airefactor #19
@ -217,7 +217,6 @@ const domainAgnosticSoftware = data['domain-agnostic-software'] || [];
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<script type="module" define:vars={{ tools, phases, domainAgnosticSoftware }}>
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// Utility functions (inline to avoid import issues)
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function showElement(element) {
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if (element) {
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element.style.display = 'block';
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@ -908,40 +907,537 @@ class AIQueryInterface {
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}
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renderAuditTrail(rawAuditTrail) {
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// Simplified audit trail rendering - remove complex processor
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const container = document.getElementById('audit-trail-container');
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if (!container || !rawAuditTrail || !Array.isArray(rawAuditTrail)) return;
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if (!container || !rawAuditTrail || !Array.isArray(rawAuditTrail)) {
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console.warn('[AI Interface] Cannot render audit trail: invalid container or data');
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return;
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}
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const totalTime = rawAuditTrail.reduce((sum, entry) => sum + (entry.processingTimeMs || 0), 0);
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const avgConfidence = rawAuditTrail.length > 0
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? Math.round(rawAuditTrail.reduce((sum, entry) => sum + (entry.confidence || 0), 0) / rawAuditTrail.length)
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: 0;
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console.log('[AI Interface] Rendering comprehensive audit trail with', rawAuditTrail.length, 'entries');
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container.innerHTML = `
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<div class="audit-trail-container">
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<div class="audit-trail-header">
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<div class="audit-trail-title">
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<div class="audit-icon">
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<div class="audit-icon-gradient">✓</div>
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<h4>KI-Entscheidungspfad</h4>
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try {
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// Calculate audit statistics
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const stats = this.calculateAuditStats(rawAuditTrail);
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container.innerHTML = `
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<div class="audit-trail-container">
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<div class="audit-trail-header clickable" onclick="this.parentElement.querySelector('.audit-trail-details').classList.toggle('collapsed'); this.querySelector('.toggle-icon').style.transform = this.parentElement.querySelector('.audit-trail-details').classList.contains('collapsed') ? 'rotate(0deg)' : 'rotate(90deg)';">
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<div class="audit-trail-title">
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<div class="audit-icon">
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<div class="audit-icon-gradient">🔍</div>
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<h4>KI-Entscheidungspfad</h4>
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</div>
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<div class="audit-stats">
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<div class="stat-item">
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<div class="stat-dot stat-time"></div>
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<span>${formatDuration(stats.totalTime)}</span>
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</div>
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<div class="stat-item">
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<div class="stat-dot" style="background-color: ${getConfidenceColor(stats.avgConfidence)};"></div>
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<span>${stats.avgConfidence}% Vertrauen</span>
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</div>
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<div class="stat-item">
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<span>${rawAuditTrail.length} Schritte</span>
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</div>
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</div>
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</div>
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<div class="audit-stats">
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<div class="stat-item">
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<span>${formatDuration(totalTime)}</span>
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<svg class="toggle-icon" width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" style="transform: rotate(90deg);">
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<polyline points="9 18 15 12 9 6"/>
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</svg>
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</div>
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<div class="audit-trail-details">
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<!-- Audit Summary -->
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<div class="audit-summary">
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<div class="summary-header">📊 Analyse-Zusammenfassung</div>
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<div class="summary-grid">
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<div class="summary-stat">
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<div class="summary-value success">${stats.aiDecisionCount}</div>
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<div class="summary-label">KI-Entscheidungen</div>
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</div>
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<div class="summary-stat">
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<div class="summary-value ${stats.embeddingsUsageCount > 0 ? 'success' : 'warning'}">${stats.embeddingsUsageCount}</div>
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<div class="summary-label">Semantische Suchen</div>
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</div>
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<div class="summary-stat">
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<div class="summary-value success">${stats.toolSelectionCount}</div>
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<div class="summary-label">Tool-Auswahlen</div>
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</div>
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</div>
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<div class="stat-item">
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<span>${avgConfidence}% Vertrauen</span>
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</div>
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<div class="stat-item">
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<span>${rawAuditTrail.length} Schritte</span>
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<div class="insights-section">
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${stats.qualityMetrics.aiTransparency >= 80 ? `
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<div class="insights-header success">✅ Hohe Transparenz</div>
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<ul class="insights-list">
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<li>${stats.qualityMetrics.aiTransparency}% der Entscheidungen mit nachvollziehbarer Begründung</li>
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<li>Durchschnittliche Verarbeitungszeit: ${formatDuration(stats.qualityMetrics.avgProcessingTime)}</li>
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</ul>
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` : `
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<div class="insights-header warning">⚠️ Transparenz-Hinweise</div>
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<ul class="insights-list">
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<li>Nur ${stats.qualityMetrics.aiTransparency}% der Entscheidungen vollständig dokumentiert</li>
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<li>Einige KI-Entscheidungen ohne detaillierte Begründung</li>
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</ul>
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`}
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</div>
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</div>
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<!-- Process Flow -->
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<div class="audit-process-flow">
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${this.renderPhaseGroups(rawAuditTrail, stats)}
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</div>
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<!-- Download/Upload Controls -->
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<div class="ai-results-controls" style="margin-top: 1.5rem; text-align: center; border-top: 1px solid var(--color-border); padding-top: 1rem;">
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<button id="download-results-btn" class="btn btn-secondary" style="margin-right: 0.5rem;">
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<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" style="margin-right: 0.5rem;">
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<path d="M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4"/>
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<polyline points="7 10 12 15 17 10"/>
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<line x1="12" y1="15" x2="12" y2="3"/>
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</svg>
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Analyse herunterladen
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</button>
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<label for="upload-results" class="btn btn-secondary">
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<svg width="16" height="16" viewBox="0 0 24 24" fill="none" stroke="currentColor" stroke-width="2" style="margin-right: 0.5rem;">
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<path d="M21 15v4a2 2 0 0 1-2 2H5a2 2 0 0 1-2-2v-4"/>
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<polyline points="17 8 12 3 7 8"/>
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<line x1="12" y1="3" x2="12" y2="15"/>
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</svg>
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Analyse hochladen
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<input type="file" id="upload-results" accept=".json" style="display: none;" />
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</label>
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</div>
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<!-- Technical Details Toggle -->
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<div class="technical-toggle">
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<button class="technical-toggle-btn" onclick="this.parentElement.parentElement.querySelector('.technical-details').classList.toggle('collapsed'); this.textContent = this.parentElement.parentElement.querySelector('.technical-details').classList.contains('collapsed') ? 'Technische Details anzeigen' : 'Technische Details verbergen';">
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Technische Details anzeigen
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</button>
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</div>
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<!-- Technical Details -->
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<div class="technical-details collapsed">
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${this.renderTechnicalDetails(rawAuditTrail)}
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</div>
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</div>
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</div>
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`;
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// Setup download functionality
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this.setupDownloadUpload();
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} catch (error) {
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console.error('[AI Interface] Error rendering audit trail:', error);
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container.innerHTML = `
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<div class="audit-trail-container">
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<div class="audit-trail-header">
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<div class="audit-trail-title">
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<div class="audit-icon">
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<div class="audit-icon-gradient">⚠️</div>
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<h4>Audit Trail Fehler</h4>
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</div>
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</div>
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</div>
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<div class="audit-trail-details">
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<p style="color: var(--color-error); padding: 1rem;">
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Fehler beim Rendern des Audit Trails. Details in der Konsole.
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</p>
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</div>
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</div>
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`;
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}
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}
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calculateAuditStats(auditTrail) {
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if (!auditTrail || auditTrail.length === 0) {
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return {
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totalTime: 0,
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avgConfidence: 0,
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stepCount: 0,
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aiDecisionCount: 0,
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embeddingsUsageCount: 0,
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toolSelectionCount: 0,
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qualityMetrics: {
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avgProcessingTime: 0,
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aiTransparency: 0
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}
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};
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}
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const totalTime = auditTrail.reduce((sum, entry) => sum + (entry.processingTimeMs || 0), 0);
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const validConfidenceEntries = auditTrail.filter(entry => typeof entry.confidence === 'number');
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const avgConfidence = validConfidenceEntries.length > 0
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? Math.round(validConfidenceEntries.reduce((sum, entry) => sum + entry.confidence, 0) / validConfidenceEntries.length)
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: 0;
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const aiDecisionCount = auditTrail.filter(entry => entry.action === 'ai-decision').length;
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const embeddingsUsageCount = auditTrail.filter(entry => entry.metadata?.embeddingsUsed).length;
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const toolSelectionCount = auditTrail.filter(entry => entry.action === 'selection-decision').length;
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const avgProcessingTime = auditTrail.length > 0 ? totalTime / auditTrail.length : 0;
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const aiTransparency = auditTrail.length > 0 ?
