top = 0;
        for (;;) {
            const dataRes = await conn.rpc(
                "GetHyperCubeData",
                { qPath: "/qHyperCubeDef", qPages: [{ qTop: top, qLeft: 0, qWidth: 4, qHeight: pageHeight }] },
                objHandle,
            );
            const pages = (dataRes.qDataPages as Array<{ qMatrix?: Matrix }>) ?? [];
            const matrix: Matrix = pages[0]?.qMatrix ?? [];
            if (matrix.length === 0) break;
            for (const row of matrix) {
                const codeCentrale = (row[0]?.qText ?? "").trim();
                if (!codeCentrale) continue;
                if (wanted && !wanted.has(codeCentrale)) continue;
                out.set(codeCentrale, {
                    codeCentrale,
                    caReseau: Number(row[1]?.qNum ?? 0) || 0,
                    qteReseau: Number(row[2]?.qNum ?? 0) || 0,
                    nbMagasinsReseau: Number(row[3]?.qNum ?? 0) || 0,
                });
            }
            if (matrix.length < pageHeight) break;
            top += matrix.length;
        }
    } finally {
        conn.close();
    }
    console.log(`[qlik] fetchNetworkMetrics: ${out.size} produits reseau`);
    return out;
 }
@@ -0,0 +1,79 @@
 /**
 * CollectFlow — Cache des metriques reseau Qlik (table qlik_network_metrics).
 *
 * Lecture par lot (jointure grille) + upsert masse (route de sync).
 */
 import "server-only";
 import { db } from "@/db";
 import { qlikNetworkMetrics } from "@/db/schema";
 import { inArray, sql } from "drizzle-orm";
 import type { NetworkMetric } from "@/lib/qlik-client";
 export interface NetworkMetricCached {
    caReseau: number;
    qteReseau: number;
    nbMagasinsReseau: number;
    fetchedAt: string | null;
 }
 /** Lit les metriques reseau pour une liste de codes centraux. */
 export async function getNetworkMetricsByCodeCentrale(
    codes: string[],
 ): Promise<Map<string, NetworkMetricCached>> {
    const out = new Map<string, NetworkMetricCached>();
    const unique = [...new Set(codes.filter(Boolean))];
    if (unique.length === 0) return out;
    const rows = await db
        .select()
        .from(qlikNetworkMetrics)
        .where(inArray(qlikNetworkMetrics.codeCentrale, unique));
    for (const r of rows) {
        out.set(r.codeCentrale, {
            caReseau: Number(r.caReseau ?? 0) || 0,
            qteReseau: Number(r.qteReseau ?? 0) || 0,
            nbMagasinsReseau: Number(r.nbMagasinsReseau ?? 0) || 0,
            fetchedAt: r.fetchedAt ? new Date(r.fetchedAt).toISOString() : null,
        });
    }
    return out;
 }
 /** Upsert en masse des metriques reseau (depuis Qlik). */
 export async function upsertNetworkMetrics(metrics: NetworkMetric[]): Promise<number> {
    if (metrics.length === 0) return 0;
    const now = new Date();
    const values = metrics.map((m) => ({
        codeCentrale: m.codeCentrale,
        caReseau: String(m.caReseau),
        qteReseau: String(m.qteReseau),
        nbMagasinsReseau: m.nbMagasinsReseau,
        periode: m.periode ?? null,
        fetchedAt: now,
    }));
    // Upsert par paquets pour eviter les requetes trop volumineuses.
    const chunk = 500;
    let count = 0;
    for (let i = 0; i < values.length; i += chunk) {
        const batch = values.slice(i, i + chunk);
        await db
            .insert(qlikNetworkMetrics)
            .values(batch)
            .onConflictDoUpdate({
                target: qlikNetworkMetrics.codeCentrale,
                set: {
                    caReseau: sql`excluded.ca_reseau`,
                    qteReseau: sql`excluded.qte_reseau`,
                    nbMagasinsReseau: sql`excluded.nb_magasins_reseau`,
                    periode: sql`excluded.periode`,
                    fetchedAt: sql`excluded.fetched_at`,
                },
            });
        count += batch.length;
    }
    return count;
 }
@@ -1,234 +0,0 @@
 /**
 * CollectFlow — Score Engine v4 (Hybride Absolu + Relatif)
 *
 * Calcule le score de performance d'un produit en combinant :
 * - Performance ABSOLUE : Volume (50pts), CA (30pts), Marge (20pts)
 * - Ajustement RELATIF  : Position dans le lot fournisseur (±10pts)
 * - Pénalité de régularité : multiplicateur si inactivité prolongée
 *
 * Score final : 0-100, sensible au prix unitaire.
