seogeneratorserver/lib/main_modulaire.js

// ========================================
// MAIN MODULAIRE - PIPELINE ARCHITECTURALE MODERNE
// Responsabilité: Orchestration workflow avec architecture modulaire complète
// Usage: node main_modulaire.js [rowNumber] [stackType]
// ========================================

const { logSh } = require('./ErrorReporting');
const { tracer } = require('./trace');

// Imports pipeline de base
const { readInstructionsData, selectPersonalityWithAI, getPersonalities } = require('./BrainConfig');
const { extractElements, buildSmartHierarchy } = require('./ElementExtraction');
const { generateMissingKeywords } = require('./MissingKeywords');
const { generateSimple } = require('./ContentGeneration');
const { injectGeneratedContent } = require('./ContentAssembly');
const { saveGeneratedArticleOrganic } = require('./ArticleStorage');

// Imports modules modulaires
const { applySelectiveLayer } = require('./selective-enhancement/SelectiveCore');
const { 
  applyPredefinedStack, 
  applyAdaptiveLayers,
  getAvailableStacks 
} = require('./selective-enhancement/SelectiveLayers');
const { 
  applyAdversarialLayer 
} = require('./adversarial-generation/AdversarialCore');
const { 
  applyPredefinedStack: applyAdversarialStack 
} = require('./adversarial-generation/AdversarialLayers');
const {
  applyHumanSimulationLayer
} = require('./human-simulation/HumanSimulationCore');
const {
  applyPredefinedSimulation,
  getAvailableSimulationStacks,
  recommendSimulationStack
} = require('./human-simulation/HumanSimulationLayers');
const {
  applyPatternBreakingLayer
} = require('./pattern-breaking/PatternBreakingCore');
const {
  applyPatternBreakingStack,
  recommendPatternBreakingStack,
  listAvailableStacks: listPatternBreakingStacks
} = require('./pattern-breaking/PatternBreakingLayers');

/**
 * WORKFLOW MODULAIRE PRINCIPAL
 */
async function handleModularWorkflow(config = {}) {
  return await tracer.run('MainModulaire.handleModularWorkflow()', async () => {
    const {
      rowNumber = 2,
      selectiveStack = 'standardEnhancement',  // lightEnhancement, standardEnhancement, fullEnhancement, personalityFocus, fluidityFocus, adaptive
      adversarialMode = 'light',               // none, light, standard, heavy, adaptive
      humanSimulationMode = 'none',            // none, lightSimulation, standardSimulation, heavySimulation, adaptiveSimulation, personalityFocus, temporalFocus
      patternBreakingMode = 'none',            // none, lightPatternBreaking, standardPatternBreaking, heavyPatternBreaking, adaptivePatternBreaking, syntaxFocus, connectorsFocus
      saveIntermediateSteps = true,            // 🆕 NOUVELLE OPTION: Sauvegarder chaque étape
      source = 'main_modulaire'
    } = config;

    await tracer.annotate({
      modularWorkflow: true,
      rowNumber,
      selectiveStack,
      adversarialMode,
      humanSimulationMode,
      patternBreakingMode,
      source
    });

    const startTime = Date.now();
    logSh(`🚀 WORKFLOW MODULAIRE DÉMARRÉ`, 'INFO');
    logSh(`   📊 Ligne: ${rowNumber} | Selective: ${selectiveStack} | Adversarial: ${adversarialMode} | Human: ${humanSimulationMode} | Pattern: ${patternBreakingMode}`, 'INFO');

    try {
      // ========================================
      // PHASE 1: PRÉPARATION DONNÉES
      // ========================================
      logSh(`📋 PHASE 1: Préparation données`, 'INFO');
      
      const csvData = await readInstructionsData(rowNumber);
      if (!csvData) {
        throw new Error(`Impossible de lire les données ligne ${rowNumber}`);
      }
      
      const personalities = await getPersonalities();
      const selectedPersonality = await selectPersonalityWithAI(
        csvData.mc0,
        csvData.t0,
        personalities
      );
      
      csvData.personality = selectedPersonality;
      
      logSh(`   ✅ Données: ${csvData.mc0} | Personnalité: ${selectedPersonality.nom}`, 'DEBUG');

