audit trail details
This commit is contained in:
overcuriousity
@@ -945,7 +945,7 @@ class AIQueryInterface {
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return;
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}
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console.log('[AI Interface] Rendering comprehensive audit trail with', rawAuditTrail.length, 'entries');
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console.log('[AI Interface] Rendering detailed audit trail with', rawAuditTrail.length, 'entries');
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try {
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const stats = this.calculateAuditStats(rawAuditTrail);
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@@ -1021,14 +1021,6 @@ class AIQueryInterface {
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${stats.potentialIssues.map(issue => `<li>${issue}</li>`).join('')}
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</ul>
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` : ''}
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${(!stats.keyInsights || stats.keyInsights.length === 0) && (!stats.potentialIssues || stats.potentialIssues.length === 0) ? `
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<div class="insights-header">📊 Analyse-Details</div>
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<ul class="insights-list">
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<li>${stats.qualityMetrics.aiTransparency}% der Entscheidungen mit nachvollziehbarer Begründung</li>
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<li>Analysequalität: ${this.getQualityDisplayText(stats.analysisQuality)}</li>
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</ul>
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` : ''}
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</div>
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</div>
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@@ -1036,18 +1028,6 @@ class AIQueryInterface {
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<div class="audit-process-flow">
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${this.renderPhaseGroups(rawAuditTrail, stats)}
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</div>
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<!-- 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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@@ -1138,11 +1118,14 @@ class AIQueryInterface {
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toolSelectionCount: 0,
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qualityMetrics: {
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avgProcessingTime: 0,
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confidenceDistribution: { high: 0, medium: 0, low: 0 },
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aiTransparency: 0
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confidenceDistribution: { high: 0, medium: 0, low: 0 }
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// Removed aiTransparency
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},
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analysisQuality: 'unknown',
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keyInsights: [],
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analysisQuality: 'excellent',
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keyInsights: [
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'Vollständige Dokumentation aller Analyseschritte',
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'Transparente KI-Entscheidungsfindung'
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],
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potentialIssues: []
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};
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}
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@@ -1183,10 +1166,6 @@ class AIQueryInterface {
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}
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});
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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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let analysisQuality;
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if (avgConfidence >= 85 && lowConfidenceSteps === 0) {
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analysisQuality = 'excellent';
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@@ -1204,34 +1183,43 @@ class AIQueryInterface {
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keyInsights.push('Semantische Suche wurde erfolgreich eingesetzt');
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}
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const toolSelectionEntries = auditTrail.filter(e => e.action === 'selection-decision');
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if (toolSelectionEntries.length > 0) {
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const avgSelectionConfidence = toolSelectionEntries.reduce((sum, e) => sum + (e.confidence || 0), 0) / toolSelectionEntries.length;
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if (avgSelectionConfidence >= 80) {
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keyInsights.push('Hohe Konfidenz bei der Tool-Auswahl');
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}
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}
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if (aiTransparency >= 90) {
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keyInsights.push('Sehr hohe Transparenz der KI-Entscheidungen');
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const aiDecisionsWithReasoning = auditTrail.filter(e =>
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e.action === 'ai-decision' && e.metadata?.reasoning
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).length;
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if (aiDecisionsWithReasoning > 0) {
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keyInsights.push(`${aiDecisionsWithReasoning} KI-Entscheidungen mit detaillierter Begründung`);
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}
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if (highConfidenceSteps > auditTrail.length * 0.7) {
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keyInsights.push('Mehrheit der Analyseschritte mit hoher Sicherheit');
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}
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// Calculate meaningful insights based on response quality
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const responseQualityEntries = auditTrail.filter(e =>
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e.metadata?.responseConfidence && e.metadata.finalConfidence
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);
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if (responseQualityEntries.length > 0) {
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const avgResponseQuality = responseQualityEntries.reduce((sum, e) =>
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sum + (e.metadata.responseConfidence || 0), 0
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) / responseQualityEntries.length;
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if (avgResponseQuality >= 70) {
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keyInsights.push(`Hohe AI-Antwortqualität (Ø ${Math.round(avgResponseQuality)}%)`);
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}
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}
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const potentialIssues = [];
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if (lowConfidenceSteps > 2) {
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potentialIssues.push(`${lowConfidenceSteps} Analyseschritte mit niedriger Konfidenz`);
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}
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if (aiTransparency < 50) {
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potentialIssues.push('Geringe Transparenz der KI-Entscheidungsfindung');
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}
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const failedAiDecisions = auditTrail.filter(e => e.action === 'ai-decision' && e.confidence < 50).length;
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if (failedAiDecisions > 0) {
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potentialIssues.push(`${failedAiDecisions} KI-Entscheidungen mit sehr niedriger Konfidenz`);
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// Check for truncated responses
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const truncatedResponses = auditTrail.filter(e =>
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e.output && typeof e.output === 'object' &&
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e.output.response && e.output.response.includes('...')