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(auditTrail.filter(entry => entry.metadata?.aiPrompt || entry.metadata?.reasoning).length / auditTrail.length) * 100 : 0;
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return {
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totalTime,
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avgConfidence,
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stepCount: auditTrail.length,
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aiDecisionCount,
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embeddingsUsageCount,
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toolSelectionCount,
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qualityMetrics: {
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avgProcessingTime,
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aiTransparency: Math.round(aiTransparency)
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}
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};
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}
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renderPhaseGroups(auditTrail, stats) {
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// Group audit entries by phase
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const phaseGroups = new Map();
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auditTrail.forEach(entry => {
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const phase = entry.phase || 'unknown';
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if (!phaseGroups.has(phase)) {
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phaseGroups.set(phase, []);
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}
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// FIXED: Remove non-null assertion, use proper null checking
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const phaseEntries = phaseGroups.get(phase);
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if (phaseEntries) {
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phaseEntries.push(entry);
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}
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});
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let html = '';
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let groupIndex = 0;
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for (const [phaseName, entries] of phaseGroups) {
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const isLastPhase = groupIndex === phaseGroups.size - 1;
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const phaseAvgConfidence = entries.reduce((sum, e) => sum + (e.confidence || 0), 0) / entries.length;
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html += `
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<div class="phase-group ${isLastPhase ? 'last-phase' : ''}">
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<div class="phase-header" style="display: flex; align-items: center; gap: 1rem; margin-bottom: 1rem;">
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<div style="display: flex; align-items: center; gap: 0.75rem;">
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<div class="phase-icon">${this.getPhaseIcon(phaseName)}</div>
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<div class="phase-name">${this.getPhaseDisplayName(phaseName)}</div>
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</div>
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<div class="phase-divider"></div>
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<div class="phase-stats">
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<div class="confidence-bar">
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<div class="confidence-fill" style="width: ${phaseAvgConfidence}%; background-color: ${getConfidenceColor(phaseAvgConfidence)};"></div>
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</div>
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<span class="confidence-text">${Math.round(phaseAvgConfidence)}%</span>
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</div>
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</div>
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<div class="phase-entries">
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${entries.map(entry => this.renderAuditEntry(entry)).join('')}
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</div>
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</div>
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`;
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groupIndex++;
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}
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return html;
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}
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renderAuditEntry(entry) {
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const confidenceColor = getConfidenceColor(entry.confidence || 0);
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const processingTime = formatDuration(entry.processingTimeMs || 0);
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return `
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<div class="audit-entry">
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<div class="entry-main">
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<div class="entry-action">${this.getActionDisplayName(entry.action)}</div>
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<div class="entry-meta">
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<div class="confidence-indicator" style="background-color: ${confidenceColor};"></div>
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<span class="confidence-value">${entry.confidence || 0}%</span>
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<span class="processing-time">${processingTime}</span>
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</div>
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</div>
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${this.renderEntryDetails(entry)}
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</div>
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`;
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}
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renderEntryDetails(entry) {
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const details = [];
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// AI-specific details
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if (entry.action === 'ai-decision' && entry.metadata?.reasoning) {
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details.push(`<div class="detail-item"><strong>Begründung:</strong> ${truncateText(entry.metadata.reasoning, 200)}</div>`);
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}
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// Tool selection details
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if (entry.action === 'selection-decision') {
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if (entry.metadata?.selectedToolsCount && entry.metadata?.availableToolsCount) {
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details.push(`<div class="detail-item"><strong>Auswahl:</strong> ${entry.metadata.selectedToolsCount} von ${entry.metadata.availableToolsCount} Tools</div>`);
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}
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if (entry.metadata?.selectionMethod) {
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details.push(`<div class="detail-item"><strong>Methode:</strong> ${entry.metadata.selectionMethod}</div>`);
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}
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}
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// Embeddings details
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if (entry.metadata?.embeddingsUsed && entry.metadata?.totalMatches) {
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details.push(`<div class="detail-item"><strong>Semantische Treffer:</strong> ${entry.metadata.totalMatches}</div>`);
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}
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// Confidence factors
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if (entry.metadata?.confidenceFactors?.length > 0) {
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const factors = entry.metadata.confidenceFactors.slice(0, 2).join(', ');
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details.push(`<div class="detail-item"><strong>Faktoren:</strong> ${factors}</div>`);
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}
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if (details.length === 0) return '';
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return `
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<div class="entry-details">
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${details.join('')}
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</div>
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`;
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}
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renderTechnicalDetails(auditTrail) {
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return auditTrail.map(entry => `
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<div class="technical-entry">
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<div class="technical-header">
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<div class="technical-phase">${entry.phase}/${entry.action}</div>
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<div class="technical-time">${new Date(entry.timestamp).toLocaleTimeString('de-DE')}</div>
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</div>
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<div class="technical-content">
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${entry.metadata?.aiModel ? `<div class="technical-row">Model: ${entry.metadata.aiModel}</div>` : ''}
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${entry.metadata?.promptTokens ? `<div class="technical-row">Tokens: ${entry.metadata.promptTokens}/${entry.metadata.completionTokens}</div>` : ''}
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${entry.metadata?.microTaskType ? `<div class="technical-row">Task: ${entry.metadata.microTaskType}</div>` : ''}
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${entry.metadata?.selectionMethod ? `<div class="technical-row">Method: ${entry.metadata.selectionMethod}</div>` : ''}
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<div class="technical-row">Confidence: ${entry.confidence}% (${entry.processingTimeMs}ms)</div>
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</div>
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</div>
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`).join('');
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}
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getPhaseIcon(phase) {
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const icons = {
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'initialization': '🚀',
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'tool-selection': '🔧',
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'contextual-analysis': '🧠',
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'workflow-phase': '⚡',
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'tool-reasoning': '💭',
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'knowledge-synthesis': '📚',
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'confidence-scoring': '📊',
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'phase-completion': '✅',
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'completion': '🎯',
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'embeddings': '🔍',
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'unknown': '❓'
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};
