485 lines
16 KiB
JavaScript
485 lines
16 KiB
JavaScript
// ========================================
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// ORCHESTRATEUR PATTERN BREAKING - NIVEAU 2
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// Responsabilité: Coordonner les 3 techniques anti-détection
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// Objectif: -20% détection IA vs Niveau 1
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// ========================================
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const { logSh } = require('../ErrorReporting');
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const { tracer } = require('../trace');
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// Import des 3 techniques Pattern Breaking
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const { applySentenceVariation } = require('./SentenceVariation');
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const { removeLLMFingerprints } = require('./LLMFingerprintRemoval');
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const { humanizeTransitions } = require('./TransitionHumanization');
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/**
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* MAIN ENTRY POINT - PATTERN BREAKING COMPLET
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* @param {Object} input - { content: {}, csvData: {}, options: {} }
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* @returns {Object} - { content: {}, stats: {}, debug: {} }
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*/
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async function applyPatternBreaking(input) {
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return await tracer.run('PatternBreaking.applyPatternBreaking()', async () => {
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const { content, csvData, options = {} } = input;
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const config = {
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// Configuration globale
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intensity = 0.6, // Intensité générale (60%)
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// Contrôle par technique
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sentenceVariation: true, // Activer variation phrases
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fingerprintRemoval: true, // Activer suppression empreintes
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transitionHumanization: true, // Activer humanisation transitions
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// Configuration spécifique par technique
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sentenceVariationConfig: {
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intensity: 0.3,
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splitThreshold: 100,
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mergeThreshold: 30,
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preserveQuestions: true,
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preserveTitles: true
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},
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fingerprintRemovalConfig: {
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intensity: 1.0,
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preserveKeywords: true,
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contextualMode: true,
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csvData
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},
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transitionHumanizationConfig: {
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intensity: 0.6,
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personalityStyle: csvData?.personality?.style,
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avoidRepetition: true,
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preserveFormal: false,
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csvData
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},
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// Options avancées
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qualityPreservation: true, // Préserver qualité contenu
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seoIntegrity: true, // Maintenir intégrité SEO
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readabilityCheck: true, // Vérifier lisibilité
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...options // Override avec options fournies
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};
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await tracer.annotate({
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level: 2,
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technique: 'pattern_breaking',
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elementsCount: Object.keys(content).length,
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personality: csvData?.personality?.nom,
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config: {
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sentenceVariation: config.sentenceVariation,
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fingerprintRemoval: config.fingerprintRemoval,
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transitionHumanization: config.transitionHumanization,
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intensity: config.intensity
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}
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});
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const startTime = Date.now();
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logSh(`🎯 NIVEAU 2: PATTERN BREAKING (3 techniques)`, 'INFO');
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logSh(` 🎭 Personnalité: ${csvData?.personality?.nom} (${csvData?.personality?.style})`, 'INFO');
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logSh(` 📊 ${Object.keys(content).length} éléments à traiter`, 'INFO');
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logSh(` ⚙️ Techniques actives: ${[config.sentenceVariation && 'Variation', config.fingerprintRemoval && 'Empreintes', config.transitionHumanization && 'Transitions'].filter(Boolean).join(' + ')}`, 'INFO');
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try {
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let currentContent = { ...content };
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const pipelineStats = {
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techniques: [],
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totalDuration: 0,
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qualityMetrics: {}
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};
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// Analyse initiale de qualité
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if (config.qualityPreservation) {
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pipelineStats.qualityMetrics.initial = analyzeContentQuality(currentContent);
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}
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// TECHNIQUE 1: VARIATION LONGUEUR PHRASES
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if (config.sentenceVariation) {
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const step1Result = await applySentenceVariation({
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content: currentContent,
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config: config.sentenceVariationConfig,
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context: { step: 1, totalSteps: 3 }
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});
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currentContent = step1Result.content;
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pipelineStats.techniques.push({
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name: 'SentenceVariation',
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...step1Result.stats,
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qualityImpact: calculateQualityImpact(content, step1Result.content)
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});
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logSh(` ✅ 1/3: Variation phrases - ${step1Result.stats.modified}/${step1Result.stats.processed} éléments`, 'INFO');
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}
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// TECHNIQUE 2: SUPPRESSION EMPREINTES LLM
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if (config.fingerprintRemoval) {
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const step2Result = await removeLLMFingerprints({