 *
 * Exemples :
 *   - 0.80€ × 100 unités (80€ CA) → ~53 (bon trafic malgré petit CA)
 *   - 40€ × 2 unités (80€ CA)     → ~19 (faible rotation)
 *   - 500€ CA, 200u, 45% marge    → ~90 (star)
 *   - 8€ CA, 2 unités              → ~13 (stock mort)
 */
 import type { ProductRow } from "@/types/grid";
 // ---------------------------------------------------------------------------
 // Helpers
 // ---------------------------------------------------------------------------
 /** Interpolation linéaire entre deux paliers */
 function lerp(value: number, minVal: number, maxVal: number, minPts: number, maxPts: number): number {
    if (value >= maxVal) return maxPts;
    if (value <= minVal) return minPts;
    return minPts + ((value - minVal) / (maxVal - minVal)) * (maxPts - minPts);
 }
 /** Score Volume (0-50) basé sur unités / magasin / mois */
 function computeVolumeScore(unitsPerStorePerMonth: number): number {
    if (unitsPerStorePerMonth >= 10) return 50;
    if (unitsPerStorePerMonth >= 5) return lerp(unitsPerStorePerMonth, 5, 10, 40, 50);
    if (unitsPerStorePerMonth >= 2) return lerp(unitsPerStorePerMonth, 2, 5, 30, 40);
    if (unitsPerStorePerMonth >= 1) return lerp(unitsPerStorePerMonth, 1, 2, 20, 30);
    if (unitsPerStorePerMonth >= 0.5) return lerp(unitsPerStorePerMonth, 0.5, 1, 10, 20);
    return lerp(unitsPerStorePerMonth, 0, 0.5, 0, 10);
 }
 /** Score CA (0-30) basé sur CA € / magasin / an */
 function computeCaScore(caPerStorePerYear: number): number {
    if (caPerStorePerYear >= 500) return 30;
    if (caPerStorePerYear >= 200) return lerp(caPerStorePerYear, 200, 500, 22, 30);
    if (caPerStorePerYear >= 100) return lerp(caPerStorePerYear, 100, 200, 15, 22);
    if (caPerStorePerYear >= 50) return lerp(caPerStorePerYear, 50, 100, 8, 15);
    return lerp(caPerStorePerYear, 0, 50, 0, 8);
 }
 /** Score Marge (0-20) basé sur taux de marge % */
 function computeMargeScore(tauxMarge: number): number {
    if (tauxMarge >= 50) return 20;
    if (tauxMarge >= 40) return lerp(tauxMarge, 40, 50, 16, 20);
    if (tauxMarge >= 30) return lerp(tauxMarge, 30, 40, 12, 16);
    if (tauxMarge >= 20) return lerp(tauxMarge, 20, 30, 8, 12);
    return lerp(tauxMarge, 0, 20, 0, 8);
 }
 /** Rangs percentiles (0-100) pour un tableau de valeurs numériques. */
 function computePercentileRanks(values: number[]): number[] {
    const n = values.length;
    if (n === 0) return [];
    if (n === 1) return [50];
    const indexed = values.map((v, i) => ({ v, i }));
    indexed.sort((a, b) => a.v - b.v);
    const ranks = new Array<number>(n);
    let i = 0;
    while (i < n) {
        let j = i;
        while (j < n && indexed[j].v === indexed[i].v) j++;
        const avgRank = ((i + j - 1) / 2) / (n - 1) * 100;
        for (let k = i; k < j; k++) {
            ranks[indexed[k].i] = Math.round(avgRank);
        }
        i = j;
    }
    return ranks;
 }
 // ---------------------------------------------------------------------------
 // API publique
 // ---------------------------------------------------------------------------
 /**
 * Calcule les scores pour un ensemble de produits d'un même fournisseur.
 * Les rows sont modifiées en place et retournées.