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return icons[phase] || icons['unknown'];
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}
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getPhaseDisplayName(phase) {
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const names = {
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'initialization': 'Initialisierung',
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'tool-selection': 'Tool-Auswahl',
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'contextual-analysis': 'Kontext-Analyse',
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'workflow-phase': 'Workflow-Phase',
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'tool-reasoning': 'Tool-Bewertung',
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'knowledge-synthesis': 'Wissens-Synthese',
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'confidence-scoring': 'Vertrauenswertung',
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'phase-completion': 'Phasen-Vervollständigung',
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'completion': 'Abschluss',
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'embeddings': 'Semantische Suche',
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'unknown': 'Unbekannt'
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};
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return names[phase] || phase;
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}
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getActionDisplayName(action) {
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const actions = {
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'pipeline-start': 'Analyse gestartet',
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'selection-decision': 'Tools ausgewählt',
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'ai-decision': 'KI-Entscheidung',
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'phase-tool-selection': 'Phasen-Tools evaluiert',
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'tool-added-to-phase': 'Tool zur Phase hinzugefügt',
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'concept-selection': 'Konzepte ausgewählt',
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'tool-confidence': 'Vertrauen berechnet',
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'phase-enhancement': 'Phase vervollständigt',
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'similarity-search': 'Ähnlichkeitssuche',
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'pipeline-end': 'Analyse abgeschlossen'
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};
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return actions[action] || action;
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}
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setupDownloadUpload() {
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const downloadBtn = document.getElementById('download-results-btn');
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const uploadInput = document.getElementById('upload-results');
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if (downloadBtn) {
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downloadBtn.addEventListener('click', () => this.downloadResults());
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}
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if (uploadInput) {
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uploadInput.addEventListener('change', (event) => {
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// FIXED: Remove TypeScript casting
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const files = event.target.files;
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const file = files ? files[0] : null;
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if (file) {
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this.handleFileUpload(file);
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}
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});
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}
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}
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downloadResults() {
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if (!this.currentRecommendation) {
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alert('Keine Analyse zum Herunterladen verfügbar.');
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return;
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}
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// FIXED: Use safer property access
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const inputValue = this.elements.input ? this.elements.input.value : '';
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const exportData = {
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metadata: {
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timestamp: new Date().toISOString(),
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version: "1.0",
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toolsDataHash: "current", // This would come from dataService
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aiModel: "claude-sonnet-4", // This would come from aiService
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||||
aiParameters: {},
|
||||
userQuery: inputValue,
|
||||
mode: this.currentMode,
|
||||
processingStats: {},
|
||||
exportedBy: 'ForensicPathways'
|
||||
},
|
||||
recommendation: this.currentRecommendation,
|
||||
auditTrail: this.currentRecommendation.auditTrail || [],
|
||||
rawContext: {
|
||||
selectedTools: [],
|
||||
backgroundKnowledge: [],
|
||||
contextHistory: [],
|
||||
embeddingsSimilarities: {}
|
||||
}
|
||||
};
|
||||
|
||||
const blob = new Blob([JSON.stringify(exportData, null, 2)], {
|
||||
type: 'application/json'
|
||||
});
|
||||
|
||||
const url = URL.createObjectURL(blob);
|
||||
const a = document.createElement('a');
|
||||
a.href = url;
|
||||
a.download = `forensic-ai-analysis-${Date.now()}.json`;
|
||||
a.click();
|
||||
URL.revokeObjectURL(url);
|
||||
|
||||
console.log('[AI Interface] Analysis downloaded');
|
||||
}
|
||||
|
||||
async handleFileUpload(file) {
|
||||
try {
|
||||
// Security validation
|
||||
if (file.size > 10 * 1024 * 1024) {
|
||||
throw new Error('Datei zu groß (max 10MB)');
|
||||
}
|
||||
|
||||
if (!file.name.endsWith('.json')) {
|
||||
throw new Error('Ungültiger Dateityp - nur JSON-Dateien werden unterstützt');
|
||||
}
|
||||
|
||||
const text = await file.text();
|
||||
let data;
|
||||
|
||||
try {
|
||||
data = JSON.parse(text);
|
||||
} catch (error) {
|
||||
throw new Error('Ungültiges JSON-Format');
|
||||
}
|
||||
|
||||
if (!this.validateUploadStructure(data)) {
|
||||
throw new Error('Ungültiges Analyse-Dateiformat');
|
||||
}
|
||||
|
||||
console.log('[AI Interface] Valid analysis file uploaded');
|
||||
this.displayUploadedResults(data);
|
||||
|
||||
} catch (error) {
|
||||
console.error('[AI Interface] Upload failed:', error);
|
||||
alert(`Upload fehlgeschlagen: ${error.message}`);
|
||||
}
|
||||
}
|
||||
|
||||
validateUploadStructure(data) {
|
||||
try {
|
||||
return !!(
|
||||
data &&
|
||||
typeof data === 'object' &&
|
||||
data.metadata &&
|
||||
typeof data.metadata === 'object' &&
|
||||
typeof data.metadata.timestamp === 'string' &&
|
||||
data.recommendation &&
|
||||
typeof data.recommendation === 'object' &&
|
||||
Array.isArray(data.auditTrail)
|
||||
);
|
||||
} catch (error) {
|
||||
console.error('[AI Interface] Structure validation error:', error);
|
||||
return false;
|
||||
}
|
||||
}
|
||||
|
||||
displayUploadedResults(data) {
|
||||
try {
|
||||
// Show upload banner
|
||||
this.showUploadedBanner(data.metadata);
|
||||
|
||||
// Restore interface state
|
||||
this.currentRecommendation = data.recommendation;
|
||||
|
||||
// Display the uploaded analysis
|
||||
this.showResults();
|
||||
|
||||
// Update the recommendation display
|
||||
if (data.metadata.mode === 'workflow') {
|
||||
this.displayWorkflowResults(data.recommendation, data.metadata.userQuery);
|
||||
} else {
|
||||
this.displayToolResults(data.recommendation, data.metadata.userQuery);
|
||||
}
|
||||
|
||||
// Render the uploaded audit trail
|
||||
setTimeout(() => {
|
||||
this.renderAuditTrail(data.auditTrail);
|
||||
}, 100);
|
||||
|
||||
console.log('[AI Interface] Uploaded analysis displayed successfully');
|
||||
} catch (error) {
|
||||
console.error('[AI Interface] Error displaying uploaded results:', error);
|
||||
alert('Fehler beim Anzeigen der hochgeladenen Analyse');
|
||||
}
|
||||
}
|
||||
|
||||
showUploadedBanner(metadata) {
|
||||
const banner = `
|
||||
<div class="uploaded-results-banner" style="background: var(--color-bg-secondary); border: 1px solid var(--color-warning); border-radius: 0.5rem; padding: 1rem; margin-bottom: 1rem; display: flex; align-items: center; gap: 1rem;">
|
||||
<div style="font-size: 1.5rem;">📁</div>
|
||||
<div style="flex: 1;">
|
||||
<strong style="color: var(--color-warning);">Hochgeladene Analyse</strong>
|
||||
<div style="font-size: 0.875rem; color: var(--color-text-secondary); margin-top: 0.25rem;">
|
||||
Erstellt: ${new Date(metadata.timestamp).toLocaleString('de-DE')} |
|
||||
Modus: ${metadata.mode} |
|
||||
${metadata.toolsDataHash ? `Hash: ${metadata.toolsDataHash.slice(0, 8)}...` : ''}
|
||||
</div>
|
||||
</div>
|
||||
<button onclick="this.parentElement.remove()" style="background: none; border: none; color: var(--color-text-secondary); cursor: pointer; font-size: 1.25rem;">×</button>
|
||||
</div>
|
||||
`;
|
||||
|
||||
// FIXED: Add null checking
|
||||
if (this.elements && this.elements.results) {
|
||||
this.elements.results.insertAdjacentHTML('afterbegin', banner);
|
||||
}
|
||||
}
|
||||
|
||||
renderHeader(title, query) {
|
||||
return `
|
||||
<div style="text-align: center; margin-bottom: 2rem; padding: 1.5rem; background: linear-gradient(135deg, var(--color-primary) 0%, #525252 100%); color: white; border-radius: 0.75rem;">
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
---
|
||||
import { createToolSlug } from '../utils/toolHelpers.js';
|
||||
import { createToolSlug } from '../utils/clientUtils.js';
|
||||
|
||||
export interface Props {
|
||||
toolName: string;
|
||||
|
||||
@ -1,10 +1,11 @@
|
||||
// src/utils/aiPipeline.ts - Refactored
|
||||
import { getCompressedToolsDataForAI } from './dataService.js';
|
||||
// src/utils/aiPipeline.ts - Enhanced with comprehensive audit logging
|
||||
import { getCompressedToolsDataForAI, getDataVersion } from './dataService.js';
|
||||
import { aiService } from './aiService.js';
|
||||
import { toolSelector, type SelectionContext } from './toolSelector.js';
|
||||
import { confidenceScoring, type AnalysisContext } from './confidenceScoring.js';
|
||||
import { embeddingsService } from './embeddings.js';
|
||||
import { auditService, type AuditEntry } from './auditService.js';
|
||||
import { JSONParser } from './jsonUtils.js'; // FIXED: Use centralized JSON parsing
|
||||
import { getPrompt } from '../config/prompts.js';
|
||||
import 'dotenv/config';
|
||||
|
||||
@ -20,6 +21,11 @@ interface MicroTaskResult {
|
||||
processingTimeMs: number;
|
||||
success: boolean;
|
||||
error?: string;
|
||||
aiUsage?: {
|
||||
promptTokens?: number;
|
||||
completionTokens?: number;
|
||||
totalTokens?: number;
|
||||
};
|
||||
}
|
||||
|
||||
interface AnalysisResult {
|
||||
@ -32,6 +38,8 @@ interface AnalysisResult {
|
||||
microTasksCompleted: number;
|
||||
microTasksFailed: number;
|
||||
contextContinuityUsed: boolean;
|
||||
totalAITokensUsed: number;
|
||||
auditEntriesGenerated: number;
|
||||
};
|
||||
}
|
||||
|
||||
@ -64,6 +72,7 @@ interface PipelineContext {
|
||||
|
||||
class AIPipeline {
|
||||
private config: PipelineConfig;
|
||||
private totalTokensUsed: number = 0;
|
||||
|
||||
constructor() {
|
||||
this.config = {
|
||||
@ -79,6 +88,7 @@ class AIPipeline {
|
||||
const startTime = Date.now();
|
||||
let completedTasks = 0;
|
||||
let failedTasks = 0;
|
||||
this.totalTokensUsed = 0;
|
||||
|
||||