      // ========================================
      // PHASE 2: EXTRACTION ÉLÉMENTS
      // ========================================
      logSh(`📝 PHASE 2: Extraction éléments XML`, 'INFO');
      
      const elements = await extractElements(csvData.xmlTemplate, csvData);
      logSh(`   ✅ ${elements.length} éléments extraits`, 'DEBUG');

      // ========================================
      // PHASE 3: GÉNÉRATION MOTS-CLÉS MANQUANTS
      // ========================================
      logSh(`🔍 PHASE 3: Génération mots-clés manquants`, 'INFO');
      
      const finalElements = await generateMissingKeywords(elements, csvData);
      logSh(`   ✅ Mots-clés complétés`, 'DEBUG');

      // ========================================
      // PHASE 4: CONSTRUCTION HIÉRARCHIE
      // ========================================
      logSh(`🏗️ PHASE 4: Construction hiérarchie`, 'INFO');
      
      const hierarchy = await buildSmartHierarchy(finalElements);
      logSh(`   ✅ ${Object.keys(hierarchy).length} sections hiérarchisées`, 'DEBUG');

      // ========================================
      // PHASE 5: GÉNÉRATION CONTENU DE BASE
      // ========================================
      logSh(`💫 PHASE 5: Génération contenu de base`, 'INFO');
      
      const generatedContent = await generateSimple(hierarchy, csvData);
      
      logSh(`   ✅ ${Object.keys(generatedContent).length} éléments générés`, 'DEBUG');

      // 🆕 SAUVEGARDE ÉTAPE 1: Génération initiale
      let parentArticleId = null;
      let versionHistory = [];
      
      if (saveIntermediateSteps) {
        logSh(`💾 SAUVEGARDE v1.0: Génération initiale`, 'INFO');
        
        const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
        const initialAssembledContent = await injectGeneratedContent(xmlString, generatedContent, finalElements);
        
        const initialStorage = await saveGeneratedArticleOrganic({ generatedTexts: generatedContent }, csvData, {
          version: 'v1.0',
          stage: 'initial_generation',
          source: `${source}_initial`,
          stageDescription: 'Génération de contenu de base sans améliorations',
          useVersionedSheet: true  // 🆕 Utiliser Generated_Articles_Versioned
        });
        
        parentArticleId = initialStorage.articleId;
        versionHistory.push({
          version: 'v1.0',
          stage: 'initial_generation',
          articleId: initialStorage.articleId,
          length: initialStorage.textLength,
          wordCount: initialStorage.wordCount
        });
        
        logSh(`   ✅ Sauvé v1.0 - ID: ${parentArticleId}`, 'DEBUG');
      }

      // ========================================
      // PHASE 6: SELECTIVE ENHANCEMENT MODULAIRE
      // ========================================
      logSh(`🔧 PHASE 6: Selective Enhancement Modulaire (${selectiveStack})`, 'INFO');
      
      let selectiveResult;
      
      switch (selectiveStack) {
        case 'adaptive':
          selectiveResult = await applyAdaptiveLayers(generatedContent, {
            maxIntensity: 1.1,
            analysisThreshold: 0.3,
            csvData
          });
          break;
          
        case 'technical':
        case 'transitions':  
        case 'style':
          selectiveResult = await applySelectiveLayer(generatedContent, {
            layerType: selectiveStack,
            llmProvider: 'auto',
            intensity: 1.0,
            csvData
          });
          break;
          
        default:
          // Stack prédéfini
          selectiveResult = await applyPredefinedStack(generatedContent, selectiveStack, {
            csvData,
            analysisMode: true
          });
      }
      
      const enhancedContent = selectiveResult.content;
      
      logSh(`   ✅ Selective: ${selectiveResult.stats.elementsEnhanced || selectiveResult.stats.totalModifications || 0} améliorations`, 'INFO');