 */
 export function computeProductScores(rows: ProductRow[]): ProductRow[] {
    if (rows.length === 0) return rows;
    // 1. Données pondérées pour normalisation multi-magasins
    const weightedData = rows.map((r) => {
        const storeCount = Math.max(1, r.workingStores?.length || 1);
        const weight = storeCount === 1 ? 2 : 1;
        // Régularité : nombre de mois avec au moins 1 vente
        const regScore = Object.values(r.sales12m || {}).filter((v) => v > 0).length;
        // Inactivité : mois sans vente en fin de fenêtre
        const allMonths = Object.keys(r.sales12m || {});
        const refMonth = allMonths.length > 0 ? Math.max(...allMonths.map(m => parseInt(m))).toString() : "";
        const salesMonths = Object.entries(r.sales12m || {})
            .filter(([, qty]) => qty > 0)
            .map(([m]) => parseInt(m))
            .sort((a, b) => b - a);
        const lastSaleMonth = salesMonths.length > 0 ? salesMonths[0].toString() : "";
        let inactivity = 0;
        if (refMonth && lastSaleMonth) {
            const refY = parseInt(refMonth.substring(0, 4));
            const refM = parseInt(refMonth.substring(4, 6));
            const lastY = parseInt(lastSaleMonth.substring(0, 4));
            const lastM = parseInt(lastSaleMonth.substring(4, 6));
            inactivity = (refY - lastY) * 12 + (refM - lastM);
        } else if (refMonth && !lastSaleMonth) {
            // Jamais vendu sur la fenêtre → inactivité maximale
            inactivity = 24;
        }
        return {
            row: r,
            storeCount,
            weight,
            wQty: (r.totalQuantite ?? 0) * weight,
            wCa: (r.totalCa ?? 0) * weight,
            tauxMarge: Number.isFinite(r.tauxMarge) ? r.tauxMarge : 0,
            regScore,
            inactivity,
        };
    });
    // 2. Totaux fournisseur
    const totalQty = weightedData.reduce((acc, d) => acc + d.wQty, 0);
    const totalCa = weightedData.reduce((acc, d) => acc + d.wCa, 0);
    const totalMarge = weightedData.reduce((sum, d) => sum + d.tauxMarge, 0);
    const avgQty = rows.length > 0 ? totalQty / rows.length : 0;
    // 3. Totaux par rayon (code2)
    const rayonTotals = new Map<string, { total: number; count: number }>();
    weightedData.forEach((d) => {
        const r2 = d.row.code2 || "default";
        const current = rayonTotals.get(r2) || { total: 0, count: 0 };
        rayonTotals.set(r2, { total: current.total + d.wQty, count: current.count + 1 });
    });
    // 4. Percentiles dans le lot (pour le bonus relatif)
    const caPctRanks = computePercentileRanks(weightedData.map(d => d.wCa));
    const qtyPctRanks = computePercentileRanks(weightedData.map(d => d.wQty));
    const margePctRanks = computePercentileRanks(weightedData.map(d => d.tauxMarge));
    // 5. Seuil top 30% CA pour le flag isTop30Supplier
    const sortedCa = [...weightedData.map(d => d.wCa)].sort((a, b) => b - a);
    const top30Idx = Math.max(0, Math.ceil(sortedCa.length * 0.3) - 1);
    const top30CaThreshold = sortedCa[top30Idx] ?? 0;
    // 6. Score de chaque produit
    for (let idx = 0; idx < weightedData.length; idx++) {
        const d = weightedData[idx];
        const r = d.row;
        // --- Guard absolu : aucune vente → score 0, quelle que soit la marge ou le ranking ---
        if (d.wQty === 0 && d.wCa === 0) {
            r.avgQtyFournisseur   = avgQty;
            r.totalFournisseurCa  = totalCa;
            r.shareQty            = 0;
            r.shareCa             = 0;
            r.shareMarge          = 0;
            const r2z             = r.code2 || "default";
            const rStat           = rayonTotals.get(r2z);
            r.avgQtyRayon         = rStat ? rStat.total / rStat.count : 0;
            r.unitsPerStorePerMonth = 0;
            r.caPerStorePerYear   = 0;
            r.score               = 0;
            r.isRecent            = true;
            r.isLastProduct       = rows.length === 1;
            r.isTop30Supplier     = false;
            continue;
        }
        // --- Métriques de contexte (inchangées, pour l'IA et l'affichage) ---
        r.avgQtyFournisseur = avgQty;
        r.totalFournisseurCa = totalCa;
        r.shareQty = totalQty > 0 ? (d.wQty / totalQty) * 100 : 0;