console.log('[AI-PIPELINE] Starting', mode, 'analysis pipeline');
|
||||
|
||||
@ -87,6 +97,8 @@ class AIPipeline {
|
||||
|
||||
try {
|
||||
const toolsData = await getCompressedToolsDataForAI();
|
||||
const aiConfig = aiService.getConfig();
|
||||
const toolsDataHash = getDataVersion?.() || 'unknown';
|
||||
|
||||
const context: PipelineContext = {
|
||||
userQuery,
|
||||
@ -99,67 +111,119 @@ class AIPipeline {
|
||||
embeddingsSimilarities: new Map<string, number>()
|
||||
};
|
||||
|
||||
// Phase 1: Get intelligent tool candidates
|
||||
// AUDIT: Pipeline initialization
|
||||
auditService.addEntry(
|
||||
'initialization',
|
||||
'pipeline-start',
|
||||
{
|
||||
userQuery: this.truncateForAudit(userQuery),
|
||||
mode,
|
||||
toolsDataLoaded: !!toolsData,
|
||||
aiConfig: { model: aiConfig.model }
|
||||
},
|
||||
{
|
||||
totalAvailableTools: toolsData.tools.length,
|
||||
totalAvailableConcepts: toolsData.concepts.length,
|
||||
embeddingsEnabled: embeddingsService.isEnabled()
|
||||
},
|
||||
90,
|
||||
startTime,
|
||||
{
|
||||
toolsDataHash,
|
||||
aiModel: aiConfig.model,
|
||||
embeddingsUsed: embeddingsService.isEnabled(),
|
||||
pipelineVersion: '2.0-enhanced'
|
||||
}
|
||||
);
|
||||
|
||||
// Phase 1: Get intelligent tool candidates with enhanced logging
|
||||
console.log('[AI-PIPELINE] Phase 1: Tool candidate selection');
|
||||
const candidateSelectionStart = Date.now();
|
||||
|
||||
const candidateData = await toolSelector.getIntelligentCandidates(userQuery, toolsData, mode, context);
|
||||
|
||||
// AUDIT: Tool candidate selection
|
||||
auditService.addToolSelection(
|
||||
candidateData.tools.map(t => t.name),
|
||||
toolsData.tools.map(t => t.name),
|
||||
candidateData.selectionMethod,
|
||||
85,
|
||||
candidateSelectionStart,
|
||||
{
|
||||
embeddingsUsed: embeddingsService.isEnabled(),
|
||||
totalCandidatesFound: candidateData.tools.length + candidateData.concepts.length,
|
||||
selectionMethod: candidateData.selectionMethod,
|
||||
reductionRatio: candidateData.tools.length / toolsData.tools.length
|
||||
}
|
||||
);
|
||||
|
||||
context.filteredData = candidateData;
|
||||
|
||||
this.addAuditEntry(
|
||||
'initialization',
|
||||
'pipeline-start',
|
||||
{ userQuery, mode, toolsDataLoaded: !!toolsData },
|
||||
{ candidateTools: candidateData.tools.length, candidateConcepts: candidateData.concepts.length },
|
||||
90,
|
||||
startTime,
|
||||
{ selectionMethod: candidateData.selectionMethod }
|
||||
);
|
||||
|
||||
// Phase 2: Contextual analysis micro-tasks
|
||||
// Phase 2: Contextual analysis micro-tasks with enhanced logging
|
||||
console.log('[AI-PIPELINE] Phase 2: Contextual analysis');
|
||||
|
||||
const analysisResult = await this.analyzeScenario(context);
|
||||
const analysisResult = await this.analyzeScenario(context, startTime);
|
||||
if (analysisResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(analysisResult.aiUsage);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
|
||||
const approachResult = await this.generateApproach(context);
|
||||
const approachResult = await this.generateApproach(context, startTime);
|
||||
if (approachResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(approachResult.aiUsage);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
|
||||
const considerationsResult = await this.generateCriticalConsiderations(context);
|
||||
const considerationsResult = await this.generateCriticalConsiderations(context, startTime);
|
||||
if (considerationsResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(considerationsResult.aiUsage);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
|
||||
// Phase 3: Tool-specific analysis
|
||||
// Phase 3: Tool-specific analysis with enhanced logging
|
||||
console.log('[AI-PIPELINE] Phase 3: Tool-specific analysis');
|
||||
|
||||
if (mode === 'workflow') {
|
||||
await this.processWorkflowMode(context, toolsData, completedTasks, failedTasks);
|
||||
const workflowResults = await this.processWorkflowMode(context, toolsData, completedTasks, failedTasks, startTime);
|
||||
completedTasks = workflowResults.completed;
|
||||
failedTasks = workflowResults.failed;
|
||||
} else {
|
||||
await this.processToolMode(context, completedTasks, failedTasks);
|
||||
const toolResults = await this.processToolMode(context, completedTasks, failedTasks, startTime);
|
||||
completedTasks = toolResults.completed;
|
||||
failedTasks = toolResults.failed;
|
||||
}
|
||||
|
||||
// Phase 4: Knowledge and finalization
|
||||
// Phase 4: Knowledge and finalization with enhanced logging
|
||||
console.log('[AI-PIPELINE] Phase 4: Knowledge synthesis');
|
||||
|
||||
const knowledgeResult = await this.selectBackgroundKnowledge(context);
|
||||
const knowledgeResult = await this.selectBackgroundKnowledge(context, startTime);
|
||||
if (knowledgeResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(knowledgeResult.aiUsage);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
|
||||
const finalResult = await this.generateFinalRecommendations(context);
|
||||
const finalResult = await this.generateFinalRecommendations(context, startTime);
|
||||
if (finalResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(finalResult.aiUsage);
|
||||
|
||||
// Build final recommendation
|
||||
const recommendation = this.buildRecommendation(context, mode, finalResult.content);
|
||||
|
||||
this.addAuditEntry(
|
||||
// AUDIT: Pipeline completion
|
||||
auditService.addEntry(
|
||||
'completion',
|
||||
'pipeline-end',
|
||||
{ completedTasks, failedTasks },
|
||||
{ finalRecommendation: !!recommendation, auditEntriesGenerated: auditService.getCurrentAuditTrail().length },
|
||||
{ completedTasks, failedTasks, totalTokensUsed: this.totalTokensUsed },
|
||||
{
|
||||
finalRecommendation: !!recommendation,
|
||||
auditEntriesGenerated: auditService.getCurrentAuditTrail().length,
|
||||
selectedToolsCount: context.selectedTools?.length || 0,
|
||||
backgroundKnowledgeCount: context.backgroundKnowledge?.length || 0
|
||||
},
|
||||
completedTasks > failedTasks ? 85 : 60,
|
||||
startTime,
|
||||
{ totalProcessingTimeMs: Date.now() - startTime }
|
||||
{
|
||||
totalProcessingTimeMs: Date.now() - startTime,
|
||||
aiModel: aiConfig.model,
|
||||
finalTokenUsage: this.totalTokensUsed,
|
||||
pipelineEfficiency: completedTasks / (completedTasks + failedTasks)
|
||||
}
|
||||
);
|
||||
|
||||
const processingStats = {
|
||||
@ -169,7 +233,9 @@ class AIPipeline {
|
||||
processingTimeMs: Date.now() - startTime,
|
||||
microTasksCompleted: completedTasks,
|
||||
microTasksFailed: failedTasks,
|
||||
contextContinuityUsed: true
|
||||
contextContinuityUsed: true,
|
||||
totalAITokensUsed: this.totalTokensUsed,
|
||||
auditEntriesGenerated: auditService.getCurrentAuditTrail().length
|
||||
};
|
||||
|
||||
console.log('[AI-PIPELINE] Pipeline completed successfully:', {
|
||||
@ -177,7 +243,9 @@ class AIPipeline {
|
||||
processingTimeMs: processingStats.processingTimeMs,
|
||||
completedTasks,
|
||||
failedTasks,
|
||||
finalItems: processingStats.finalSelectedItems
|
||||
finalItems: processingStats.finalSelectedItems,
|
||||
totalTokensUsed: this.totalTokensUsed,
|
||||
auditEntries: processingStats.auditEntriesGenerated
|
||||
});
|
||||
|
||||
// Finalize audit trail
|
||||
@ -193,6 +261,18 @@ class AIPipeline {
|
||||
|
||||
} catch (error) {
|
||||
console.error('[AI-PIPELINE] Pipeline failed:', error);
|
||||
|
||||
// AUDIT: Pipeline failure
|
||||
auditService.addEntry(
|
||||
'error',
|
||||
'pipeline-failure',
|
||||
{ userQuery: this.truncateForAudit(userQuery), mode },
|
||||
{ error: error.message, completedTasks, failedTasks },
|
||||
0,
|
||||
startTime,
|
||||
{ errorType: error.constructor.name, totalTokensUsed: this.totalTokensUsed }
|
||||
);
|
||||
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
@ -201,23 +281,63 @@ class AIPipeline {
|
||||
context: PipelineContext,
|
||||
toolsData: any,
|
||||
completedTasks: number,
|
||||
failedTasks: number
|
||||
): Promise<void> {
|
||||
failedTasks: number,
|
||||
pipelineStart: number
|
||||
): Promise<{ completed: number; failed: number }> {
|
||||
const phases = toolsData.phases || [];
|
||||
|
||||
// Select tools for each phase
|
||||
// Select tools for each phase with enhanced logging
|
||||
for (const phase of phases) {
|
||||
const phaseStart = Date.now();
|
||||
const phaseTools = context.filteredData.tools.filter((tool: any) =>
|
||||
tool && tool.phases && Array.isArray(tool.phases) && tool.phases.includes(phase.id)
|
||||
);
|
||||
|
||||
const selections = await toolSelector.selectToolsForPhase(context.userQuery, phase, phaseTools, context);
|
||||
|
||||
// AUDIT: Phase tool selection
|
||||
auditService.addEntry(
|
||||
'workflow-phase',
|
||||
'phase-tool-selection',
|
||||
{
|
||||
phaseId: phase.id,
|
||||
phaseName: phase.name,
|
||||
availableTools: phaseTools.map(t => t.name)
|
||||
},
|
||||
{
|
||||
selectedTools: selections.map(s => s.toolName),
|
||||
selectionCount: selections.length
|
||||
},
|
||||
selections.length > 0 ? 80 : 50,
|
||||
phaseStart,
|
||||
{
|
||||
phaseId: phase.id,
|
||||
availableToolsCount: phaseTools.length,
|
||||
selectedToolsCount: selections.length,
|
||||
microTaskType: 'phase-tool-selection'
|
||||
}
|
||||
);
|
||||
|
||||
selections.forEach((sel: any) => {
|
||||
const tool = phaseTools.find((t: any) => t && t.name === sel.toolName);
|
||||
if (tool) {
|
||||
const priority = this.derivePriorityFromScore(sel.taskRelevance);
|
||||
this.addToolToSelection(context, tool, phase.id, priority, sel.justification, sel.taskRelevance, sel.limitations);
|
||||
|
||||
// AUDIT: Individual tool selection reasoning
|
||||
auditService.addEntry(
|
||||
'tool-reasoning',
|
||||
'tool-added-to-phase',
|
||||
{ toolName: tool.name, phaseId: phase.id, taskRelevance: sel.taskRelevance },
|
||||
{ justification: sel.justification, limitations: sel.limitations },
|
||||
sel.taskRelevance || 70,
|
||||
phaseStart,
|
||||
{
|
||||
toolType: tool.type,
|
||||
priority,
|
||||
selectionReasoning: sel.justification
|
||||
}
|
||||
);
|
||||
}
|
||||
});
|
||||
|
||||
@ -225,26 +345,37 @@ class AIPipeline {
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
}
|
||||
|
||||
// Complete underrepresented phases
|
||||
await this.completeUnderrepresentedPhases(context, toolsData);
|
||||
// Complete underrepresented phases with enhanced logging
|
||||
const completionResult = await this.completeUnderrepresentedPhases(context, toolsData, pipelineStart);
|
||||
|
||||
return { completed: completedTasks, failed: failedTasks };
|
||||
}
|
||||
|
||||
private async processToolMode(context: PipelineContext, completedTasks: number, failedTasks: number): Promise<void> {
|
||||
private async processToolMode(
|
||||
context: PipelineContext,
|
||||
completedTasks: number,
|
||||
failedTasks: number,
|
||||
pipelineStart: number
|
||||
): Promise<{ completed: number; failed: number }> {
|
||||
const topTools = context.filteredData.tools.slice(0, 3);
|
||||
|
||||
for (let i = 0; i < topTools.length; i++) {
|
||||
const evaluationResult = await this.evaluateSpecificTool(context, topTools[i], i + 1);
|
||||
const evaluationResult = await this.evaluateSpecificTool(context, topTools[i], i + 1, pipelineStart);
|
||||
if (evaluationResult.success) completedTasks++; else failedTasks++;
|
||||
this.trackTokenUsage(evaluationResult.aiUsage);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
}
|
||||
|
||||
return { completed: completedTasks, failed: failedTasks };
|
||||
}
|
||||
|
||||
private async analyzeScenario(context: PipelineContext): Promise<MicroTaskResult> {
|
||||
private async analyzeScenario(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Scenario analysis');
|
||||
const taskStart = Date.now();
|
||||
const isWorkflow = context.mode === 'workflow';
|
||||
const prompt = getPrompt('scenarioAnalysis', isWorkflow, context.userQuery);
|
||||
|
||||
const result = await this.callMicroTaskAI(prompt, context, 400);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 400, 'scenario-analysis');
|
||||
|
||||
if (result.success) {
|
||||
if (isWorkflow) {