      // 🆕 SAUVEGARDE ÉTAPE 2: Selective Enhancement
      if (saveIntermediateSteps) {
        logSh(`💾 SAUVEGARDE v1.1: Selective Enhancement`, 'INFO');
        
        const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
        const selectiveAssembledContent = await injectGeneratedContent(xmlString, enhancedContent, finalElements);
        
        const selectiveStorage = await saveGeneratedArticleOrganic({ generatedTexts: enhancedContent }, csvData, {
          version: 'v1.1',
          stage: 'selective_enhancement',
          source: `${source}_selective_${selectiveStack}`,
          stageDescription: `Amélioration selective (${selectiveStack}) - ${selectiveResult.stats.elementsEnhanced || selectiveResult.stats.totalModifications || 0} modifications`,
          parentArticleId: parentArticleId,
          useVersionedSheet: true  // 🆕 Utiliser Generated_Articles_Versioned
        });
        
        versionHistory.push({
          version: 'v1.1',
          stage: 'selective_enhancement',
          articleId: selectiveStorage.articleId,
          length: selectiveStorage.textLength,
          wordCount: selectiveStorage.wordCount,
          modifications: selectiveResult.stats.elementsEnhanced || selectiveResult.stats.totalModifications || 0
        });
        
        logSh(`   ✅ Sauvé v1.1 - ID: ${selectiveStorage.articleId}`, 'DEBUG');
      }
      
      // ========================================
      // PHASE 7: ADVERSARIAL ENHANCEMENT (OPTIONNEL)
      // ========================================
      let finalContent = enhancedContent;
      let adversarialStats = null;
      
      if (adversarialMode !== 'none') {
        logSh(`🎯 PHASE 7: Adversarial Enhancement (${adversarialMode})`, 'INFO');
        
        let adversarialResult;
        
        switch (adversarialMode) {
          case 'adaptive':
            // Utiliser adversarial adaptatif
            adversarialResult = await applyAdversarialLayer(enhancedContent, {
              detectorTarget: 'general',
              method: 'hybrid',
              intensity: 0.8,
              analysisMode: true
            });
            break;
            
          case 'light':
          case 'standard':
          case 'heavy':
            // Utiliser stack adversarial prédéfini
            const stackMapping = {
              light: 'lightDefense',
              standard: 'standardDefense', 
              heavy: 'heavyDefense'
            };
            
            adversarialResult = await applyAdversarialStack(enhancedContent, stackMapping[adversarialMode], {
              csvData
            });
            break;
        }
        
        if (adversarialResult && !adversarialResult.fallback) {
          finalContent = adversarialResult.content;
          adversarialStats = adversarialResult.stats;
          
          logSh(`   ✅ Adversarial: ${adversarialStats.elementsModified || adversarialStats.totalModifications || 0} modifications`, 'INFO');
          
          // 🆕 SAUVEGARDE ÉTAPE 3: Adversarial Enhancement
          if (saveIntermediateSteps) {
            logSh(`💾 SAUVEGARDE v1.2: Adversarial Enhancement`, 'INFO');
            
            const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
            const adversarialAssembledContent = await injectGeneratedContent(xmlString, finalContent, finalElements);
            
            const adversarialStorage = await saveGeneratedArticleOrganic({ generatedTexts: finalContent }, csvData, {
              version: 'v1.2',
              stage: 'adversarial_enhancement',
              source: `${source}_adversarial_${adversarialMode}`,
              stageDescription: `Amélioration adversarial (${adversarialMode}) - ${adversarialStats.elementsModified || adversarialStats.totalModifications || 0} modifications`,
              parentArticleId: parentArticleId,
              useVersionedSheet: true  // 🆕 Utiliser Generated_Articles_Versioned
            });
            
            versionHistory.push({
              version: 'v1.2',
              stage: 'adversarial_enhancement',
              articleId: adversarialStorage.articleId,
              length: adversarialStorage.textLength,
              wordCount: adversarialStorage.wordCount,
              modifications: adversarialStats.elementsModified || adversarialStats.totalModifications || 0
            });
            
            logSh(`   ✅ Sauvé v1.2 - ID: ${adversarialStorage.articleId}`, 'DEBUG');
          }
        } else {
          logSh(`   ⚠️ Adversarial fallback: contenu selective préservé`, 'WARNING');
        }
      }

