forensic-ai #4
@ -702,12 +702,10 @@ class AIQueryInterface {
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toolsByPhase[phase] = [];
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});
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// DEBUG: Log recommendation structure
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console.log('[AI Results] Recommendation structure:', recommendation);
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console.log('[AI Results] Recommended tools:', recommendation.recommended_tools);
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recommendation.recommended_tools?.forEach(recTool => {
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// DEBUG: Log each tool's confidence data
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console.log('[AI Results] Tool confidence data:', recTool.name, recTool.confidence);
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if (toolsByPhase[recTool.phase]) {
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@ -716,7 +714,7 @@ class AIQueryInterface {
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toolsByPhase[recTool.phase].push({
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...fullTool,
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recommendation: recTool,
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confidence: recTool.confidence, // Ensure confidence is passed
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confidence: recTool.confidence,
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justification: recTool.justification,
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priority: recTool.priority,
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recommendationStrength: recTool.recommendationStrength
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@ -836,13 +834,11 @@ class AIQueryInterface {
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return '';
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}
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// Calculate summary statistics
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const totalTime = auditTrail.reduce((sum, entry) => sum + entry.processingTimeMs, 0);
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const avgConfidence = auditTrail.reduce((sum, entry) => sum + entry.confidence, 0) / auditTrail.length;
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const lowConfidenceSteps = auditTrail.filter(entry => entry.confidence < 60).length;
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const highConfidenceSteps = auditTrail.filter(entry => entry.confidence >= 80).length;
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// Group entries by phase for better organization
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const groupedEntries = auditTrail.reduce((groups, entry) => {
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if (!groups[entry.phase]) groups[entry.phase] = [];
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groups[entry.phase].push(entry);
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@ -1048,7 +1044,6 @@ class AIQueryInterface {
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second: '2-digit'
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});
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// Reuse existing grid and text utilities
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return `
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<div class="border-l-2 pl-3 py-2 mb-2" style="border-left-color: ${confidenceColor};">
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<div class="flex justify-between items-center mb-1">
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@ -2,7 +2,6 @@
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export const AI_PROMPTS = {
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// Main tool selection prompt
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toolSelection: (mode: string, userQuery: string, selectionMethod: string, maxSelectedItems: number) => {
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const modeInstruction = mode === 'workflow'
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? 'Der Benutzer möchte einen UMFASSENDEN WORKFLOW mit mehreren Tools/Methoden über verschiedene Phasen. Wählen Sie 15-25 Tools aus, die den vollständigen Untersuchungslebenszyklus abdecken.'
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@ -51,7 +50,6 @@ Antworten Sie NUR mit diesem JSON-Format:
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}`;
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},
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// Scenario analysis prompt
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scenarioAnalysis: (isWorkflow: boolean, userQuery: string) => {
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const analysisType = isWorkflow ? 'forensische Szenario' : 'technische Problem';
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const considerations = isWorkflow ?
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@ -74,7 +72,6 @@ ${considerations}
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WICHTIG: Antworten Sie NUR in fließendem deutschen Text ohne Listen, Aufzählungen oder Markdown-Formatierung. Maximum 150 Wörter.`;
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},
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// Investigation approach prompt
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investigationApproach: (isWorkflow: boolean, userQuery: string) => {
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const approachType = isWorkflow ? 'Untersuchungsansatz' : 'Lösungsansatz';
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const considerations = isWorkflow ?
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@ -96,7 +93,6 @@ ${considerations}
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WICHTIG: Antworten Sie NUR in fließendem deutschen Text ohne Listen oder Markdown. Maximum 150 Wörter.`;
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},
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// Critical considerations prompt
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criticalConsiderations: (isWorkflow: boolean, userQuery: string) => {
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const considerationType = isWorkflow ? 'kritische forensische Überlegungen' : 'wichtige methodische Voraussetzungen';
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const aspects = isWorkflow ?
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@ -179,7 +175,6 @@ WICHTIG:
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- "pros" soll die Stärken für diese spezifische Aufgabe hervorheben`;
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},
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// Background knowledge selection prompt
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backgroundKnowledgeSelection: (userQuery: string, mode: string, selectedToolNames: string[], availableConcepts: any[]) => {
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return `Wählen Sie relevante forensische Konzepte für das Verständnis der empfohlenen Methodik.