|
||||
@ -254,52 +385,109 @@ class AIPipeline {
|
||||
}
|
||||
|
||||
this.addToContextHistory(context, `${isWorkflow ? 'Szenario' : 'Problem'}-Analyse: ${result.content.slice(0, 200)}...`);
|
||||
|
||||
// AUDIT: Scenario analysis
|
||||
auditService.addAIDecision(
|
||||
'contextual-analysis',
|
||||
prompt,
|
||||
result.content,
|
||||
80,
|
||||
`Generated ${isWorkflow ? 'scenario' : 'problem'} analysis for user query`,
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'scenario-analysis',
|
||||
analysisType: isWorkflow ? 'scenario' : 'problem',
|
||||
contentLength: result.content.length,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async generateApproach(context: PipelineContext): Promise<MicroTaskResult> {
|
||||
private async generateApproach(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Investigation approach');
|
||||
const taskStart = Date.now();
|
||||
const isWorkflow = context.mode === 'workflow';
|
||||
const prompt = getPrompt('investigationApproach', isWorkflow, context.userQuery);
|
||||
|
||||
const result = await this.callMicroTaskAI(prompt, context, 400);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 400, 'investigation-approach');
|
||||
|
||||
if (result.success) {
|
||||
context.investigationApproach = result.content;
|
||||
this.addToContextHistory(context, `${isWorkflow ? 'Untersuchungs' : 'Lösungs'}ansatz: ${result.content.slice(0, 200)}...`);
|
||||
|
||||
// AUDIT: Investigation approach
|
||||
auditService.addAIDecision(
|
||||
'contextual-analysis',
|
||||
prompt,
|
||||
result.content,
|
||||
75,
|
||||
`Generated ${isWorkflow ? 'investigation' : 'solution'} approach`,
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'investigation-approach',
|
||||
approachType: isWorkflow ? 'investigation' : 'solution',
|
||||
contentLength: result.content.length,
|
||||
contextHistoryLength: context.contextHistory.length,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async generateCriticalConsiderations(context: PipelineContext): Promise<MicroTaskResult> {
|
||||
private async generateCriticalConsiderations(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Critical considerations');
|
||||
const taskStart = Date.now();
|
||||
const isWorkflow = context.mode === 'workflow';
|
||||
const prompt = getPrompt('criticalConsiderations', isWorkflow, context.userQuery);
|
||||
|
||||
const result = await this.callMicroTaskAI(prompt, context, 350);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 350, 'critical-considerations');
|
||||
|
||||
if (result.success) {
|
||||
context.criticalConsiderations = result.content;
|
||||
this.addToContextHistory(context, `Kritische Überlegungen: ${result.content.slice(0, 200)}...`);
|
||||
|
||||
// AUDIT: Critical considerations
|
||||
auditService.addAIDecision(
|
||||
'contextual-analysis',
|
||||
prompt,
|
||||
result.content,
|
||||
70,
|
||||
'Generated critical considerations and constraints',
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'critical-considerations',
|
||||
contentLength: result.content.length,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async evaluateSpecificTool(context: PipelineContext, tool: any, rank: number): Promise<MicroTaskResult> {
|
||||
private async evaluateSpecificTool(
|
||||
context: PipelineContext,
|
||||
tool: any,
|
||||
rank: number,
|
||||
pipelineStart: number
|
||||
): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Tool evaluation for:', tool.name);
|
||||
const taskStart = Date.now();
|
||||
const existingSelection = context.selectedTools?.find((st: any) => st.tool && st.tool.name === tool.name);
|
||||
const taskRelevance = existingSelection?.taskRelevance || 70;
|
||||
const priority = this.derivePriorityFromScore(taskRelevance);
|
||||
|
||||
const prompt = getPrompt('toolEvaluation', context.userQuery, tool, rank, taskRelevance);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 1000);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 1000, 'tool-evaluation');
|
||||
|
||||
if (result.success) {
|
||||
const evaluation = this.safeParseJSON(result.content, {
|
||||
// FIXED: Use centralized JSON parsing
|
||||
const evaluation = JSONParser.safeParseJSON(result.content, {
|
||||
detailed_explanation: 'Evaluation failed',
|
||||
implementation_approach: '',
|
||||
pros: [],
|
||||
@ -315,13 +503,35 @@ class AIPipeline {
|
||||
task_relevance: taskRelevance
|
||||
}
|
||||
}, 'evaluation', priority, evaluation.detailed_explanation, taskRelevance, evaluation.limitations);
|
||||
|
||||
// AUDIT: Tool evaluation
|
||||
auditService.addAIDecision(
|
||||
'tool-evaluation',
|
||||
prompt,
|
||||
result.content,
|
||||
taskRelevance,
|
||||
`Evaluated tool ${tool.name} for ${context.mode} mode`,
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'tool-evaluation',
|
||||
toolName: tool.name,
|
||||
toolType: tool.type,
|
||||
rank,
|
||||
taskRelevance,
|
||||
evaluationParsed: !!evaluation.detailed_explanation,
|
||||
prosCount: evaluation.pros?.length || 0,
|
||||
limitationsCount: evaluation.limitations?.length || 0,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async selectBackgroundKnowledge(context: PipelineContext): Promise<MicroTaskResult> {
|
||||
private async selectBackgroundKnowledge(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Background knowledge selection');
|
||||
const taskStart = Date.now();
|
||||
const availableConcepts = context.filteredData.concepts;
|
||||
|
||||
if (availableConcepts.length === 0) {
|
||||
@ -335,10 +545,11 @@ class AIPipeline {
|
||||
|
||||
const selectedToolNames = context.selectedTools?.map((st: any) => st.tool && st.tool.name).filter(Boolean) || [];
|
||||
const prompt = getPrompt('backgroundKnowledgeSelection', context.userQuery, context.mode, selectedToolNames, availableConcepts);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 700);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 700, 'background-knowledge');
|
||||
|
||||
if (result.success) {
|
||||
const selections = this.safeParseJSON(result.content, []);
|
||||
// FIXED: Use centralized JSON parsing
|
||||
const selections = JSONParser.safeParseJSON(result.content, []);
|
||||
|
||||
if (Array.isArray(selections)) {
|
||||
context.backgroundKnowledge = selections.filter((sel: any) =>
|
||||
@ -347,21 +558,66 @@ class AIPipeline {
|
||||
concept: availableConcepts.find((c: any) => c.name === sel.conceptName),
|
||||
relevance: sel.relevance
|
||||
}));
|
||||
|
||||
// AUDIT: Background knowledge selection
|
||||
auditService.addEntry(
|
||||
'knowledge-synthesis',
|
||||
'concept-selection',
|
||||
{
|
||||
availableConcepts: availableConcepts.map(c => c.name),
|
||||
selectedToolsContext: selectedToolNames
|
||||
},
|
||||
{
|
||||
selectedConcepts: context.backgroundKnowledge.map(bk => bk.concept.name),
|
||||
selectionReasonings: context.backgroundKnowledge.map(bk => bk.relevance)
|
||||
},
|
||||
context.backgroundKnowledge.length > 0 ? 75 : 50,
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'background-knowledge',
|
||||
availableConceptsCount: availableConcepts.length,
|
||||
selectedConceptsCount: context.backgroundKnowledge.length,
|
||||
selectionRatio: context.backgroundKnowledge.length / availableConcepts.length,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async generateFinalRecommendations(context: PipelineContext): Promise<MicroTaskResult> {
|
||||
private async generateFinalRecommendations(context: PipelineContext, pipelineStart: number): Promise<MicroTaskResult> {
|
||||
console.log('[AI-PIPELINE] Micro-task: Final recommendations');
|
||||
const taskStart = Date.now();
|
||||
const selectedToolNames = context.selectedTools?.map((st: any) => st.tool && st.tool.name).filter(Boolean) || [];
|
||||
const prompt = getPrompt('finalRecommendations', context.mode === 'workflow', context.userQuery, selectedToolNames);
|
||||
|
||||
return this.callMicroTaskAI(prompt, context, 350);
|
||||
const result = await this.callMicroTaskAI(prompt, context, 350, 'final-recommendations');
|
||||
|
||||
if (result.success) {
|
||||
// AUDIT: Final recommendations
|
||||
auditService.addAIDecision(
|
||||
'synthesis',
|
||||
prompt,
|
||||
result.content,
|
||||
85,
|
||||
`Generated final ${context.mode} recommendations`,
|
||||
taskStart,
|
||||
{
|
||||
microTaskType: 'final-recommendations',
|
||||
mode: context.mode,
|
||||
selectedToolsCount: selectedToolNames.length,
|
||||
contentLength: result.content.length,
|
||||
...result.aiUsage
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
return result;
|
||||
}
|
||||
|
||||
private async completeUnderrepresentedPhases(context: PipelineContext, toolsData: any): Promise<void> {
|
||||
private async completeUnderrepresentedPhases(context: PipelineContext, toolsData: any, pipelineStart: number): Promise<void> {
|
||||
const phases = toolsData.phases || [];
|
||||
const selectedPhases = new Map<string, number>();
|
||||
|
||||
@ -382,13 +638,34 @@ class AIPipeline {
|
||||
|
||||
console.log('[AI-PIPELINE] Completing underrepresented phases:', underrepresentedPhases.map((p: any) => p.id).join(', '));
|
||||
|
||||
// AUDIT: Phase completion start
|
||||
auditService.addEntry(
|
||||
'phase-completion',
|
||||
'underrepresented-phases-detected',
|
||||
{
|
||||
underrepresentedPhases: underrepresentedPhases.map(p => p.id),
|
||||
currentPhaseDistribution: Array.from(selectedPhases.entries())
|
||||
},
|
||||
{
|
||||
phasesToComplete: underrepresentedPhases.length,
|
||||
completionStrategy: 'semantic-search'
|
||||
},
|
||||
70,
|
||||
pipelineStart,
|
||||
{
|
||||
totalPhases: phases.length,
|
||||
adequatelyRepresented: phases.length - underrepresentedPhases.length,
|
||||
completionMethod: 'semantic-phase-search'
|
||||
}
|
||||
);
|
||||
|
||||
for (const phase of underrepresentedPhases) {
|
||||
await this.completePhaseWithSemanticSearch(context, phase, toolsData);
|
||||
await this.completePhaseWithSemanticSearch(context, phase, toolsData, pipelineStart);
|
||||
await this.delay(this.config.microTaskDelay);
|
||||
}
|
||||
}
|
||||
|
||||
private async completePhaseWithSemanticSearch(context: PipelineContext, phase: any, toolsData: any): Promise<void> {
|
||||
private async completePhaseWithSemanticSearch(context: PipelineContext, phase: any, toolsData: any, pipelineStart: number): Promise<void> {
|
||||
const phaseStart = Date.now();
|
||||
const phaseQuery = `forensic ${phase.name.toLowerCase()} tools methods`;
|
||||
|
||||
@ -397,6 +674,19 @@ class AIPipeline {
|
||||
try {
|
||||
const phaseResults = await embeddingsService.findSimilar(phaseQuery, 20, 0.2);
|
||||
|
||||
// AUDIT: Embeddings search for phase completion
|
||||
auditService.addEmbeddingsSearch(
|
||||
phaseQuery,
|
||||
phaseResults,
|
||||
0.2,
|
||||
phaseStart,
|
||||
{
|
||||
phaseId: phase.id,
|
||||
phaseName: phase.name,
|
||||
completionPurpose: 'underrepresented-phase-enhancement'
|
||||
}
|
||||
);
|
||||
|
||||
if (phaseResults.length === 0) {
|
||||
console.log('[AI-PIPELINE] No semantic results for phase:', phase.id);
|
||||
return;
|
||||
@ -422,7 +712,7 @@ class AIPipeline {
|
||||
return;
|
||||
}
|
||||
|
||||
// Add tools with justification
|
||||
// Add tools with justification and audit each addition
|
||||
for (const tool of phaseTools) {
|
||||
const justification = `Nachträglich hinzugefügt zur Vervollständigung der ${phase.name}-Phase. Die ursprüngliche KI-Auswahl war zu spezifisch und hat wichtige Tools für diese Phase übersehen.`;
|
||||
|
||||
@ -436,11 +726,40 @@ class AIPipeline {
|
||||
['Nachträgliche Ergänzung via semantische Phasensuche']
|
||||
);
|
||||
|
||||
// AUDIT: Phase completion tool addition
|
||||
auditService.addPhaseCompletion(
|
||||
phase.id,
|
||||
[tool.name],
|
||||
justification,
|
||||
phaseStart,
|
||||
{
|
||||
toolName: tool.name,
|
||||
toolType: tool.type,
|
||||
semanticSimilarity: phaseResults.find(r => r.name === tool.name)?.similarity,
|
||||
completionReason: 'underrepresented-phase',
|
||||
originalSelectionMissed: true
|
||||
}
|
||||
);
|
||||
|
||||
console.log('[AI-PIPELINE] Added phase completion tool:', tool.name);
