brainy/examples/brainy-service-template/src/augmentations/autoDiscoveryAugmentation.js

import { logger } from '../utils/logger.js'

/**
 * Auto-Discovery Augmentation - Helps users understand their Brainy data automatically\n * Provides intelligent insights about data patterns, relationships, and optimization suggestions\n */\nexport class AutoDiscoveryAugmentation {\n  constructor(options = {}) {\n    this.type = 'COGNITION'\n    this.priority = 4\n    this.options = {\n      analysisInterval: options.analysisInterval || 300000, // 5 minutes\n      minDataPoints: options.minDataPoints || 10,\n      enablePatternDetection: options.enablePatternDetection !== false,\n      enableOptimizationSuggestions: options.enableOptimizationSuggestions !== false,\n      enableDataQualityAnalysis: options.enableDataQualityAnalysis !== false,\n      ...options\n    }\n    \n    this.db = null\n    this.analysisTimer = null\n    this.lastAnalysis = null\n    this.insights = {\n      patterns: [],\n      suggestions: [],\n      dataQuality: {},\n      statistics: {}\n    }\n  }\n\n  async augment(brainyData, context) {\n    this.db = brainyData\n    \n    try {\n      // Run initial analysis\n      await this.runAnalysis()\n      \n      // Schedule periodic analysis\n      if (this.options.analysisInterval > 0) {\n        this.scheduleAnalysis()\n      }\n      \n      logger.info('Auto-Discovery augmentation initialized', {\n        features: {\n          patternDetection: this.options.enablePatternDetection,\n          optimizationSuggestions: this.options.enableOptimizationSuggestions,\n          dataQualityAnalysis: this.options.enableDataQualityAnalysis\n        },\n        analysisInterval: this.options.analysisInterval\n      })\n      \n    } catch (error) {\n      logger.error('Failed to initialize Auto-Discovery augmentation:', error)\n      throw error\n    }\n  }\n\n  async runAnalysis() {\n    try {\n      logger.debug('Running auto-discovery analysis...')\n      \n      const stats = await this.gatherStatistics()\n      \n      // Only run analysis if we have enough data\n      if (stats.totalEntities < this.options.minDataPoints) {\n        logger.debug('Not enough data for meaningful analysis', {\n          entities: stats.totalEntities,\n          required: this.options.minDataPoints\n        })\n        return\n      }\n      \n      this.insights.statistics = stats\n      \n      // Run different types of analysis\n      if (this.options.enablePatternDetection) {\n        this.insights.patterns = await this.detectPatterns(stats)\n      }\n      \n      if (this.options.enableOptimizationSuggestions) {\n        this.insights.suggestions = await this.generateOptimizationSuggestions(stats)\n      }\n      \n      if (this.options.enableDataQualityAnalysis) {\n        this.insights.dataQuality = await this.analyzeDataQuality(stats)\n      }\n      \n      this.lastAnalysis = new Date().toISOString()\n      \n      logger.info('Auto-discovery analysis completed', {\n        patterns: this.insights.patterns.length,\n        suggestions: this.insights.suggestions.length,\n        dataQualityScore: this.insights.dataQuality.overallScore || 'N/A'\n      })\n      \n    } catch (error) {\n      logger.error('Auto-discovery analysis failed:', error)\n    }\n  }\n\n  async gatherStatistics() {\n    const stats = {\n      totalEntities: 0,\n      totalRelationships: 0,\n      averageConnectionsPerEntity: 0,\n      mostCommonRelationshipTypes: [],\n      dataTypes: {},\n      metadataFields: {},\n      embedding: {\n        averageSimilarity: 0,\n        clusters: []\n      }\n    }\n    \n    try {\n      // Get basic statistics from Brainy\n      const brainyStats = await this.db.getStatistics()\n      \n      if (brainyStats) {\n        stats.totalEntities = brainyStats.nounCount || 0\n        stats.totalRelationships = brainyStats.verbCount || 0\n        \n        if (stats.totalEntities > 0 && stats.totalRelationships > 0) {\n          stats.averageConnectionsPerEntity = stats.totalRelationships / stats.totalEntities\n        }\n      }\n      \n      // Analyze data types and metadata (sample-based for performance)\n      const sampleSize = Math.min(100, stat