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@ -200,7 +195,6 @@ Antworten Sie AUSSCHLIESSLICH mit diesem JSON-Format:
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]`;
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},
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// Final recommendations prompt
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finalRecommendations: (isWorkflow: boolean, userQuery: string, selectedToolNames: string[]) => {
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const prompt = isWorkflow ?
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`Erstellen Sie eine Workflow-Empfehlung basierend auf DFIR-Prinzipien.
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@ -225,7 +219,6 @@ WICHTIG: Antworten Sie NUR in fließendem deutschen Text ohne Listen oder Markdo
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}
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} as const;
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// Type-safe prompt function with proper overloads
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export function getPrompt(key: 'toolSelection', mode: string, userQuery: string, selectionMethod: string, maxSelectedItems: number): string;
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export function getPrompt(key: 'scenarioAnalysis', isWorkflow: boolean, userQuery: string): string;
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export function getPrompt(key: 'investigationApproach', isWorkflow: boolean, userQuery: string): string;
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@ -238,7 +231,6 @@ export function getPrompt(promptKey: keyof typeof AI_PROMPTS, ...args: any[]): s
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try {
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const promptFunction = AI_PROMPTS[promptKey];
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if (typeof promptFunction === 'function') {
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// Use type assertion since we've validated the function exists
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return (promptFunction as (...args: any[]) => string)(...args);
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} else {
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console.error(`[PROMPTS] Invalid prompt key: ${promptKey}`);
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@ -265,20 +265,15 @@ const phases = data.phases;
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return;
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}
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// AI Button click handler
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if (aiQueryBtn) {
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aiQueryBtn.addEventListener('click', () => {
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// Visual feedback
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aiQueryBtn.classList.add('activated');
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setTimeout(() => aiQueryBtn.classList.remove('activated'), 400);
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// Switch to AI view
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switchToView('ai');
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// Trigger existing view change system
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window.dispatchEvent(new CustomEvent('viewChanged', { detail: 'ai' }));
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// Scroll to AI interface
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if (window.scrollToElementById) {
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window.scrollToElementById('ai-interface');
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} else {
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@ -294,14 +289,12 @@ const phases = data.phases;
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const filtersSection = document.getElementById('filters-section');
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const noResults = document.getElementById('no-results');
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// Hide all views first
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if (toolsGrid) toolsGrid.style.display = 'none';
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if (matrixContainer) matrixContainer.style.display = 'none';
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if (aiInterface) aiInterface.style.display = 'none';
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if (filtersSection) filtersSection.style.display = 'none';
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if (noResults) noResults.style.display = 'none';
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// Show selected view
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switch (view) {
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case 'grid':
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if (toolsGrid) toolsGrid.style.display = 'block';
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@ -63,17 +63,15 @@ interface AnalysisContext {
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auditTrail: AuditEntry[];
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// Store actual similarity data from embeddings
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embeddingsSimilarities: Map<string, number>;
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}
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interface ConfidenceMetrics {
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overall: number; // 0-100: Combined confidence score
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semanticRelevance: number; // How well tool description matches query (from embeddings)
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taskSuitability: number; // AI-determined fitness for this specific task
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methodologicalConsistency: number; // How well different analysis steps agree
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uncertaintyFactors: string[]; // Specific reasons why this might not work
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strengthIndicators: string[]; // Specific reasons why this is a good choice
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overall: number;
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semanticRelevance: number;
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taskSuitability: number;
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uncertaintyFactors: string[];
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strengthIndicators: string[];
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}
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class ImprovedMicroTaskAIPipeline {
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@ -102,10 +100,10 @@ class ImprovedMicroTaskAIPipeline {
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};
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private confidenceConfig: {
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semanticWeight: number; // Weight for embeddings similarity
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suitabilityWeight: number; // Weight for AI task fit evaluation
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consistencyWeight: number; // Weight for cross-validation agreement