      // ========================================
      // PHASE 8: HUMAN SIMULATION (NIVEAU 5)
      // ========================================
      let humanSimulationStats = null;
      
      if (humanSimulationMode !== 'none') {
        logSh(`🧠 PHASE 8: Human Simulation (${humanSimulationMode})`, 'INFO');
        
        let humanSimulationResult;
        
        try {
          // Calculer éléments pour simulation fatigue
          const totalElements = Object.keys(finalContent).length;
          const elementIndex = Math.floor(totalElements * 0.6); // Position simulée milieu-fin pour fatigue
          
          // Configuration simulation
          const simulationConfig = {
            elementIndex,
            totalElements,
            currentHour: new Date().getHours(),
            csvData,
            source: `human_simulation_${humanSimulationMode}`
          };
          
          // Application selon mode
          switch (humanSimulationMode) {
            case 'adaptiveSimulation':
              // Recommandation automatique si adaptive
              const context = {
                contentLength: Object.values(finalContent).join('').length,
                personality: csvData.personality?.nom,
                hour: new Date().getHours(),
                goal: 'adaptive'
              };
              const recommendedStack = recommendSimulationStack(context);
              logSh(`   🤖 Recommandation adaptive: ${recommendedStack}`, 'DEBUG');
              
              humanSimulationResult = await applyPredefinedSimulation(finalContent, recommendedStack, simulationConfig);
              break;
              
            case 'lightSimulation':
            case 'standardSimulation': 
            case 'heavySimulation':
            case 'personalityFocus':
            case 'temporalFocus':
              // Stack prédéfini
              humanSimulationResult = await applyPredefinedSimulation(finalContent, humanSimulationMode, simulationConfig);
              break;
              
            default:
              // Mode custom ou direct
              humanSimulationResult = await applyHumanSimulationLayer(finalContent, simulationConfig);
          }
          
          // Vérification résultat
          if (humanSimulationResult && !humanSimulationResult.fallback) {
            finalContent = humanSimulationResult.content;
            humanSimulationStats = humanSimulationResult.stats;
            
            logSh(`   ✅ Human Simulation: ${humanSimulationStats.totalModifications || 0} modifications`, 'INFO');
            logSh(`   🎯 Score qualité: ${humanSimulationResult.qualityScore?.toFixed(2) || 'N/A'}`, 'INFO');
            
            // 🆕 SAUVEGARDE ÉTAPE 4: Human Simulation
            if (saveIntermediateSteps) {
              logSh(`💾 SAUVEGARDE v1.3: Human Simulation`, 'INFO');
              
              const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
              const humanAssembledContent = await injectGeneratedContent(xmlString, finalContent, finalElements);
              
              const humanStorage = await saveGeneratedArticleOrganic({ generatedTexts: finalContent }, csvData, {
                version: 'v1.3',
                stage: 'human_simulation',
                source: `${source}_human_${humanSimulationMode}`,
                stageDescription: `Simulation humaine (${humanSimulationMode}) - ${humanSimulationStats.totalModifications || 0} modifications`,
                parentArticleId: parentArticleId,
                useVersionedSheet: true  // 🆕 Utiliser Generated_Articles_Versioned
              });
              
              versionHistory.push({
                version: 'v1.3',
                stage: 'human_simulation',
                articleId: humanStorage.articleId,
                length: humanStorage.textLength,
                wordCount: humanStorage.wordCount,
                modifications: humanSimulationStats.totalModifications || 0,
                qualityScore: humanSimulationResult.qualityScore
              });
              
              logSh(`   ✅ Sauvé v1.3 - ID: ${humanStorage.articleId}`, 'DEBUG');
            }
          } else {
            logSh(`   ⚠️ Human Simulation fallback: contenu précédent préservé`, 'WARNING');
          }
          
        } catch (humanSimulationError) {
          logSh(`   ❌ Erreur Human Simulation: ${humanSimulationError.message}`, 'ERROR');
          logSh(`   🔄 Fallback: contenu adversarial préservé`, 'INFO');
        }
      }

      // ========================================
      // PHASE 8B: PATTERN BREAKING (NIVEAU 2)
      // ========================================
      let patternBreakingStats = null;
      
      if (patternBreakingMode !== 'none') {
        logSh(`🔧 PHASE 8B: Pattern Breaking (${patternBreakingMode})`, 'INFO');
        
        let patternBreakingResult;
        
        try {
          // Configuration Pattern Breaking
          const patternConfig = {
            csvData,
            source: `pattern_breaking_${patternBreakingMode}`,
            personality: csvData.personality
          };
          