|
||||
}
|
||||
|
||||
} catch (error) {
|
||||
console.error('[AI-PIPELINE] Phase completion failed for:', phase.id, error);
|
||||
|
||||
// AUDIT: Phase completion failure
|
||||
auditService.addEntry(
|
||||
'phase-completion',
|
||||
'completion-failed',
|
||||
{ phaseId: phase.id, error: error.message },
|
||||
{ success: false },
|
||||
20,
|
||||
phaseStart,
|
||||
{
|
||||
errorType: error.constructor.name,
|
||||
phaseId: phase.id
|
||||
}
|
||||
);
|
||||
}
|
||||
}
|
||||
|
||||
@ -476,6 +795,18 @@ class AIPipeline {
|
||||
st.limitations || []
|
||||
);
|
||||
|
||||
// AUDIT: Confidence calculation for each tool
|
||||
auditService.addConfidenceCalculation(
|
||||
st.tool.name,
|
||||
confidence,
|
||||
Date.now(),
|
||||
{
|
||||
phase: st.phase,
|
||||
priority: st.priority,
|
||||
toolType: st.tool.type
|
||||
}
|
||||
);
|
||||
|
||||
return {
|
||||
name: st.tool.name,
|
||||
type: st.tool.type,
|
||||
@ -508,6 +839,17 @@ class AIPipeline {
|
||||
st.limitations || []
|
||||
);
|
||||
|
||||
// AUDIT: Confidence calculation for each tool
|
||||
auditService.addConfidenceCalculation(
|
||||
st.tool.name,
|
||||
confidence,
|
||||
Date.now(),
|
||||
{
|
||||
rank: st.tool.evaluation?.rank || 1,
|
||||
toolType: st.tool.type
|
||||
}
|
||||
);
|
||||
|
||||
return {
|
||||
name: st.tool.name,
|
||||
type: st.tool.type,
|
||||
@ -532,7 +874,12 @@ class AIPipeline {
|
||||
}
|
||||
|
||||
// Helper methods
|
||||
private async callMicroTaskAI(prompt: string, context: PipelineContext, maxTokens: number = 500): Promise<MicroTaskResult> {
|
||||
private async callMicroTaskAI(
|
||||
prompt: string,
|
||||
context: PipelineContext,
|
||||
maxTokens: number = 500,
|
||||
taskType: string = 'micro-task'
|
||||
): Promise<MicroTaskResult> {
|
||||
const startTime = Date.now();
|
||||
|
||||
let contextPrompt = prompt;
|
||||
@ -549,15 +896,16 @@ class AIPipeline {
|
||||
const response = await aiService.callMicroTaskAI(contextPrompt, maxTokens);
|
||||
|
||||
return {
|
||||
taskType: 'micro-task',
|
||||
taskType,
|
||||
content: response.content,
|
||||
processingTimeMs: Date.now() - startTime,
|
||||
success: true
|
||||
success: true,
|
||||
aiUsage: response.usage
|
||||
};
|
||||
|
||||
} catch (error) {
|
||||
return {
|
||||
taskType: 'micro-task',
|
||||
taskType,
|
||||
content: '',
|
||||
processingTimeMs: Date.now() - startTime,
|
||||
success: false,
|
||||
@ -608,48 +956,21 @@ class AIPipeline {
|
||||
return 'low';
|
||||
}
|
||||
|
||||
private safeParseJSON(jsonString: string, fallback: any = null): any {
|
||||
try {
|
||||
let cleaned = jsonString.trim();
|
||||
private truncateForAudit(text: string, maxLength: number = 200): string {
|
||||
if (typeof text !== 'string') return String(text);
|
||||
if (text.length <= maxLength) return text;
|
||||
return text.slice(0, maxLength) + '...[audit-truncated]';
|
||||
}
|
||||
|
||||
// Remove code block markers
|
||||
const jsonBlockPatterns = [
|
||||
/```json\s*([\s\S]*?)\s*```/i,
|
||||
/```\s*([\s\S]*?)\s*```/i,
|
||||
/\{[\s\S]*\}/,
|
||||
];
|
||||
|
||||
for (const pattern of jsonBlockPatterns) {
|
||||
const match = cleaned.match(pattern);
|
||||
if (match) {
|
||||
cleaned = match[1] || match[0];
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
return JSON.parse(cleaned);
|
||||
|
||||
} catch (error) {
|
||||
console.warn('[AI-PIPELINE] JSON parsing failed:', error.message);
|
||||
return fallback;
|
||||
private trackTokenUsage(usage?: { promptTokens?: number; completionTokens?: number; totalTokens?: number }): void {
|
||||
if (usage?.totalTokens) {
|
||||
this.totalTokensUsed += usage.totalTokens;
|
||||
}
|
||||
}
|
||||
|
||||
private async delay(ms: number): Promise<void> {
|
||||
return new Promise(resolve => setTimeout(resolve, ms));
|
||||
}
|
||||
|
||||
private addAuditEntry(
|
||||
phase: string,
|
||||
action: string,
|
||||
input: any,
|
||||
output: any,
|
||||
confidence: number,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
auditService.addEntry(phase, action, input, output, confidence, startTime, metadata);
|
||||
}
|
||||
}
|
||||
|
||||
export const aiPipeline = new AIPipeline();
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
// src/utils/auditService.ts - Refactored
|
||||
// src/utils/auditService.ts - Enhanced for forensic-grade transparency
|
||||
import 'dotenv/config';
|
||||
|
||||
function env(key: string, fallback: string | undefined = undefined): string | undefined {
|
||||
@ -19,7 +19,29 @@ export interface AuditEntry {
|
||||
output: any;
|
||||
confidence: number;
|
||||
processingTimeMs: number;
|
||||
metadata: Record<string, any>;
|
||||
metadata: {
|
||||
aiModel?: string;
|
||||
aiParameters?: any;
|
||||
promptTokens?: number;
|
||||
completionTokens?: number;
|
||||
toolsDataHash?: string;
|
||||
embeddingsUsed?: boolean;
|
||||
selectionMethod?: string;
|
||||
microTaskType?: string;
|
||||
confidenceFactors?: string[];
|
||||
reasoning?: string;
|
||||
aiPrompt?: string;
|
||||
aiResponse?: string;
|
||||
toolSelectionCriteria?: string;
|
||||
availableToolsCount?: number;
|
||||
selectedToolsCount?: number;
|
||||
phaseId?: string;
|
||||
toolsAdded?: string[];
|
||||
completionReasoning?: string;
|
||||
similarityScores?: Record<string, number>;
|
||||
contextLength?: number;
|
||||
[key: string]: any;
|
||||
};
|
||||
}
|
||||
|
||||
interface AuditConfig {
|
||||
@ -87,6 +109,135 @@ class AuditService {
|
||||
console.log(`[AUDIT-SERVICE] ${phase}/${action}: ${confidence}% confidence, ${entry.processingTimeMs}ms`);
|
||||
}
|
||||
|
||||
// NEW: Specialized audit methods for forensic transparency
|
||||
addAIDecision(
|
||||
phase: string,
|
||||
aiPrompt: string,
|
||||
aiResponse: string,
|
||||
confidence: number,
|
||||
reasoning: string,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
this.addEntry(
|
||||
phase,
|
||||
'ai-decision',
|
||||
{ prompt: this.truncateForAudit(aiPrompt) },
|
||||
{ response: this.truncateForAudit(aiResponse) },
|
||||
confidence,
|
||||
startTime,
|
||||
{
|
||||
...metadata,
|
||||
reasoning,
|
||||
aiPrompt: this.config.detailLevel === 'verbose' ? aiPrompt : this.truncateForAudit(aiPrompt),
|
||||
aiResponse: this.config.detailLevel === 'verbose' ? aiResponse : this.truncateForAudit(aiResponse)
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
addToolSelection(
|
||||
selectedTools: string[],
|
||||
availableTools: string[],
|
||||
selectionMethod: string,
|
||||
confidence: number,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
this.addEntry(
|
||||
'tool-selection',
|
||||
'selection-decision',
|
||||
{ availableTools: availableTools.length > 10 ? availableTools.slice(0, 10) : availableTools },
|
||||
{ selectedTools },
|
||||
confidence,
|
||||
startTime,
|
||||
{
|
||||
...metadata,
|
||||
selectionMethod,
|
||||
availableToolsCount: availableTools.length,
|
||||
selectedToolsCount: selectedTools.length,
|
||||
toolSelectionCriteria: `${selectionMethod} selection from ${availableTools.length} available tools`
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
addPhaseCompletion(
|
||||
phaseId: string,
|
||||
toolsAdded: string[],
|
||||
completionReasoning: string,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
this.addEntry(
|
||||
'phase-completion',
|
||||
'phase-enhancement',
|
||||
{ phaseId, underrepresentedPhase: true },
|
||||
{ toolsAdded },
|
||||
75, // Default confidence for phase completion
|
||||
startTime,
|
||||
{
|
||||
...metadata,
|
||||
phaseId,
|
||||
toolsAdded,
|
||||
completionReasoning,
|
||||
enhancementType: 'semantic-phase-completion'
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
addEmbeddingsSearch(
|
||||
query: string,
|
||||
similarResults: any[],
|
||||
threshold: number,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
const similarityScores = similarResults.reduce((acc, result) => {
|
||||
acc[result.name] = result.similarity;
|
||||
return acc;
|
||||
}, {} as Record<string, number>);
|
||||
|
||||
this.addEntry(
|
||||
'embeddings',
|
||||
'similarity-search',
|
||||
{ query: this.truncateForAudit(query), threshold },
|
||||
{ resultsCount: similarResults.length, topResults: similarResults.slice(0, 5).map(r => r.name) },
|
||||
similarResults.length > 0 ? 85 : 50,
|
||||
startTime,
|
||||
{
|
||||
...metadata,
|
||||
embeddingsUsed: true,
|
||||
similarityScores,
|
||||
searchThreshold: threshold,
|
||||
totalMatches: similarResults.length
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
addConfidenceCalculation(
|
||||
toolName: string,
|
||||
confidenceBreakdown: any,
|
||||
startTime: number,
|
||||
metadata: Record<string, any> = {}
|
||||
): void {
|
||||
this.addEntry(
|
||||
'confidence-scoring',
|
||||
'tool-confidence',
|
||||
{ toolName },
|
||||
{ confidenceBreakdown },
|
||||
confidenceBreakdown.overall || 50,
|
||||
startTime,
|
||||
{
|
||||
...metadata,
|
||||
confidenceFactors: [
|
||||
...(confidenceBreakdown.strengthIndicators || []),
|
||||
...(confidenceBreakdown.uncertaintyFactors || [])
|
||||
],
|
||||
semanticRelevance: confidenceBreakdown.semanticRelevance,
|
||||
taskSuitability: confidenceBreakdown.taskSuitability
|
||||
}
|
||||
);
|
||||
}
|
||||
|
||||
getCurrentAuditTrail(): AuditEntry[] {
|
||||
return [...this.activeAuditTrail];
|
||||
}
|
||||
@ -135,6 +286,12 @@ class AuditService {
|
||||
return data;
|
||||
}
|
||||
|
||||
private truncateForAudit(text: string, maxLength: number = 300): string {
|
||||
if (typeof text !== 'string') return String(text);
|
||||
if (text.length <= maxLength) return text;
|
||||
return text.slice(0, maxLength) + '...[truncated for audit]';
|
||||
}
|
||||
|
||||
isEnabled(): boolean {
|
||||
return this.config.enabled;
|
||||
}
|
||||
@ -143,7 +300,7 @@ class AuditService {
|
||||
return { ...this.config };
|
||||
}
|
||||
|
||||
// Statistics and analysis methods
|
||||
// Statistics and analysis methods (enhanced)
|
||||
getAuditStatistics(auditTrail: AuditEntry[]): {
|
||||
totalTime: number;
|
||||
avgConfidence: number;
|
||||
@ -151,6 +308,14 @@ class AuditService {
|
||||
highConfidenceSteps: number;
|
||||
lowConfidenceSteps: number;
|
||||
phaseBreakdown: Record<string, { count: number; avgConfidence: number; totalTime: number }>;
|
||||
aiDecisionCount: number;
|
||||
embeddingsUsageCount: number;
|
||||
toolSelectionCount: number;
|
||||
qualityMetrics: {
|
||||
avgProcessingTime: number;
|
||||
confidenceDistribution: { high: number; medium: number; low: number };
|
||||
aiTransparency: number;
|
||||
};
|
||||
} {
|
||||
if (!auditTrail || auditTrail.length === 0) {
|
||||
return {
|
||||
@ -159,7 +324,15 @@ class AuditService {
|
||||
stepCount: 0,
|
||||
highConfidenceSteps: 0,
|
||||
lowConfidenceSteps: 0,
|
||||
phaseBreakdown: {}
|
||||
phaseBreakdown: {},
|
||||
aiDecisionCount: 0,
|
||||
embeddingsUsageCount: 0,
|
||||
toolSelectionCount: 0,
|
||||
qualityMetrics: {
|
||||
avgProcessingTime: 0,
|
||||
confidenceDistribution: { high: 0, medium: 0, low: 0 },
|
||||
aiTransparency: 0
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
@ -171,6 +344,12 @@ class AuditService {
|
||||
|
||||
const highConfidenceSteps = auditTrail.filter(entry => (entry.confidence || 0) >= 80).length;
|
||||
const lowConfidenceSteps = auditTrail.filter(entry => (entry.confidence || 0) < 60).length;
|
||||
const mediumConfidenceSteps = auditTrail.length - highConfidenceSteps - lowConfidenceSteps;
|
||||
|
||||
// Enhanced metrics
|
||||
const aiDecisionCount = auditTrail.filter(entry => entry.action === 'ai-decision').length;
|
||||
const embeddingsUsageCount = auditTrail.filter(entry => entry.metadata?.embeddingsUsed).length;
|
||||
const toolSelectionCount = auditTrail.filter(entry => entry.action === 'selection-decision').length;
|
||||
|
||||
// Phase breakdown
|
||||
const phaseBreakdown: Record<string, { count: number; avgConfidence: number; totalTime: number }> = {};
|
||||
@ -197,13 +376,29 @@ class AuditService {
|
||||
}
|
||||
});
|
||||
|
||||
const avgProcessingTime = auditTrail.length > 0 ? totalTime / auditTrail.length : 0;
|
||||
const aiTransparency = auditTrail.length > 0 ?