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reliabilityWeight: number; // Weight for tool quality indicators
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semanticWeight: number;
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suitabilityWeight: number;
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consistencyWeight: number;
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reliabilityWeight: number;
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minimumThreshold: number;
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mediumThreshold: number;
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highThreshold: number;
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@ -143,10 +141,9 @@ class ImprovedMicroTaskAIPipeline {
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retentionHours: parseInt(process.env.FORENSIC_AUDIT_RETENTION_HOURS || '72', 10)
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};
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// Updated confidence weights - more focused on AI evaluation
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this.confidenceConfig = {
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semanticWeight: parseFloat(process.env.CONFIDENCE_SEMANTIC_WEIGHT || '0.3'), // Embeddings similarity
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suitabilityWeight: parseFloat(process.env.CONFIDENCE_SUITABILITY_WEIGHT || '0.7'), // AI task fit evaluation
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semanticWeight: parseFloat(process.env.CONFIDENCE_SEMANTIC_WEIGHT || '0.3'),
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suitabilityWeight: parseFloat(process.env.CONFIDENCE_SUITABILITY_WEIGHT || '0.7'),
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consistencyWeight: 0,
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reliabilityWeight: 0,
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minimumThreshold: parseInt(process.env.CONFIDENCE_MINIMUM_THRESHOLD || '40', 10),
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@ -235,7 +232,7 @@ class ImprovedMicroTaskAIPipeline {
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const selectionRatio = result.selectedTools.length / candidateCount;
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const hasReasoning = result.reasoning && result.reasoning.length > 50;
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let confidence = 60; // Base confidence
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let confidence = 60;
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if (selectionRatio > 0.05 && selectionRatio < 0.3) confidence += 20;
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else if (selectionRatio <= 0.05) confidence -= 10;
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@ -386,7 +383,6 @@ class ImprovedMicroTaskAIPipeline {
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let candidateConcepts: any[] = [];
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let selectionMethod = 'unknown';
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// Initialize embeddings similarities storage
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context.embeddingsSimilarities = new Map<string, number>();
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if (process.env.AI_EMBEDDINGS_ENABLED === 'true') {
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@ -409,7 +405,6 @@ class ImprovedMicroTaskAIPipeline {
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console.log(`[AI PIPELINE] Embeddings found ${similarItems.length} similar items`);
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// Store actual similarity scores for confidence calculation
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similarItems.forEach(item => {
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context.embeddingsSimilarities.set(item.name, item.similarity);
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});
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@ -707,18 +702,14 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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limitations: string[] = []
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): ConfidenceMetrics {
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// 1. Semantic Relevance: Real embeddings similarity score
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const rawSemanticRelevance = context.embeddingsSimilarities.has(tool.name) ?
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context.embeddingsSimilarities.get(tool.name)! * 100 : 50;
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// 2. Task Suitability: Enhanced with phase-awareness for workflow mode
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let enhancedTaskSuitability = taskRelevance;
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if (context.mode === 'workflow') {
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// In workflow mode, boost score if tool is well-matched to its assigned phase
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const toolSelection = context.selectedTools?.find(st => st.tool.name === tool.name);
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if (toolSelection && tool.phases && tool.phases.includes(toolSelection.phase)) {
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// Boost for phase alignment (but cap at 100)
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const phaseBonus = Math.min(15, 100 - taskRelevance);
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enhancedTaskSuitability = Math.min(100, taskRelevance + phaseBonus);
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@ -726,7 +717,6 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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}
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}
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// Simple weighted combination - no artificial scaling
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const overall = (
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rawSemanticRelevance * this.confidenceConfig.semanticWeight +
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enhancedTaskSuitability * this.confidenceConfig.suitabilityWeight
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@ -747,7 +737,6 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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overall: Math.round(overall),
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semanticRelevance: Math.round(rawSemanticRelevance),
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taskSuitability: Math.round(enhancedTaskSuitability),
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methodologicalConsistency: 0,
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uncertaintyFactors,
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strengthIndicators
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};
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@ -756,18 +745,15 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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private identifySpecificUncertaintyFactors(tool: any, context: AnalysisContext, limitations: string[], confidence: number): string[] {
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const factors: string[] = [];
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// Add AI-identified limitations first (most specific)