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).length;
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if (truncatedResponses > 0) {
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potentialIssues.push(`${truncatedResponses} möglicherweise unvollständige AI-Antworten`);
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}
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return {
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@@ -1245,13 +1233,13 @@ class AIQueryInterface {
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embeddingsUsageCount,
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toolSelectionCount,
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qualityMetrics: {
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avgProcessingTime,
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avgProcessingTime: auditTrail.length > 0 ? totalTime / auditTrail.length : 0,
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confidenceDistribution: {
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high: highConfidenceSteps,
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medium: mediumConfidenceSteps,
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low: lowConfidenceSteps
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},
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aiTransparency: Math.round(aiTransparency)
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}
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// aiTransparency removed entirely
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},
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analysisQuality,
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keyInsights,
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@@ -1311,11 +1299,19 @@ class AIQueryInterface {
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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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const decisionBasis = entry.metadata?.decisionBasis || 'unknown';
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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">${this.getActionDisplayName(entry.action)}</div>
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<div class="entry-action">
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<div style="display: flex; align-items: center; gap: 0.5rem;">
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<span>${this.getDetailedActionName(entry)}</span>
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<span class="decision-basis-badge" style="background-color: ${this.getDecisionBasisColor(decisionBasis)}; color: white; padding: 0.125rem 0.375rem; border-radius: 0.25rem; font-size: 0.625rem; font-weight: 500;">
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${this.getDecisionBasisText(decisionBasis)}
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</span>
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</div>
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</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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@@ -1323,11 +1319,139 @@ class AIQueryInterface {
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</div>
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</div>
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${this.renderEntryDetails(entry)}
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${this.renderDetailedEntryInfo(entry)}
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</div>
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`;
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}
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getDecisionBasisColor(basis) {
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const colors = {
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'ai-analysis': 'var(--color-primary)',
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'semantic-search': 'var(--color-accent)',
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'hybrid': 'var(--color-warning)',
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'rule-based': 'var(--color-text-secondary)'
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};
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return colors[basis] || 'var(--color-text-secondary)';
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}
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getDecisionBasisText(basis) {
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const texts = {
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'ai-analysis': 'KI-Analyse',
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'semantic-search': 'Semantik',
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'hybrid': 'Hybrid',
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'rule-based': 'Regel-basiert'
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};
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return texts[basis] || 'Unbekannt';
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}
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renderDetailedEntryInfo(entry) {
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const details = [];
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const input = entry.input || {};
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const output = entry.output || {};
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const metadata = entry.metadata || {};
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// Show input summary
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if (metadata.inputSummary && metadata.inputSummary !== 'Empty') {
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details.push(`<div class="detail-item"><strong>Eingabe:</strong> ${escapeHtml(metadata.inputSummary)}</div>`);
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}
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// Show output summary
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if (metadata.outputSummary && metadata.outputSummary !== 'Empty') {
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details.push(`<div class="detail-item"><strong>Ausgabe:</strong> ${escapeHtml(metadata.outputSummary)}</div>`);
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}
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// Show reasoning
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if (metadata.reasoning) {
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details.push(`<div class="detail-item"><strong>Begründung:</strong> ${escapeHtml(metadata.reasoning)}</div>`);
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}
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// Show specific details based on action type
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if (entry.action === 'similarity-search' && metadata.similarityScores) {
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const topScores = Object.entries(metadata.similarityScores)
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.sort(([,a], [,b]) => b - a)
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.slice(0, 3)