          // Application selon mode
          switch (patternBreakingMode) {
            case 'adaptivePatternBreaking':
              // Recommandation automatique si adaptive
              const patternContext = {
                contentLength: Object.values(finalContent).join('').length,
                critical: false,
                preserveQuality: true
              };
              const recommendedPattern = recommendPatternBreakingStack(Object.values(finalContent).join(' '), patternContext);
              logSh(`   🤖 Recommandation Pattern Breaking: ${recommendedPattern.recommendedStack}`, 'DEBUG');
              
              patternBreakingResult = await applyPatternBreakingStack(recommendedPattern.recommendedStack, finalContent, patternConfig);
              break;
              
            case 'lightPatternBreaking':
            case 'standardPatternBreaking': 
            case 'heavyPatternBreaking':
            case 'syntaxFocus':
            case 'connectorsFocus':
              // Stack prédéfini
              patternBreakingResult = await applyPatternBreakingStack(patternBreakingMode, finalContent, patternConfig);
              break;
              
            default:
              // Mode custom ou direct
              patternBreakingResult = await applyPatternBreakingLayer(finalContent, patternConfig);
          }
          
          // Vérification résultat
          if (patternBreakingResult && !patternBreakingResult.fallback) {
            finalContent = patternBreakingResult.content;
            patternBreakingStats = patternBreakingResult.stats;
            
            logSh(`   ✅ Pattern Breaking: ${patternBreakingStats.totalModifications || 0} modifications`, 'INFO');
            logSh(`   🎯 Patterns détectés: ${patternBreakingStats.patternsDetected || 0}`, 'INFO');
            
            // 🆕 SAUVEGARDE ÉTAPE 5: Pattern Breaking
            if (saveIntermediateSteps) {
              logSh(`💾 SAUVEGARDE v1.4: Pattern Breaking`, 'INFO');
              
              const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
              const patternAssembledContent = await injectGeneratedContent(xmlString, finalContent, finalElements);
              
              const patternStorage = await saveGeneratedArticleOrganic({ generatedTexts: finalContent }, csvData, {
                version: 'v1.4',
                stage: 'pattern_breaking',
                source: `${source}_pattern_${patternBreakingMode}`,
                stageDescription: `Pattern Breaking (${patternBreakingMode}) - ${patternBreakingStats.totalModifications || 0} modifications`,
                parentArticleId: parentArticleId,
                useVersionedSheet: true  // 🆕 Utiliser Generated_Articles_Versioned
              });
              
              versionHistory.push({
                version: 'v1.4',
                stage: 'pattern_breaking',
                articleId: patternStorage.articleId,
                length: patternStorage.textLength,
                wordCount: patternStorage.wordCount,
                modifications: patternBreakingStats.totalModifications || 0,
                patternsDetected: patternBreakingStats.patternsDetected || 0
              });
              
              logSh(`   ✅ Sauvé v1.4 - ID: ${patternStorage.articleId}`, 'DEBUG');
            }
          } else {
            logSh(`   ⚠️ Pattern Breaking fallback: contenu précédent préservé`, 'WARNING');
          }
          
        } catch (patternBreakingError) {
          logSh(`   ❌ Erreur Pattern Breaking: ${patternBreakingError.message}`, 'ERROR');
          logSh(`   🔄 Fallback: contenu précédent préservé`, 'INFO');
        }
      }

      // ========================================
      // PHASE 9: ASSEMBLAGE ET STOCKAGE FINAL
      // ========================================
      logSh(`🔗 PHASE 9: Assemblage et stockage final`, 'INFO');
      
      // D'abord récupérer le XML décodé et les finalElements
      const xmlString = csvData.xmlTemplate.startsWith('<?xml') ? csvData.xmlTemplate : Buffer.from(csvData.xmlTemplate, 'base64').toString('utf8');
      const assembledContent = await injectGeneratedContent(xmlString, finalContent, finalElements);
      
