// ========================================
// FICHIER: HumanSimulationUtils.js
// RESPONSABILITÉ: Utilitaires partagés Human Simulation
// Fonctions d'analyse, validation et helpers
// ========================================

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

/**
 * SEUILS DE QUALITÉ
 */
const QUALITY_THRESHOLDS = {
  readability: {
    minimum: 0.3,    // FIXÉ: Plus permissif (était 0.6)
    good: 0.6,
    excellent: 0.8
  },
  keywordPreservation: {
    minimum: 0.7,    // FIXÉ: Plus permissif (était 0.8)
    good: 0.9,
    excellent: 0.95
  },
  similarity: {
    minimum: 0.5,    // FIXÉ: Plus permissif (était 0.7)
    maximum: 1.0     // FIXÉ: Accepter même contenu identique (était 0.95)
  }
};

/**
 * MOTS-CLÉS À PRÉSERVER ABSOLUMENT
 */
const CRITICAL_KEYWORDS = [
  // Mots-clés SEO génériques
  'plaque', 'personnalisée', 'gravure', 'métal', 'bois', 'acrylique',
  'design', 'qualité', 'fabrication', 'artisanal', 'sur-mesure',
  // Termes techniques importants
  'laser', 'CNC', 'impression', 'découpe', 'finition', 'traitement',
  // Termes commerciaux
  'prix', 'tarif', 'devis', 'livraison', 'garantie', 'service'
];

/**
 * ANALYSE COMPLEXITÉ CONTENU
 * @param {object} content - Contenu à analyser
 * @returns {object} - Métriques de complexité
 */
function analyzeContentComplexity(content) {
  logSh('🔍 Analyse complexité contenu', 'DEBUG');

  const contentArray = Object.values(content).filter(c => typeof c === 'string');
  const totalText = contentArray.join(' ');
  
  // Métriques de base
  const totalWords = totalText.split(/\s+/).length;
  const totalSentences = totalText.split(/[.!?]+/).length;
  const totalParagraphs = contentArray.length;
  
  // Complexité lexicale
  const uniqueWords = new Set(totalText.toLowerCase().split(/\s+/)).size;
  const lexicalDiversity = uniqueWords / totalWords;
  
  // Longueur moyenne des phrases
  const avgSentenceLength = totalWords / totalSentences;
  
  // Complexité syntaxique (approximative)
  const complexConnectors = (totalText.match(/néanmoins|cependant|par conséquent|en outre|toutefois/gi) || []).length;
  const syntacticComplexity = complexConnectors / totalSentences;
  
  // Score global de complexité
  const complexityScore = (
    (lexicalDiversity * 0.4) +
    (Math.min(avgSentenceLength / 100, 1) * 0.3) +
    (syntacticComplexity * 0.3)
  );

  const complexity = {
    totalWords,
    totalSentences,
    totalParagraphs,
    avgSentenceLength,
    lexicalDiversity,
    syntacticComplexity,
    complexityScore,
    level: complexityScore > 0.7 ? 'high' : complexityScore > 0.4 ? 'medium' : 'low'
  };

  logSh(`   📊 Complexité: ${complexity.level} (score: ${complexityScore.toFixed(2)})`, 'DEBUG');
  logSh(`   📝 ${totalWords} mots, ${totalSentences} phrases, diversité: ${lexicalDiversity.toFixed(2)}`, 'DEBUG');

  return complexity;
}

/**
 * CALCUL SCORE LISIBILITÉ
 * Approximation de l'index Flesch-Kincaid adapté au français
 * @param {string} text - Texte à analyser
 * @returns {number} - Score lisibilité (0-1)
 */
function calculateReadabilityScore(text) {
  if (!text || text.trim().length === 0) {
    return 0;
  }

  // Nettoyage du texte
  const cleanText = text.replace(/[^\w\s.!?]/gi, '');
  
  // Comptages de base
  const sentences = cleanText.split(/[.!?]+/).filter(s => s.trim().length > 0);
  const words = cleanText.split(/\s+/).filter(w => w.length > 0);
  const syllables = countSyllables(cleanText);

  if (sentences.length === 0 || words.length === 0) {
    return 0;
  }

  // Métriques Flesch-Kincaid adaptées français
  const avgWordsPerSentence = words.length / sentences.length;
  const avgSyllablesPerWord = syllables / words.length;
  
  // Formule adaptée (plus clémente que l'originale)
  const fleschScore = 206.835 - (1.015 * avgWordsPerSentence) - (84.6 * avgSyllablesPerWord);
  
  // Normalisation 0-1 (100 = parfait en Flesch)
  const normalizedScore = Math.max(0, Math.min(1, fleschScore / 100));
  
  logSh(`   📖 Lisibilité: ${normalizedScore.toFixed(2)} (mots/phrase: ${avgWordsPerSentence.toFixed(1)}, syll/mot: ${avgSyllablesPerWord.toFixed(1)})`, 'DEBUG');

  return normalizedScore;
}

/**
 * COMPTAGE SYLLABES (APPROXIMATIF FRANÇAIS)
 */
function countSyllables(text) {
  // Approximation pour le français
  const vowels = /[aeiouyàáâäèéêëìíîïòóôöùúûü]/gi;
  const vowelGroups = text.match(vowels) || [];
  