|
||||
(auditTrail.filter(entry => entry.metadata?.aiPrompt || entry.metadata?.reasoning).length / auditTrail.length) * 100 : 0;
|
||||
|
||||
return {
|
||||
totalTime,
|
||||
avgConfidence,
|
||||
stepCount: auditTrail.length,
|
||||
highConfidenceSteps,
|
||||
lowConfidenceSteps,
|
||||
phaseBreakdown
|
||||
phaseBreakdown,
|
||||
aiDecisionCount,
|
||||
embeddingsUsageCount,
|
||||
toolSelectionCount,
|
||||
qualityMetrics: {
|
||||
avgProcessingTime,
|
||||
confidenceDistribution: {
|
||||
high: highConfidenceSteps,
|
||||
medium: mediumConfidenceSteps,
|
||||
low: lowConfidenceSteps
|
||||
},
|
||||
aiTransparency: Math.round(aiTransparency)
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
@ -238,6 +433,15 @@ class AuditService {
|
||||
}
|
||||
});
|
||||
|
||||
// Enhanced validation for audit quality
|
||||
if (entry.action === 'ai-decision' && !entry.metadata?.aiPrompt && !entry.metadata?.reasoning) {
|
||||
warnings.push(`Entry ${index}: AI decision lacks transparency (no prompt or reasoning)`);
|
||||
}
|
||||
|
||||
if (entry.action === 'selection-decision' && !entry.metadata?.selectionMethod) {
|
||||
warnings.push(`Entry ${index}: Tool selection lacks methodology info`);
|
||||
}
|
||||
|
||||
// Data type validation
|
||||
if (typeof entry.confidence !== 'number' || entry.confidence < 0 || entry.confidence > 100) {
|
||||
warnings.push(`Entry ${index} has invalid confidence value: ${entry.confidence}`);
|
||||
|
||||
@ -1,5 +1,5 @@
|
||||
// src/utils/confidenceScoring.ts
|
||||
import { isToolHosted } from './toolHelpers.js';
|
||||
import { isToolHosted } from './clientUtils.js';
|
||||
import 'dotenv/config';
|
||||
|
||||
export interface ConfidenceMetrics {
|
||||
|
||||
@ -1,4 +1,4 @@
|
||||
// src/utils/jsonUtils.ts
|
||||
// src/utils/jsonUtils.ts - Centralized JSON parsing and utilities
|
||||
export class JSONParser {
|
||||
static safeParseJSON(jsonString: string, fallback: any = null): any {
|
||||
try {
|
||||
@ -129,4 +129,246 @@ export class JSONParser {
|
||||
|
||||
return { selectedTools, selectedConcepts };
|
||||
}
|
||||
|
||||
static secureParseJSON(jsonString: string, maxSize: number = 10 * 1024 * 1024): any {
|
||||
if (typeof jsonString !== 'string') {
|
||||
throw new Error('Input must be a string');
|
||||
}
|
||||
|
||||
if (jsonString.length > maxSize) {
|
||||
throw new Error(`JSON string too large (${jsonString.length} bytes, max ${maxSize})`);
|
||||
}
|
||||
|
||||
// Security checks for potentially malicious content
|
||||
const suspiciousPatterns = [
|
||||
/<script/i,
|
||||
/javascript:/i,
|
||||
/eval\(/i,
|
||||
/function\s*\(/i,
|
||||
/__proto__/i,
|
||||
/constructor/i
|
||||
];
|
||||
|
||||
for (const pattern of suspiciousPatterns) {
|
||||
if (pattern.test(jsonString)) {
|
||||
throw new Error('Potentially malicious content detected in JSON');
|
||||
}
|
||||
}
|
||||
|
||||
try {
|
||||
const parsed = JSON.parse(jsonString);
|
||||
|
||||
// Validate basic structure
|
||||
if (typeof parsed !== 'object' || parsed === null) {
|
||||
throw new Error('JSON must be an object');
|
||||
}
|
||||
|
||||
return parsed;
|
||||
} catch (error) {
|
||||
if (error instanceof SyntaxError) {
|
||||
throw new Error(`Invalid JSON syntax: ${error.message}`);
|
||||
}
|
||||
throw error;
|
||||
}
|
||||
}
|
||||
|
||||
static sanitizeForAudit(obj: any, maxDepth: number = 5, currentDepth: number = 0): any {
|
||||
if (currentDepth >= maxDepth) {
|
||||
return '[Max depth reached]';
|
||||
}
|
||||
|
||||
if (obj === null || obj === undefined) {
|
||||
return obj;
|
||||
}
|
||||
|
||||
if (typeof obj === 'string') {
|
||||
// Sanitize strings that might contain sensitive data
|
||||
if (obj.length > 500) {
|
||||
return obj.slice(0, 500) + '...[truncated]';
|
||||
}
|
||||
// Remove potential code injection patterns
|
||||
return obj.replace(/<script[\s\S]*?<\/script>/gi, '[script removed]');
|
||||
}
|
||||
|
||||
if (typeof obj === 'number' || typeof obj === 'boolean') {
|
||||
return obj;
|
||||
}
|
||||
|
||||
if (Array.isArray(obj)) {
|
||||
if (obj.length > 20) {
|
||||
return [
|
||||
...obj.slice(0, 20).map(item => this.sanitizeForAudit(item, maxDepth, currentDepth + 1)),
|
||||
`...[${obj.length - 20} more items]`
|
||||
];
|
||||
}
|
||||
return obj.map(item => this.sanitizeForAudit(item, maxDepth, currentDepth + 1));
|
||||
}
|
||||
|
||||
if (typeof obj === 'object') {
|
||||
const keys = Object.keys(obj);
|
||||
if (keys.length > 50) {
|
||||
const sanitized: any = {};
|
||||
keys.slice(0, 50).forEach(key => {
|
||||
sanitized[key] = this.sanitizeForAudit(obj[key], maxDepth, currentDepth + 1);
|
||||
});
|
||||
sanitized['[truncated]'] = `${keys.length - 50} more properties`;
|
||||
return sanitized;
|
||||
}
|
||||
|
||||
const sanitized: any = {};
|
||||
keys.forEach(key => {
|
||||
// Skip potential dangerous properties
|
||||
if (['__proto__', 'constructor', 'prototype'].includes(key)) {
|
||||
return;
|
||||
}
|
||||
sanitized[key] = this.sanitizeForAudit(obj[key], maxDepth, currentDepth + 1);
|
||||
});
|
||||
return sanitized;
|
||||
}
|
||||
|
||||
return String(obj);
|
||||
}
|
||||
|
||||
static validateAuditExportStructure(data: any): { isValid: boolean; errors: string[] } {
|
||||
const errors: string[] = [];
|
||||
|
||||
if (!data || typeof data !== 'object') {
|
||||
errors.push('Export data must be an object');
|
||||
return { isValid: false, errors };
|
||||
}
|
||||
|
||||
// Check required top-level properties
|
||||
const requiredProps = ['metadata', 'recommendation', 'auditTrail'];
|
||||
for (const prop of requiredProps) {
|
||||
if (!(prop in data)) {
|
||||
errors.push(`Missing required property: ${prop}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Validate metadata
|
||||
if (data.metadata && typeof data.metadata === 'object') {
|
||||
const requiredMetadataProps = ['timestamp', 'version', 'userQuery', 'mode'];
|
||||
for (const prop of requiredMetadataProps) {
|
||||
if (!(prop in data.metadata)) {
|
||||
errors.push(`Missing required metadata property: ${prop}`);
|
||||
}
|
||||
}
|
||||
} else {
|
||||
errors.push('Invalid metadata structure');
|
||||
}
|
||||
|
||||
// Validate audit trail
|
||||
if (!Array.isArray(data.auditTrail)) {
|
||||
errors.push('auditTrail must be an array');
|
||||
} else {
|
||||
data.auditTrail.forEach((entry: any, index: number) => {
|
||||
if (!entry || typeof entry !== 'object') {
|
||||
errors.push(`Audit entry ${index} is not a valid object`);
|
||||
return;
|
||||
}
|
||||
|
||||
const requiredEntryProps = ['timestamp', 'phase', 'action', 'confidence', 'processingTimeMs'];
|
||||
for (const prop of requiredEntryProps) {
|
||||
if (!(prop in entry)) {
|
||||
errors.push(`Audit entry ${index} missing required property: ${prop}`);
|
||||
}
|
||||
}
|
||||
});
|
||||
}
|
||||
|
||||
return {
|
||||
isValid: errors.length === 0,
|
||||
errors
|
||||
};
|
||||
}
|
||||
|
||||
static prepareAuditExport(
|
||||
recommendation: any,
|
||||
userQuery: string,
|
||||
mode: string,
|
||||
auditTrail: any[] = [],
|
||||
additionalMetadata: any = {}
|
||||
): any {
|
||||
return {
|
||||
metadata: {
|
||||
timestamp: new Date().toISOString(),
|
||||
version: "1.0",
|
||||
userQuery: userQuery.slice(0, 1000), // Truncate for security
|
||||
mode,
|
||||
exportedBy: 'ForensicPathways',
|
||||
toolsDataHash: additionalMetadata.toolsDataHash || 'unknown',
|
||||
aiModel: additionalMetadata.aiModel || 'unknown',
|
||||
aiParameters: additionalMetadata.aiParameters || {},