      // 🆕 SAUVEGARDE VERSION FINALE
      const finalSourceTag = `${source}_${selectiveStack}${adversarialMode !== 'none' ? `_${adversarialMode}` : ''}${humanSimulationMode !== 'none' ? `_${humanSimulationMode}` : ''}${patternBreakingMode !== 'none' ? `_${patternBreakingMode}` : ''}`;
      
      const storageResult = await saveGeneratedArticleOrganic({ generatedTexts: finalContent }, csvData, {
        version: saveIntermediateSteps ? 'v2.0' : '1.0',
        stage: 'final_version',
        source: finalSourceTag,
        stageDescription: `Version finale complète avec toutes améliorations`,
        parentArticleId: parentArticleId,
        versionHistory: saveIntermediateSteps ? versionHistory : undefined,
        useVersionedSheet: false  // 🆕 Version finale → Generated_Articles (comme avant)
      });
      
      // Ajouter la version finale à l'historique
      if (saveIntermediateSteps) {
        versionHistory.push({
          version: 'v2.0',
          stage: 'final_version',
          articleId: storageResult.articleId,
          length: storageResult.textLength,
          wordCount: storageResult.wordCount
        });
        
        logSh(`💾 SAUVEGARDE v2.0: Version finale`, 'INFO');
        logSh(`   📋 Historique complet: ${versionHistory.length} versions`, 'INFO');
      }
      
      logSh(`   ✅ Stocké: ${storageResult.textLength} caractères`, 'DEBUG');

      // ========================================
      // RÉSUMÉ FINAL
      // ========================================
      const totalDuration = Date.now() - startTime;
      const finalStats = {
        rowNumber,
        selectiveStack,
        adversarialMode,
        humanSimulationMode,
        patternBreakingMode,
        totalDuration,
        elementsGenerated: Object.keys(generatedContent).length,
        selectiveEnhancements: selectiveResult.stats.elementsEnhanced || selectiveResult.stats.totalModifications || 0,
        adversarialModifications: adversarialStats?.elementsModified || adversarialStats?.totalModifications || 0,
        humanSimulationModifications: humanSimulationStats?.totalModifications || 0,
        patternBreakingModifications: patternBreakingStats?.totalModifications || 0,
        finalLength: storageResult.textLength,
        personality: selectedPersonality.nom,
        source,
        versionHistory: saveIntermediateSteps ? versionHistory : undefined,
        parentArticleId: parentArticleId
      };

      logSh(`✅ WORKFLOW MODULAIRE TERMINÉ (${totalDuration}ms)`, 'INFO');
      logSh(`   📊 ${finalStats.elementsGenerated} générés | ${finalStats.selectiveEnhancements} selective | ${finalStats.adversarialModifications} adversarial | ${finalStats.humanSimulationModifications} humain | ${finalStats.patternBreakingModifications} pattern`, 'INFO');
      logSh(`   🎭 Personnalité: ${finalStats.personality} | Taille finale: ${finalStats.finalLength} chars`, 'INFO');

      await tracer.event('Workflow modulaire terminé', finalStats);

      return {
        success: true,
        stats: finalStats,
        content: finalContent,
        assembledContent,
        storageResult,
        selectiveResult,
        adversarialResult: adversarialStats ? { stats: adversarialStats } : null,
        humanSimulationResult: humanSimulationStats ? { stats: humanSimulationStats } : null,
        patternBreakingResult: patternBreakingStats ? { stats: patternBreakingStats } : null
      };

    } catch (error) {
      const duration = Date.now() - startTime;
      logSh(`❌ WORKFLOW MODULAIRE ÉCHOUÉ après ${duration}ms: ${error.message}`, 'ERROR');
      logSh(`Stack trace: ${error.stack}`, 'ERROR');
      
      await tracer.event('Workflow modulaire échoué', { 
        error: error.message, 
        duration, 
        rowNumber, 
        selectiveStack, 
        adversarialMode,
        humanSimulationMode,
        patternBreakingMode 
      });
      
      throw error;
    }
  }, { config });
}

/**
 * BENCHMARK COMPARATIF STACKS
 */
async function benchmarkStacks(rowNumber = 2) {
  console.log('\n⚡ === BENCHMARK STACKS MODULAIRES ===\n');
  