  // Approximation: 1 groupe de voyelles ≈ 1 syllabe
  // Ajustements pour le français
  let syllables = vowelGroups.length;
  
  // Corrections courantes
  const corrections = [
    { pattern: /ion/gi, adjustment: 0 },      // "tion" = 1 syllabe, pas 2
    { pattern: /ieu/gi, adjustment: -1 },     // "ieux" = 1 syllabe
    { pattern: /eau/gi, adjustment: -1 },     // "eau" = 1 syllabe
    { pattern: /ai/gi, adjustment: -1 },      // "ai" = 1 syllabe
    { pattern: /ou/gi, adjustment: -1 },      // "ou" = 1 syllabe
    { pattern: /e$/gi, adjustment: -0.5 }     // "e" final muet
  ];

  corrections.forEach(correction => {
    const matches = text.match(correction.pattern) || [];
    syllables += matches.length * correction.adjustment;
  });

  return Math.max(1, Math.round(syllables));
}

/**
 * PRÉSERVATION MOTS-CLÉS
 * @param {string} originalText - Texte original
 * @param {string} modifiedText - Texte modifié
 * @returns {number} - Score préservation (0-1)
 */
function preserveKeywords(originalText, modifiedText) {
  if (!originalText || !modifiedText) {
    return 0;
  }

  const originalLower = originalText.toLowerCase();
  const modifiedLower = modifiedText.toLowerCase();

  // Extraire mots-clés du texte original
  const originalKeywords = extractKeywords(originalLower);
  
  // Vérifier préservation
  let preservedCount = 0;
  let criticalPreservedCount = 0;
  let criticalTotalCount = 0;

  originalKeywords.forEach(keyword => {
    const isCritical = CRITICAL_KEYWORDS.some(ck => 
      keyword.toLowerCase().includes(ck.toLowerCase()) || 
      ck.toLowerCase().includes(keyword.toLowerCase())
    );
    
    if (isCritical) {
      criticalTotalCount++;
    }

    // Vérifier présence dans texte modifié
    const keywordRegex = new RegExp(`\\b${keyword}\\b`, 'gi');
    if (modifiedLower.match(keywordRegex)) {
      preservedCount++;
      if (isCritical) {
        criticalPreservedCount++;
      }
    }
  });

  // Score avec bonus pour mots-clés critiques
  const basicPreservation = preservedCount / Math.max(1, originalKeywords.length);
  const criticalPreservation = criticalTotalCount > 0 ? 
    criticalPreservedCount / criticalTotalCount : 1.0;

  const finalScore = (basicPreservation * 0.6) + (criticalPreservation * 0.4);

  logSh(`   🔑 Mots-clés: ${preservedCount}/${originalKeywords.length} préservés (${criticalPreservedCount}/${criticalTotalCount} critiques)`, 'DEBUG');
  logSh(`   🎯 Score préservation: ${finalScore.toFixed(2)}`, 'DEBUG');

  return finalScore;
}

/**
 * EXTRACTION MOTS-CLÉS SIMPLES
 */
function extractKeywords(text) {
  // Mots de plus de 3 caractères, non vides
  const words = text.match(/\b\w{4,}\b/g) || [];
  
  // Filtrer mots courants français
  const stopWords = [
    'avec', 'dans', 'pour', 'cette', 'sont', 'tout', 'mais', 'plus', 'très',
    'bien', 'encore', 'aussi', 'comme', 'après', 'avant', 'entre', 'depuis'
  ];

  const keywords = words
    .filter(word => !stopWords.includes(word.toLowerCase()))
    .filter((word, index, array) => array.indexOf(word) === index) // Unique
    .slice(0, 20); // Limiter à 20 mots-clés

  return keywords;
}

/**
 * VALIDATION QUALITÉ SIMULATION
 * @param {string} originalContent - Contenu original
 * @param {string} simulatedContent - Contenu simulé
 * @param {number} qualityThreshold - Seuil qualité minimum
 * @returns {object} - Résultat validation
 */
function validateSimulationQuality(originalContent, simulatedContent, qualityThreshold = 0.7) {
  if (!originalContent || !simulatedContent) {
    return { acceptable: false, reason: 'Contenu manquant' };
  }

  logSh('🎯 Validation qualité simulation', 'DEBUG');

  // Métriques de qualité
  const readabilityScore = calculateReadabilityScore(simulatedContent);
  const keywordScore = preserveKeywords(originalContent, simulatedContent);
  const similarityScore = calculateSimilarity(originalContent, simulatedContent);