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content: currentContent,
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config: config.fingerprintRemovalConfig,
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context: { step: 2, totalSteps: 3 }
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});
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currentContent = step2Result.content;
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pipelineStats.techniques.push({
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name: 'FingerprintRemoval',
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...step2Result.stats,
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qualityImpact: calculateQualityImpact(content, step2Result.content)
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});
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logSh(` ✅ 2/3: Suppression empreintes - ${step2Result.stats.totalReplacements} remplacements`, 'INFO');
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}
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// TECHNIQUE 3: HUMANISATION TRANSITIONS
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if (config.transitionHumanization) {
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const step3Result = await humanizeTransitions({
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content: currentContent,
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config: config.transitionHumanizationConfig,
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context: { step: 3, totalSteps: 3 }
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});
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currentContent = step3Result.content;
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pipelineStats.techniques.push({
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name: 'TransitionHumanization',
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...step3Result.stats,
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qualityImpact: calculateQualityImpact(content, step3Result.content)
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});
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logSh(` ✅ 3/3: Humanisation transitions - ${step3Result.stats.totalReplacements} améliorations`, 'INFO');
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}
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// POST-PROCESSING: Vérifications qualité
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if (config.qualityPreservation || config.readabilityCheck) {
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const qualityCheck = performQualityChecks(content, currentContent, config);
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pipelineStats.qualityMetrics.final = qualityCheck;
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// Rollback si qualité trop dégradée
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if (qualityCheck.shouldRollback) {
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logSh(`⚠️ ROLLBACK: Qualité dégradée, retour contenu original`, 'WARNING');
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currentContent = content;
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pipelineStats.rollback = true;
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}
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}
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// RÉSULTATS FINAUX
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const totalDuration = Date.now() - startTime;
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pipelineStats.totalDuration = totalDuration;
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const totalModifications = pipelineStats.techniques.reduce((sum, tech) => {
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return sum + (tech.modified || tech.totalReplacements || 0);
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}, 0);
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const stats = {
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level: 2,
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technique: 'pattern_breaking',
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processed: Object.keys(content).length,
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totalModifications,
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techniquesUsed: pipelineStats.techniques.length,
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duration: totalDuration,
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techniques: pipelineStats.techniques,
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qualityPreserved: !pipelineStats.rollback,
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rollback: pipelineStats.rollback || false
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};
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logSh(`🎯 NIVEAU 2 TERMINÉ: ${totalModifications} modifications sur ${stats.processed} éléments (${totalDuration}ms)`, 'INFO');
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// Log détaillé par technique
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pipelineStats.techniques.forEach(tech => {
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const modificationsCount = tech.modified || tech.totalReplacements || 0;
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logSh(` • ${tech.name}: ${modificationsCount} modifications (${tech.duration}ms)`, 'DEBUG');
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});
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await tracer.event('Pattern breaking terminé', stats);
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return {
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content: currentContent,
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stats,
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debug: {
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level: 2,
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technique: 'pattern_breaking',
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config,
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pipeline: pipelineStats,
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qualityMetrics: pipelineStats.qualityMetrics
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}
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};
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} catch (error) {
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const totalDuration = Date.now() - startTime;
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logSh(`❌ NIVEAU 2 ÉCHOUÉ après ${totalDuration}ms: ${error.message}`, 'ERROR');
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// Fallback: retourner contenu original
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logSh(`🔄 Fallback: contenu original conservé`, 'WARNING');
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await tracer.event('Pattern breaking échoué', {
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error: error.message,
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duration: totalDuration,
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fallback: true
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});
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return {
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content,
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stats: {
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level: 2,
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technique: 'pattern_breaking',
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processed: Object.keys(content).length,
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totalModifications: 0,
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duration: totalDuration,
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error: error.message,
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fallback: true
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},
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debug: { error: error.message, fallback: true }
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};
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}
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}, input);
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}
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/**
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* MODE DIAGNOSTIC - Test individuel des techniques
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*/
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async function diagnosticPatternBreaking(content, csvData) {
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logSh(`🔬 DIAGNOSTIC NIVEAU 2: Test individuel des techniques`, 'INFO');