  const stacks = getAvailableStacks();
  const adversarialModes = ['none', 'light', 'standard'];
  const humanSimulationModes = ['none', 'lightSimulation', 'standardSimulation'];
  const patternBreakingModes = ['none', 'lightPatternBreaking', 'standardPatternBreaking'];
  
  const results = [];
  
  for (const stack of stacks.slice(0, 2)) { // Tester 2 stacks principaux
    for (const advMode of adversarialModes.slice(0, 2)) { // 2 modes adversarial  
      for (const humanMode of humanSimulationModes.slice(0, 2)) { // 2 modes human simulation
      for (const patternMode of patternBreakingModes.slice(0, 2)) { // 2 modes pattern breaking
        
        console.log(`🧪 Test: ${stack.name} + adversarial ${advMode} + human ${humanMode} + pattern ${patternMode}`);
        
        try {
          const startTime = Date.now();
          
          const result = await handleModularWorkflow({
            rowNumber,
            selectiveStack: stack.name,
            adversarialMode: advMode,
            humanSimulationMode: humanMode,
            patternBreakingMode: patternMode,
            source: 'benchmark'
          });
        
        const duration = Date.now() - startTime;
        
          results.push({
            stack: stack.name,
            adversarial: advMode,
            humanSimulation: humanMode,
            patternBreaking: patternMode,
            duration,
            success: true,
            selectiveEnhancements: result.stats.selectiveEnhancements,
            adversarialModifications: result.stats.adversarialModifications,
            humanSimulationModifications: result.stats.humanSimulationModifications,
            patternBreakingModifications: result.stats.patternBreakingModifications,
            finalLength: result.stats.finalLength
          });
          
          console.log(`   ✅ ${duration}ms | ${result.stats.selectiveEnhancements} selective | ${result.stats.adversarialModifications} adversarial | ${result.stats.humanSimulationModifications} humain | ${result.stats.patternBreakingModifications} pattern`);
        
        } catch (error) {
          results.push({
            stack: stack.name,
            adversarial: advMode,
            humanSimulation: humanMode,
            patternBreaking: patternMode,
            success: false,
            error: error.message
          });
          
          console.log(`   ❌ Échoué: ${error.message}`);
        }
      }
      }
    }
  }
  
  // Résumé benchmark
  console.log('\n📊 RÉSUMÉ BENCHMARK:');
  
  const successful = results.filter(r => r.success);
  if (successful.length > 0) {
    const avgDuration = successful.reduce((sum, r) => sum + r.duration, 0) / successful.length;
    const bestPerf = successful.reduce((best, r) => r.duration < best.duration ? r : best);
    const mostEnhancements = successful.reduce((best, r) => {
      const rTotal = r.selectiveEnhancements + r.adversarialModifications + (r.humanSimulationModifications || 0) + (r.patternBreakingModifications || 0);
      const bestTotal = best.selectiveEnhancements + best.adversarialModifications + (best.humanSimulationModifications || 0) + (best.patternBreakingModifications || 0);
      return rTotal > bestTotal ? r : best;
    });
    
    console.log(`   ⚡ Durée moyenne: ${avgDuration.toFixed(0)}ms`);
    console.log(`   🏆 Meilleure perf: ${bestPerf.stack} + ${bestPerf.adversarial} + ${bestPerf.humanSimulation} + ${bestPerf.patternBreaking} (${bestPerf.duration}ms)`);
    console.log(`   🔥 Plus d'améliorations: ${mostEnhancements.stack} + ${mostEnhancements.adversarial} + ${mostEnhancements.humanSimulation} + ${mostEnhancements.patternBreaking} (${mostEnhancements.selectiveEnhancements + mostEnhancements.adversarialModifications + (mostEnhancements.humanSimulationModifications || 0) + (mostEnhancements.patternBreakingModifications || 0)})`);
  }
  
  return results;
}

/**
 * INTERFACE LIGNE DE COMMANDE
 */
async function main() {
  const args = process.argv.slice(2);
  const command = args[0] || 'workflow';
  