|
||||
processingStats: additionalMetadata.processingStats || {}
|
||||
},
|
||||
recommendation: this.sanitizeForAudit(recommendation, 6),
|
||||
auditTrail: auditTrail.map(entry => this.sanitizeForAudit(entry, 4)),
|
||||
rawContext: {
|
||||
selectedTools: additionalMetadata.selectedTools || [],
|
||||
backgroundKnowledge: additionalMetadata.backgroundKnowledge || [],
|
||||
contextHistory: additionalMetadata.contextHistory || [],
|
||||
embeddingsSimilarities: additionalMetadata.embeddingsSimilarities || {}
|
||||
}
|
||||
};
|
||||
}
|
||||
|
||||
static validateUploadedAnalysis(data: any): { isValid: boolean; issues: string[]; warnings: string[] } {
|
||||
const issues: string[] = [];
|
||||
const warnings: string[] = [];
|
||||
|
||||
// Basic structure validation
|
||||
const structureValidation = this.validateAuditExportStructure(data);
|
||||
if (!structureValidation.isValid) {
|
||||
issues.push(...structureValidation.errors);
|
||||
return { isValid: false, issues, warnings };
|
||||
}
|
||||
|
||||
// Additional validation for uploaded content
|
||||
if (data.metadata) {
|
||||
// Check timestamp validity
|
||||
const timestamp = new Date(data.metadata.timestamp);
|
||||
if (isNaN(timestamp.getTime())) {
|
||||
warnings.push('Invalid timestamp in metadata');
|
||||
} else {
|
||||
const age = Date.now() - timestamp.getTime();
|
||||
const maxAge = 30 * 24 * 60 * 60 * 1000; // 30 days
|
||||
if (age > maxAge) {
|
||||
warnings.push(`Analysis is ${Math.floor(age / (24 * 60 * 60 * 1000))} days old`);
|
||||
}
|
||||
}
|
||||
|
||||
// Validate mode
|
||||
if (!['workflow', 'tool'].includes(data.metadata.mode)) {
|
||||
warnings.push(`Unknown analysis mode: ${data.metadata.mode}`);
|
||||
}
|
||||
}
|
||||
|
||||
// Validate audit trail quality
|
||||
if (Array.isArray(data.auditTrail)) {
|
||||
const aiDecisions = data.auditTrail.filter(e => e.action === 'ai-decision').length;
|
||||
const toolSelections = data.auditTrail.filter(e => e.action === 'selection-decision').length;
|
||||
|
||||
if (aiDecisions === 0) {
|
||||
warnings.push('No AI decisions found in audit trail');
|
||||
}
|
||||
|
||||
if (toolSelections === 0) {
|
||||
warnings.push('No tool selections found in audit trail');
|
||||
}
|
||||
|
||||
// Check for confidence values
|
||||
const entriesWithConfidence = data.auditTrail.filter(e => typeof e.confidence === 'number').length;
|
||||
const confidenceRatio = entriesWithConfidence / data.auditTrail.length;
|
||||
|
||||
if (confidenceRatio < 0.8) {
|
||||
warnings.push(`Only ${Math.round(confidenceRatio * 100)}% of audit entries have confidence scores`);
|
||||
}
|
||||
}
|
||||
|
||||
return {
|
||||
isValid: issues.length === 0,
|
||||
issues,
|
||||
warnings
|
||||
};
|
||||
}
|
||||
}
|
||||
@ -1,22 +0,0 @@
|
||||
// src/utils/toolHelpers.ts
|
||||
|
||||
export interface Tool {
|
||||
name: string;
|
||||
type?: 'software' | 'method' | 'concept';
|
||||
projectUrl?: string | null;
|
||||
license?: string;
|
||||
knowledgebase?: boolean;
|
||||
domains?: string[];
|
||||
phases?: string[];
|
||||
platforms?: string[];
|
||||
skillLevel?: string;
|
||||
description?: string;
|
||||
tags?: string[];
|
||||
related_concepts?: string[];
|
||||
}
|
||||
|
||||
export {
|
||||
createToolSlug,
|
||||
findToolByIdentifier,
|
||||
isToolHosted
|
||||
} from './clientUtils.js';
|
||||
@ -2,6 +2,7 @@
|
||||
import { aiService } from './aiService.js';
|
||||
import { embeddingsService, type SimilarityResult } from './embeddings.js';
|
||||
import { confidenceScoring } from './confidenceScoring.js';
|
||||
import { JSONParser } from './jsonUtils.js'; // FIXED: Use centralized JSON parsing
|
||||
import { getPrompt } from '../config/prompts.js';
|
||||
import 'dotenv/config';
|
||||
|
||||
@ -248,7 +249,8 @@ class ToolSelector {
|
||||
|
||||
try {
|
||||
const response = await aiService.callAI(prompt, { maxTokens: 2500 });
|
||||
const result = this.safeParseJSON(response.content, null);
|
||||
// FIXED: Use centralized JSON parsing
|
||||
const result = JSONParser.safeParseJSON(response.content, null);
|
||||
|
||||
if (!result || !Array.isArray(result.selectedTools) || !Array.isArray(result.selectedConcepts)) {
|
||||
console.error('[TOOL-SELECTOR] AI selection returned invalid structure');
|
||||
@ -313,7 +315,8 @@ class ToolSelector {
|
||||
|
||||
try {
|
||||
const response = await aiService.callMicroTaskAI(prompt, 1000);
|
||||
const selections = this.safeParseJSON(response.content, []);
|
||||
// FIXED: Use centralized JSON parsing
|
||||
const selections = JSONParser.safeParseJSON(response.content, []);
|
||||
|
||||
if (Array.isArray(selections)) {
|
||||
const validSelections = selections.filter((sel: any) => {
|
||||
@ -365,90 +368,7 @@ class ToolSelector {
|
||||
related_software: concept.related_software || []
|
||||
});
|
||||
|
||||
private safeParseJSON(jsonString: string, fallback: any = null): any {
|
||||
try {
|
||||
let cleaned = jsonString.trim();
|
||||
|
||||
// Remove code block markers
|
||||
const jsonBlockPatterns = [
|
||||
/```json\s*([\s\S]*?)\s*```/i,
|
||||
/```\s*([\s\S]*?)\s*```/i,
|
||||
/\{[\s\S]*\}/,
|
||||
];
|
||||
|
||||
for (const pattern of jsonBlockPatterns) {
|
||||
const match = cleaned.match(pattern);
|
||||
if (match) {
|
||||
cleaned = match[1] || match[0];
|
||||
break;
|
||||
}
|
||||
}
|
||||
|
||||
// Handle truncated JSON
|
||||
if (!cleaned.endsWith('}') && !cleaned.endsWith(']')) {
|
||||
console.warn('[TOOL-SELECTOR] JSON appears truncated, attempting recovery');
|
||||
|
||||
let braceCount = 0;
|
||||
let bracketCount = 0;
|
||||
let inString = false;
|
||||
let escaped = false;
|
||||
let lastCompleteStructure = '';
|
||||
|
||||
for (let i = 0; i < cleaned.length; i++) {
|
||||
const char = cleaned[i];
|
||||
|
||||
if (escaped) {
|
||||
escaped = false;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (char === '\\') {
|
||||
escaped = true;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (char === '"' && !escaped) {
|
||||
inString = !inString;
|
||||
continue;
|
||||
}
|
||||
|
||||
if (!inString) {
|
||||
if (char === '{') braceCount++;
|
||||
if (char === '}') braceCount--;
|
||||
if (char === '[') bracketCount++;
|
||||
if (char === ']') bracketCount--;
|
||||
|
||||
if (braceCount === 0 && bracketCount === 0 && (char === '}' || char === ']')) {
|
||||
lastCompleteStructure = cleaned.substring(0, i + 1);
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
if (lastCompleteStructure) {
|
||||
cleaned = lastCompleteStructure;
|
||||
} else {
|
||||
if (braceCount > 0) cleaned += '}';
|
||||
if (bracketCount > 0) cleaned += ']';
|
||||
}
|
||||
}
|
||||
|
||||
const parsed = JSON.parse(cleaned);
|
||||
|
||||
// Ensure proper structure
|
||||
if (parsed && typeof parsed === 'object') {
|
||||
if (!parsed.selectedTools) parsed.selectedTools = [];
|
||||
if (!parsed.selectedConcepts) parsed.selectedConcepts = [];
|
||||
if (!Array.isArray(parsed.selectedTools)) parsed.selectedTools = [];
|
||||
if (!Array.isArray(parsed.selectedConcepts)) parsed.selectedConcepts = [];
|
||||
}
|
||||
|
||||
return parsed;
|
||||
|
||||
} catch (error) {
|
||||
console.warn('[TOOL-SELECTOR] JSON parsing failed:', error.message);
|
||||
return fallback;
|
||||
}
|
||||
}
|
||||
// REMOVED: safeParseJSON method - now using centralized version from jsonUtils.ts
|
||||
|
||||
getConfig(): ToolSelectionConfig {
|
||||
return { ...this.config };
|
||||
|
||||
Loading…
x
Reference in New Issue
Block a user