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const diagnostics = {
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techniques: [],
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errors: [],
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performance: {},
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recommendations: []
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};
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const techniques = [
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{ name: 'SentenceVariation', func: applySentenceVariation },
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{ name: 'FingerprintRemoval', func: removeLLMFingerprints },
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{ name: 'TransitionHumanization', func: humanizeTransitions }
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];
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for (const technique of techniques) {
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try {
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const startTime = Date.now();
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const result = await technique.func({
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content,
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config: { csvData },
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context: { diagnostic: true }
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});
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diagnostics.techniques.push({
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name: technique.name,
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success: true,
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duration: Date.now() - startTime,
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stats: result.stats,
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effectivenessScore: calculateEffectivenessScore(result.stats)
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});
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} catch (error) {
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diagnostics.errors.push({
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technique: technique.name,
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error: error.message
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});
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diagnostics.techniques.push({
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name: technique.name,
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success: false,
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error: error.message
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});
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}
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}
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// Générer recommandations
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diagnostics.recommendations = generateRecommendations(diagnostics.techniques);
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const successfulTechniques = diagnostics.techniques.filter(t => t.success);
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diagnostics.performance.totalDuration = diagnostics.techniques.reduce((sum, t) => sum + (t.duration || 0), 0);
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diagnostics.performance.successRate = Math.round((successfulTechniques.length / techniques.length) * 100);
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logSh(`🔬 DIAGNOSTIC TERMINÉ: ${successfulTechniques.length}/${techniques.length} techniques opérationnelles`, 'INFO');
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return diagnostics;
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}
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/**
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* Analyser qualité du contenu
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*/
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function analyzeContentQuality(content) {
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const allText = Object.values(content).join(' ');
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const wordCount = allText.split(/\s+/).length;
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const avgWordsPerElement = wordCount / Object.keys(content).length;
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// Métrique de lisibilité approximative (Flesch simplifié)
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const sentences = allText.split(/[.!?]+/).filter(s => s.trim().length > 5);
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const avgWordsPerSentence = wordCount / Math.max(1, sentences.length);
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const readabilityScore = Math.max(0, 100 - (avgWordsPerSentence * 1.5));
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return {
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wordCount,
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elementCount: Object.keys(content).length,
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avgWordsPerElement: Math.round(avgWordsPerElement),
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avgWordsPerSentence: Math.round(avgWordsPerSentence),
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readabilityScore: Math.round(readabilityScore),
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sentenceCount: sentences.length
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};
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}
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/**
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* Calculer impact qualité entre avant/après
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*/
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function calculateQualityImpact(originalContent, modifiedContent) {
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const originalQuality = analyzeContentQuality(originalContent);
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const modifiedQuality = analyzeContentQuality(modifiedContent);
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const wordCountChange = ((modifiedQuality.wordCount - originalQuality.wordCount) / originalQuality.wordCount) * 100;
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const readabilityChange = modifiedQuality.readabilityScore - originalQuality.readabilityScore;
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return {
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wordCountChange: Math.round(wordCountChange * 100) / 100,
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readabilityChange: Math.round(readabilityChange),
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severe: Math.abs(wordCountChange) > 10 || Math.abs(readabilityChange) > 15
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};
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}
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/**
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* Effectuer vérifications qualité
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*/
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function performQualityChecks(originalContent, modifiedContent, config) {
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const originalQuality = analyzeContentQuality(originalContent);
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const modifiedQuality = analyzeContentQuality(modifiedContent);
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const qualityThresholds = {
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maxWordCountChange: 15, // % max changement nombre mots
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minReadabilityScore: 50, // Score lisibilité minimum
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maxReadabilityDrop: 20 // Baisse max lisibilité
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};
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const issues = [];
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// Vérification nombre de mots
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const wordCountChange = Math.abs(modifiedQuality.wordCount - originalQuality.wordCount) / originalQuality.wordCount * 100;
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if (wordCountChange > qualityThresholds.maxWordCountChange) {
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issues.push({
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type: 'word_count_change',
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severity: 'high',
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change: wordCountChange,
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threshold: qualityThresholds.maxWordCountChange