  try {
    switch (command) {
      case 'workflow':
        const rowNumber = parseInt(args[1]) || 2;
        const selectiveStack = args[2] || 'standardEnhancement';
        const adversarialMode = args[3] || 'light';
        const humanSimulationMode = args[4] || 'none';
        const patternBreakingMode = args[5] || 'none';
        
        console.log(`\n🚀 Exécution workflow modulaire:`);
        console.log(`   📊 Ligne: ${rowNumber}`);
        console.log(`   🔧 Stack selective: ${selectiveStack}`);
        console.log(`   🎯 Mode adversarial: ${adversarialMode}`);
        console.log(`   🧠 Mode human simulation: ${humanSimulationMode}`);
        console.log(`   🔧 Mode pattern breaking: ${patternBreakingMode}`);
        
        const result = await handleModularWorkflow({
          rowNumber,
          selectiveStack,
          adversarialMode,
          humanSimulationMode,
          patternBreakingMode,
          source: 'cli'
        });
        
        console.log('\n✅ WORKFLOW MODULAIRE RÉUSSI');
        console.log(`📈 Stats: ${JSON.stringify(result.stats, null, 2)}`);
        break;
        
      case 'benchmark':
        const benchRowNumber = parseInt(args[1]) || 2;
        
        console.log(`\n⚡ Benchmark stacks (ligne ${benchRowNumber})`);
        const benchResults = await benchmarkStacks(benchRowNumber);
        
        console.log('\n📊 Résultats complets:');
        console.table(benchResults);
        break;
        
      case 'stacks':
        console.log('\n📦 STACKS SELECTIVE DISPONIBLES:');
        const availableStacks = getAvailableStacks();
        availableStacks.forEach(stack => {
          console.log(`\n   🔧 ${stack.name}:`);
          console.log(`      📝 ${stack.description}`);
          console.log(`      📊 ${stack.layersCount} couches`);
          console.log(`      🎯 Couches: ${stack.layers ? stack.layers.map(l => `${l.type}(${l.llm})`).join(' → ') : 'N/A'}`);
        });
        
        console.log('\n🎯 MODES ADVERSARIAL DISPONIBLES:');
        console.log('   - none: Pas d\'adversarial');
        console.log('   - light: Défense légère');
        console.log('   - standard: Défense standard');
        console.log('   - heavy: Défense intensive');
        console.log('   - adaptive: Adaptatif intelligent');
        
        console.log('\n🧠 MODES HUMAN SIMULATION DISPONIBLES:');
        const humanStacks = getAvailableSimulationStacks();
        humanStacks.forEach(stack => {
          console.log(`\n   🎭 ${stack.name}:`);
          console.log(`      📝 ${stack.description}`);
          console.log(`      📊 ${stack.layersCount} couches`);
          console.log(`      ⚡ ${stack.expectedImpact.modificationsPerElement} modifs | ${stack.expectedImpact.detectionReduction} anti-détection`);
        });
        break;
        
      case 'help':
      default:
        console.log('\n🔧 === MAIN MODULAIRE - USAGE ===');
        console.log('\nCommandes disponibles:');
        console.log('  workflow [ligne] [stack] [adversarial] [human]  - Exécuter workflow complet');
        console.log('  benchmark [ligne]                                - Benchmark stacks');
        console.log('  stacks                                           - Lister stacks disponibles');
        console.log('  help                                             - Afficher cette aide');
        console.log('\nExemples:');
        console.log('  node main_modulaire.js workflow 2 standardEnhancement light standardSimulation');
        console.log('  node main_modulaire.js workflow 3 adaptive standard heavySimulation');
        console.log('  node main_modulaire.js workflow 2 fullEnhancement none personalityFocus');
        console.log('  node main_modulaire.js benchmark 2');
        console.log('  node main_modulaire.js stacks');
        break;
    }
    
  } catch (error) {
    console.error('\n❌ ERREUR MAIN MODULAIRE:', error.message);
    console.error(error.stack);
    process.exit(1);
  }
}

// Export pour usage programmatique
module.exports = {
  handleModularWorkflow,
  benchmarkStacks
};

// Exécution CLI si appelé directement
if (require.main === module) {
  main().catch(error => {
    console.error('❌ ERREUR FATALE:', error.message);
    process.exit(1);
  });
}