  // Score global pondéré
  const globalScore = (
    readabilityScore * 0.4 +
    keywordScore * 0.4 +
    (similarityScore > QUALITY_THRESHOLDS.similarity.minimum && 
     similarityScore < QUALITY_THRESHOLDS.similarity.maximum ? 0.2 : 0)
  );

  const acceptable = globalScore >= qualityThreshold;
  
  const validation = {
    acceptable,
    globalScore,
    readabilityScore,
    keywordScore,
    similarityScore,
    reason: acceptable ? 'Qualité acceptable' : determineQualityIssue(readabilityScore, keywordScore, similarityScore),
    details: {
      readabilityOk: readabilityScore >= QUALITY_THRESHOLDS.readability.minimum,
      keywordsOk: keywordScore >= QUALITY_THRESHOLDS.keywordPreservation.minimum,
      similarityOk: similarityScore >= QUALITY_THRESHOLDS.similarity.minimum && 
                    similarityScore <= QUALITY_THRESHOLDS.similarity.maximum
    }
  };

  logSh(`   🎯 Validation: ${acceptable ? 'ACCEPTÉ' : 'REJETÉ'} (score: ${globalScore.toFixed(2)})`, acceptable ? 'INFO' : 'WARNING');
  logSh(`   📊 Lisibilité: ${readabilityScore.toFixed(2)} | Mots-clés: ${keywordScore.toFixed(2)} | Similarité: ${similarityScore.toFixed(2)}`, 'DEBUG');

  return validation;
}

/**
 * CALCUL SIMILARITÉ APPROXIMATIVE
 */
function calculateSimilarity(text1, text2) {
  // Similarité basée sur les mots partagés (simple mais efficace)
  const words1 = new Set(text1.toLowerCase().split(/\s+/));
  const words2 = new Set(text2.toLowerCase().split(/\s+/));
  
  const intersection = new Set([...words1].filter(word => words2.has(word)));
  const union = new Set([...words1, ...words2]);
  
  return intersection.size / union.size;
}

/**
 * DÉTERMINER PROBLÈME QUALITÉ
 */
function determineQualityIssue(readabilityScore, keywordScore, similarityScore) {
  if (readabilityScore < QUALITY_THRESHOLDS.readability.minimum) {
    return 'Lisibilité insuffisante';
  }
  if (keywordScore < QUALITY_THRESHOLDS.keywordPreservation.minimum) {
    return 'Mots-clés mal préservés';
  }
  if (similarityScore < QUALITY_THRESHOLDS.similarity.minimum) {
    return 'Trop différent de l\'original';
  }
  if (similarityScore > QUALITY_THRESHOLDS.similarity.maximum) {
    return 'Pas assez modifié';
  }
  return 'Score global insuffisant';
}

/**
 * GÉNÉRATION RAPPORT QUALITÉ DÉTAILLÉ
 * @param {object} content - Contenu à analyser
 * @param {object} simulationStats - Stats simulation
 * @returns {object} - Rapport détaillé
 */
function generateQualityReport(content, simulationStats) {
  const report = {
    timestamp: new Date().toISOString(),
    contentAnalysis: analyzeContentComplexity(content),
    simulationStats,
    qualityMetrics: {},
    recommendations: []
  };

  // Analyse par élément
  Object.entries(content).forEach(([key, elementContent]) => {
    if (typeof elementContent === 'string') {
      const readability = calculateReadabilityScore(elementContent);
      const complexity = analyzeContentComplexity({ [key]: elementContent });
      
      report.qualityMetrics[key] = {
        readability,
        complexity: complexity.complexityScore,
        wordCount: elementContent.split(/\s+/).length
      };
    }
  });

  // Recommandations automatiques
  if (report.contentAnalysis.complexityScore > 0.8) {
    report.recommendations.push('Simplifier le vocabulaire pour améliorer la lisibilité');
  }
  
  if (simulationStats.fatigueModifications < 1) {
    report.recommendations.push('Augmenter l\'intensité de simulation fatigue');
  }

  return report;
}

/**
 * HELPERS STATISTIQUES
 */
function calculateStatistics(values) {
  const sorted = values.slice().sort((a, b) => a - b);
  const length = values.length;
  
  return {
    mean: values.reduce((sum, val) => sum + val, 0) / length,
    median: length % 2 === 0 ? 
      (sorted[length / 2 - 1] + sorted[length / 2]) / 2 : 
      sorted[Math.floor(length / 2)],
    min: sorted[0],
    max: sorted[length - 1],
    stdDev: calculateStandardDeviation(values)
  };
}

function calculateStandardDeviation(values) {
  const mean = values.reduce((sum, val) => sum + val, 0) / values.length;
  const squaredDifferences = values.map(val => Math.pow(val - mean, 2));
  const variance = squaredDifferences.reduce((sum, val) => sum + val, 0) / values.length;
  return Math.sqrt(variance);
}

// ============= EXPORTS =============
module.exports = {
  analyzeContentComplexity,
  calculateReadabilityScore,
  preserveKeywords,
  validateSimulationQuality,
  generateQualityReport,
  calculateStatistics,
  calculateStandardDeviation,
  countSyllables,
  extractKeywords,
  calculateSimilarity,
  determineQualityIssue,
  QUALITY_THRESHOLDS,
  CRITICAL_KEYWORDS
};