        r.shareCa = totalCa > 0 ? (d.wCa / totalCa) * 100 : 0;
        r.shareMarge = totalMarge > 0 ? (d.tauxMarge / totalMarge) * 100 : 0;
        const r2 = r.code2 || "default";
        const rayonStat = rayonTotals.get(r2);
        r.avgQtyRayon = rayonStat ? rayonStat.total / rayonStat.count : 0;
        // --- KPIs normalisés (sensibles au prix) ---
        const activeMonths = Math.max(d.regScore, 3); // plancher 3 mois
        const unitsPerStorePerMonth = d.wQty / (d.storeCount * activeMonths);
        const caPerStorePerYear = d.wCa / d.storeCount;
        r.unitsPerStorePerMonth = Math.round(unitsPerStorePerMonth * 100) / 100;
        r.caPerStorePerYear = Math.round(caPerStorePerYear * 100) / 100;
        // --- Score absolu (Volume + CA + Marge = 0-100 pts) ---
        const volumeScore = computeVolumeScore(unitsPerStorePerMonth);
        const caScore = computeCaScore(caPerStorePerYear);
        const margeScore = computeMargeScore(d.tauxMarge);
        // --- Bonus relatif (±10 pts) ---
        const pctComposite = (caPctRanks[idx] * 0.40 + qtyPctRanks[idx] * 0.35 + margePctRanks[idx] * 0.25);
        const relativeBonus = ((pctComposite - 50) / 50) * 10;
        // --- Pénalité de régularité ---
        let regularityMultiplier = 1;
        if (d.regScore <= 2 && d.inactivity >= 6) {
            regularityMultiplier = 0.3;
        } else if (d.regScore <= 2 && d.inactivity >= 3) {
            regularityMultiplier = 0.5;
        } else if (d.inactivity >= 6) {
            regularityMultiplier = 0.5;
        } else if (d.inactivity >= 3) {
            regularityMultiplier = 0.7;
        }
        // --- Score final ---
        const rawScore = (volumeScore + caScore + margeScore + relativeBonus) * regularityMultiplier;
        r.score = Math.round(Math.max(0, Math.min(100, rawScore)) * 10) / 10;
        // --- Flags de protection ---
        r.isRecent = d.regScore <= 3;
        r.isLastProduct = rows.length === 1;
        r.isTop30Supplier = d.wCa >= top30CaThreshold && top30CaThreshold > 0;
    }
    return rows;
 }
@@ -73,8 +73,6 @@ export interface ProductRow {
    totalCa: number;
    totalMarge: number;
    tauxMarge: number;
    /** Score de performance hybride (0-100) */
    score: number;
    workingStores: string[];
    /** Rotation normalisée : unités vendues / magasin / mois */
    unitsPerStorePerMonth?: number;
@@ -86,7 +84,6 @@ export interface ProductRow {
    isLastProduct?: boolean;
    /** Top 30% CA du lot fournisseur */
    isTop30Supplier?: boolean;
    aiRecommendation?: string | null;
    /** SQL Server internal ID — nécessaire pour /api/articles/:noid/mensuel */
    noid?: number;
    /** Données stock & approvisionnement (API FF Nancy) */
@@ -110,14 +107,16 @@ export interface ProductRow {
    shareQty?: number;
    /** Référentiels globaux */
    totalFournisseurCa?: number;
-    /** Ranking réseau (classement global) */
+    /** Code centrale (clé jointure Qlik, format 10000XXXXXX) */
-    rankingCa?: number;
+    codeCentrale?: string;
-    rankingQte?: number;
+    /** Données réseau Qlik (~270 magasins) */
-    /** Ranking magasin */
+    caReseau?: number;
-    rankingMagCa?: number;
+    qteReseau?: number;
-    rankingMagQte?: number;
+    nbMagasinsReseau?: number;
-    /** Nombre total de produits classés dans le réseau (produits avec ventes sur la période) */
+    /** Taux de présence réseau = nbMagasinsReseau / 270 */
-    totalRankedProducts?: number;
+    tauxPresenceReseau?: number;
    /** Fraîcheur des données réseau (ISO) */
    networkFetchedAt?: string;
 }
 /** Summary bar totals for the currently visible/filtered rows */
@@ -0,0 +1,23 @@
 declare module "httpntlm" {
    interface NtlmOptions {
        url: string;
        username: string;
        password: string;
        domain?: string;
        workstation?: string;
        headers?: Record<string, string>;
        rejectUnauthorized?: boolean;
        [key: string]: unknown;
    }
    interface NtlmResponse {
        statusCode: number;
        headers: Record<string, unknown>;
        body: string;
    }
    type Cb = (err: Error | null, res: NtlmResponse) => void;
    const httpntlm: {
        get(opts: NtlmOptions, cb: Cb): void;
        post(opts: NtlmOptions, cb: Cb): void;
    };
    export default httpntlm;
 }