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});
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}
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// Vérification lisibilité
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if (modifiedQuality.readabilityScore < qualityThresholds.minReadabilityScore) {
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issues.push({
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type: 'low_readability',
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severity: 'medium',
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score: modifiedQuality.readabilityScore,
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threshold: qualityThresholds.minReadabilityScore
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});
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}
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const readabilityDrop = originalQuality.readabilityScore - modifiedQuality.readabilityScore;
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if (readabilityDrop > qualityThresholds.maxReadabilityDrop) {
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issues.push({
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type: 'readability_drop',
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severity: 'high',
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drop: readabilityDrop,
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threshold: qualityThresholds.maxReadabilityDrop
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});
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}
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// Décision rollback
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const highSeverityIssues = issues.filter(issue => issue.severity === 'high');
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const shouldRollback = highSeverityIssues.length > 0 && config.qualityPreservation;
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return {
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originalQuality,
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modifiedQuality,
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issues,
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shouldRollback,
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qualityScore: calculateOverallQualityScore(issues, modifiedQuality)
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};
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}
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/**
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* Calculer score de qualité global
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*/
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function calculateOverallQualityScore(issues, quality) {
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let baseScore = 100;
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issues.forEach(issue => {
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const penalty = issue.severity === 'high' ? 30 : issue.severity === 'medium' ? 15 : 5;
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baseScore -= penalty;
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});
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// Bonus pour bonne lisibilité
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if (quality.readabilityScore > 70) baseScore += 10;
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return Math.max(0, Math.min(100, baseScore));
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}
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/**
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* Calculer score d'efficacité d'une technique
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*/
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function calculateEffectivenessScore(stats) {
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if (!stats) return 0;
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const modificationsCount = stats.modified || stats.totalReplacements || 0;
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const processedCount = stats.processed || 1;
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const modificationRate = (modificationsCount / processedCount) * 100;
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// Score basé sur taux de modification et durée
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const baseScore = Math.min(100, modificationRate * 2); // Max 50% modification = score 100
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const durationPenalty = Math.max(0, (stats.duration - 1000) / 100); // Pénalité si > 1s
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return Math.max(0, Math.round(baseScore - durationPenalty));
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}
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/**
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* Générer recommandations basées sur diagnostic
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*/
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function generateRecommendations(techniqueResults) {
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const recommendations = [];
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techniqueResults.forEach(tech => {
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if (!tech.success) {
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recommendations.push({
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type: 'error',
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technique: tech.name,
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message: `${tech.name} a échoué: ${tech.error}`,
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action: 'Vérifier configuration et dépendances'
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});
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return;
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}
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const effectiveness = tech.effectivenessScore || 0;
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if (effectiveness < 30) {
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recommendations.push({
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type: 'low_effectiveness',
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technique: tech.name,
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message: `${tech.name} peu efficace (score: ${effectiveness})`,
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action: 'Augmenter intensité ou réviser configuration'
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});
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} else if (effectiveness > 80) {
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recommendations.push({
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type: 'high_effectiveness',
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technique: tech.name,
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message: `${tech.name} très efficace (score: ${effectiveness})`,
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action: 'Configuration optimale'
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});
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}
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if (tech.duration > 3000) {
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recommendations.push({
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type: 'performance',
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technique: tech.name,
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message: `${tech.name} lent (${tech.duration}ms)`,
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action: 'Considérer réduction intensité ou optimisation'
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});
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}
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});
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return recommendations;
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}
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module.exports = {
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applyPatternBreaking, // ← MAIN ENTRY POINT
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diagnosticPatternBreaking, // ← Mode diagnostic
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analyzeContentQuality,
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performQualityChecks,
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calculateQualityImpact,
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calculateEffectivenessScore
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}; |