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if (limitations && limitations.length > 0) {
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factors.push(...limitations.slice(0, 2)); // Limit to top 2 to leave room for others
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factors.push(...limitations.slice(0, 2));
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}
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// Low semantic similarity
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const similarity = context.embeddingsSimilarities.get(tool.name) || 0.5;
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if (similarity < 0.7) {
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factors.push('Geringe semantische Ähnlichkeit zur Anfrage - Tool-Beschreibung passt möglicherweise nicht optimal');
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}
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// Skill level vs scenario complexity mismatch
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if (tool.skillLevel === 'expert' && /schnell|rapid|triage|urgent|sofort/i.test(context.userQuery)) {
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factors.push('Experten-Tool für zeitkritisches Szenario - Setup und Einarbeitung könnten zu lange dauern');
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}
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@ -776,35 +762,29 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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factors.push('Einsteiger-Tool für komplexe Analyse - könnte funktionale Limitierungen haben');
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}
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// Access and deployment concerns
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if (tool.type === 'software' && !isToolHosted(tool) && tool.accessType === 'download') {
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factors.push('Installation und Setup erforderlich');
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}
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// License restrictions
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if (tool.license === 'Proprietary') {
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factors.push('Kommerzielle Software - Lizenzkosten und rechtliche Beschränkungen zu beachten');
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}
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// Low overall confidence warning
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if (confidence < 60) {
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factors.push('Moderate Gesamtbewertung - alternative Ansätze sollten ebenfalls betrachtet werden');
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}
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return factors.slice(0, 4); // Limit to 4 most relevant factors
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return factors.slice(0, 4);
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}
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// NEW: Identify specific strength indicators
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private identifySpecificStrengthIndicators(tool: any, context: AnalysisContext, confidence: number): string[] {
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const indicators: string[] = [];
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// High semantic similarity
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const similarity = context.embeddingsSimilarities.get(tool.name) || 0.5;
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if (similarity >= 0.7) {
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indicators.push('Sehr gute semantische Übereinstimmung mit Ihrer Anfrage');
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}
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// Quality indicators
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if (tool.knowledgebase === true) {
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indicators.push('Umfassende Dokumentation und Wissensbasis verfügbar');
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}
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@ -813,17 +793,15 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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indicators.push('Sofort verfügbar über gehostete Lösung - kein Setup erforderlich');
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}
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// Skill level match
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if (tool.skillLevel === 'intermediate' || tool.skillLevel === 'advanced') {
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indicators.push('Ausgewogenes Verhältnis zwischen Funktionalität und Benutzerfreundlichkeit');
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}
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// Method alignment
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if (tool.type === 'method' && /methodik|vorgehen|prozess|ansatz/i.test(context.userQuery)) {
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indicators.push('Methodischer Ansatz passt zu Ihrer prozeduralen Anfrage');
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}
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return indicators.slice(0, 4); // Limit to 4 most important indicators
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return indicators.slice(0, 4);
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}
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private async analyzeScenario(context: AnalysisContext): Promise<MicroTaskResult> {
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@ -902,11 +880,9 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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validSelections.forEach((sel: any) => {
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const tool = phaseTools.find((t: any) => t.name === sel.toolName);
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if (tool) {
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// Ensure taskRelevance is a number
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const taskRelevance = typeof sel.taskRelevance === 'number' ?
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sel.taskRelevance : parseInt(String(sel.taskRelevance)) || 70;
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// Derive priority automatically from score
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const priority = this.derivePriorityFromScore(taskRelevance);
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this.addToolToSelection(context, tool, phase.id, priority, sel.justification, taskRelevance, sel.limitations);
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@ -967,7 +943,7 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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hasExplanation: !!evaluation.detailed_explanation,
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hasImplementationApproach: !!evaluation.implementation_approach,
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prosCount: evaluation.pros?.length || 0,
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limitationsCount: evaluation.limitations?.length || 0, // ← Updated field name
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limitationsCount: evaluation.limitations?.length || 0,