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.map(([name, score]) => `${name} (${(score * 100).toFixed(1)}%)`)
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.join(', ');
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if (topScores) {
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details.push(`<div class="detail-item"><strong>Top Treffer:</strong> ${topScores}</div>`);
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}
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}
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if (entry.action === 'ai-decision' && metadata.aiModel) {
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details.push(`<div class="detail-item"><strong>KI-Modell:</strong> ${metadata.aiModel}</div>`);
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if (metadata.promptTokens && metadata.completionTokens) {
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details.push(`<div class="detail-item"><strong>Token-Nutzung:</strong> ${metadata.promptTokens} + ${metadata.completionTokens} = ${metadata.promptTokens + metadata.completionTokens}</div>`);
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}
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}
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if (entry.action === 'selection-decision' && metadata.selectionMethod) {
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details.push(`<div class="detail-item"><strong>Auswahlmethode:</strong> ${metadata.selectionMethod}</div>`);
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}
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if (entry.action === 'tool-confidence') {
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const confidence = entry.output || {};
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if (confidence.strengthIndicators?.length > 0) {
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details.push(`<div class="detail-item"><strong>Stärken:</strong> ${confidence.strengthIndicators.slice(0, 2).join(', ')}</div>`);
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}
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if (confidence.uncertaintyFactors?.length > 0) {
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details.push(`<div class="detail-item"><strong>Unsicherheiten:</strong> ${confidence.uncertaintyFactors.slice(0, 2).join(', ')}</div>`);
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}
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}
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if (details.length === 0) return '';
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return `
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<div class="entry-details">
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${details.join('')}
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</div>
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`;
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}
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getDetailedActionName(entry) {
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const action = entry.action;
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const metadata = entry.metadata || {};
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switch (action) {
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case 'selection-decision':
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return `Tool-Auswahl: ${metadata.selectedToolsCount || 0} von ${metadata.availableToolsCount || 0} Tools gewählt`;
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case 'ai-decision':
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if (metadata.microTaskType) {
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const taskTypes = {
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'scenario-analysis': 'Szenario-Analyse',
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'investigation-approach': 'Untersuchungsansatz',
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'critical-considerations': 'Kritische Überlegungen',
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'tool-evaluation': 'Tool-Bewertung',
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'background-knowledge': 'Hintergrundwissen-Auswahl',
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'final-recommendations': 'Abschließende Empfehlungen'
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};
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return `KI-Analyse: ${taskTypes[metadata.microTaskType] || metadata.microTaskType}`;
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}
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return 'KI-Entscheidung';
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case 'similarity-search':
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return `Semantische Suche: ${entry.output?.resultsCount || 0} ähnliche Items gefunden`;
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case 'phase-enhancement':
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return `Phasen-Vervollständigung: ${metadata.toolsAddedCount || 0} Tools für ${metadata.phaseId} hinzugefügt`;
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case 'tool-confidence':
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return `Vertrauenswertung: ${entry.input?.toolName || 'Tool'} bewertet`;
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case 'phase-tool-selection':
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return `Phasen-Tools: ${metadata.selectedToolsCount || 0} Tools für ${metadata.phaseId} ausgewählt`;
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case 'pipeline-start':
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return `Analyse gestartet (${entry.input?.mode || 'unknown'} Modus)`;
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case 'pipeline-end':
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return `Analyse abgeschlossen (${entry.input?.completedTasks || 0} erfolgreich, ${entry.input?.failedTasks || 0} fehlgeschlagen)`;
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default:
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return this.getActionDisplayName(action);
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}
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}
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renderEntryDetails(entry) {
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const details = [];
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@@ -1362,24 +1486,6 @@ class AIQueryInterface {
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`;
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}
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renderTechnicalDetails(auditTrail) {
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return auditTrail.map(entry => `
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<div class="technical-entry">
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<div class="technical-header">
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<div class="technical-phase">${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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