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hasLimitations: Array.isArray(evaluation.limitations) && evaluation.limitations.length > 0
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},
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70,
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@ -1101,7 +1077,7 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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const context: AnalysisContext = {
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userQuery,
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mode,
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filteredData: {}, // Will be populated by getIntelligentCandidates
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filteredData: {},
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contextHistory: [],
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maxContextLength: this.maxContextTokens,
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currentContextLength: 0,
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@ -1125,8 +1101,6 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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{ auditEnabled: this.auditConfig.enabled, confidenceScoringEnabled: true }
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);
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// MICRO-TASK SEQUENCE WITH ENHANCED CONFIDENCE TRACKING
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const analysisResult = await this.analyzeScenario(context);
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if (analysisResult.success) completeTasks++; else failedTasks++;
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await this.delay(this.microTaskDelay);
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@ -1234,7 +1208,6 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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components: {
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semantic: confidence.semanticRelevance,
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suitability: confidence.taskSuitability,
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consistency: confidence.methodologicalConsistency
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}
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},
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confidence.overall,
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@ -1286,7 +1259,7 @@ ${JSON.stringify(conceptsToSend, null, 2)}`;
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detailed_explanation: st.tool.evaluation?.detailed_explanation || '',
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implementation_approach: st.tool.evaluation?.implementation_approach || '',
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pros: st.tool.evaluation?.pros || [],
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cons: st.tool.evaluation?.limitations || [], // ← FIXED: Use limitations as cons for display
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cons: st.tool.evaluation?.limitations || [],
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alternatives: st.tool.evaluation?.alternatives || '',
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confidence: confidence,
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recommendationStrength: confidence.overall >= this.confidenceConfig.highThreshold ? 'strong' :
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@ -31,7 +31,7 @@ interface SimilarityResult extends EmbeddingData {
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class EmbeddingsService {
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private embeddings: EmbeddingData[] = [];
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private isInitialized = false;
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private initializationPromise: Promise<void> | null = null; // ADD THIS LINE
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private initializationPromise: Promise<void> | null = null;
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private readonly embeddingsPath = path.join(process.cwd(), 'data', 'embeddings.json');
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private readonly batchSize: number;
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private readonly batchDelay: number;
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@ -43,24 +43,19 @@ class EmbeddingsService {
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this.batchDelay = parseInt(process.env.AI_EMBEDDINGS_BATCH_DELAY_MS || '1000', 10);
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}
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// REPLACE the existing initialize method with this:
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async initialize(): Promise<void> {
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// If initialization is already in progress, wait for it
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if (this.initializationPromise) {
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return this.initializationPromise;
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}
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// If already initialized, return immediately
|
||||
if (this.isInitialized) {
|
||||
return Promise.resolve();
|
||||
}
|
||||
|
||||
// Start initialization and store the promise
|
||||
this.initializationPromise = this.performInitialization();
|
||||
return this.initializationPromise;
|
||||
}
|
||||
|
||||
// ADD THIS NEW METHOD:
|
||||
private async performInitialization(): Promise<void> {
|
||||
if (!this.enabled) {
|
||||
console.log('[EMBEDDINGS] Embeddings disabled, skipping initialization');
|
||||
@ -70,13 +65,11 @@ class EmbeddingsService {
|
||||
try {
|
||||
console.log('[EMBEDDINGS] Initializing embeddings system...');
|
||||
|
||||
// Create data directory if it doesn't exist
|
||||
await fs.mkdir(path.dirname(this.embeddingsPath), { recursive: true });
|
||||
|
||||
const toolsData = await getCompressedToolsDataForAI();
|
||||
const currentDataHash = this.hashData(toolsData);
|
||||
|
||||
// Try to load existing embeddings
|
||||
const existingEmbeddings = await this.loadEmbeddings();
|
||||
|
||||
if (existingEmbeddings && existingEmbeddings.version === currentDataHash) {
|
||||
@ -336,12 +329,10 @@ class EmbeddingsService {
|
||||
|
||||
|
||||
|
||||
// Global instance
|
||||
const embeddingsService = new EmbeddingsService();
|
||||
|
||||
export { embeddingsService, type EmbeddingData, type SimilarityResult };
|
||||
|
||||
// Auto-initialize on import in server environment
|
||||
if (typeof window === 'undefined' && process.env.NODE_ENV !== 'test') {
|
||||
embeddingsService.initialize().catch(error => {
|
||||
console.error('[EMBEDDINGS] Auto-initialization failed:', error);
|
||||
|
||||
@ -96,7 +96,6 @@ class RateLimitedQueue {
|
||||
|
||||
this.tasks.push(queuedTask);
|
||||
|
||||
// Kick the processor soon.
|
||||
setTimeout(() => {
|
||||
this.processQueue();
|
||||
}, 100);
|
||||
@ -170,7 +169,7 @@ class RateLimitedQueue {
|
||||
.filter((t) => t.status === "queued")
|
||||
.sort((a, b) => a.addedAt - b.addedAt)[0];
|
||||
|
||||
if (!nextTask) break; // No more work
|
||||
if (!nextTask) break;
|
||||
|
||||
nextTask.status = "processing";
|
||||
nextTask.startedAt = Date.now();
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user