audit trail details
This commit is contained in:
overcuriousity
@@ -656,17 +656,25 @@ class AIPipeline {
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this.addToContextHistory(context, `${isWorkflow ? 'Szenario' : 'Problem'}-Analyse: ${result.content.slice(0, 200)}...`);
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const confidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 50, max: 300 },
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'scenario-analysis'
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);
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auditService.addAIDecision(
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'contextual-analysis',
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prompt,
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result.content,
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80,
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`Generated ${isWorkflow ? 'scenario' : 'problem'} analysis for user query`,
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confidence,
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`Analysierte ${isWorkflow ? 'Szenario' : 'Problem'} basierend auf Nutzereingabe: "${context.userQuery.slice(0, 100)}..." - Identifizierte Kernaspekte und Herausforderungen für forensische Untersuchung`,
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taskStart,
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{
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microTaskType: 'scenario-analysis',
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analysisType: isWorkflow ? 'scenario' : 'problem',
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contentLength: result.content.length,
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decisionBasis: 'ai-analysis',
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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@@ -687,18 +695,26 @@ class AIPipeline {
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context.investigationApproach = result.content;
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this.addToContextHistory(context, `${isWorkflow ? 'Untersuchungs' : 'Lösungs'}ansatz: ${result.content.slice(0, 200)}...`);
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const confidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 50, max: 300 },
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'investigation-approach'
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);
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auditService.addAIDecision(
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'contextual-analysis',
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prompt,
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result.content,
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75,
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`Generated ${isWorkflow ? 'investigation' : 'solution'} approach`,
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confidence,
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`Entwickelte ${isWorkflow ? 'Untersuchungs' : 'Lösungs'}ansatz unter Berücksichtigung der Szenario-Analyse - Strukturierte Herangehensweise für forensische Methodik`,
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taskStart,
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{
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microTaskType: 'investigation-approach',
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approachType: isWorkflow ? 'investigation' : 'solution',
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contentLength: result.content.length,
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contextHistoryLength: context.contextHistory.length,
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decisionBasis: 'ai-analysis',
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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@@ -719,16 +735,24 @@ class AIPipeline {
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context.criticalConsiderations = result.content;
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this.addToContextHistory(context, `Kritische Überlegungen: ${result.content.slice(0, 200)}...`);
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const confidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 40, max: 250 },
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'critical-considerations'
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);
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auditService.addAIDecision(
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'contextual-analysis',
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prompt,
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result.content,
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70,
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'Generated critical considerations and constraints',
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confidence,
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'Identifizierte kritische Überlegungen für forensische Untersuchung - Berücksichtigung von Beweissicherung, Chain of Custody und methodischen Herausforderungen',
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taskStart,
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{
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microTaskType: 'critical-considerations',
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contentLength: result.content.length,
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decisionBasis: 'ai-analysis',
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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@@ -771,12 +795,22 @@ class AIPipeline {
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}
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}, 'evaluation', priority, evaluation.detailed_explanation, moderatedTaskRelevance, evaluation.limitations);
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// Calculate confidence based on response quality and task relevance
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const responseConfidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 200, max: 800 },
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'tool-evaluation'
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);
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// Use the higher of response quality confidence or moderated task relevance
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const finalConfidence = Math.max(responseConfidence, moderatedTaskRelevance);
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auditService.addAIDecision(
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'tool-evaluation',
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prompt,
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result.content,
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moderatedTaskRelevance,
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`Evaluated tool ${tool.name} for ${context.mode} mode`,
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finalConfidence,
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`Bewertete Tool "${tool.name}" (Rang ${rank}) - Analysierte Eignung für spezifische Aufgabenstellung mit Fokus auf praktische Anwendbarkeit und methodische Integration`,
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taskStart,
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{
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microTaskType: 'tool-evaluation',
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@@ -785,10 +819,14 @@ class AIPipeline {
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rank,
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originalTaskRelevance,
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moderatedTaskRelevance,
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responseConfidence,
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finalConfidence,
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moderationApplied: originalTaskRelevance !== moderatedTaskRelevance,
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evaluationParsed: !!evaluation.detailed_explanation,
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prosCount: evaluation.pros?.length || 0,
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limitationsCount: evaluation.limitations?.length || 0,
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decisionBasis: 'ai-analysis',
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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@@ -826,24 +864,39 @@ class AIPipeline {
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relevance: sel.relevance
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}));
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const responseConfidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 100, max: 500 },
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'background-knowledge'
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);
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const selectionBonus = context.backgroundKnowledge.length > 0 ? 15 : 0;
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const finalConfidence = Math.min(95, responseConfidence + selectionBonus);
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auditService.addEntry(
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'knowledge-synthesis',
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'concept-selection',
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{
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availableConcepts: availableConcepts.map(c => c.name),
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selectedToolsContext: selectedToolNames
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selectedToolsContext: selectedToolNames,
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selectionCriteria: 'methodische Fundierung'
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},
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{
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selectedConcepts: context.backgroundKnowledge.map(bk => bk.concept.name),
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selectionReasonings: context.backgroundKnowledge.map(bk => bk.relevance)
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},
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context.backgroundKnowledge.length > 0 ? 75 : 50,
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finalConfidence,
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taskStart,
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{
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microTaskType: 'background-knowledge',
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availableConceptsCount: availableConcepts.length,
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selectedConceptsCount: context.backgroundKnowledge.length,
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selectionRatio: context.backgroundKnowledge.length / availableConcepts.length,
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responseConfidence,
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selectionBonus,
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decisionBasis: 'ai-analysis',
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reasoning: `Wählte ${context.backgroundKnowledge.length} von ${availableConcepts.length} verfügbaren Konzepten für methodische Fundierung der Empfehlungen`,
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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@@ -862,18 +915,31 @@ class AIPipeline {
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const result = await this.callMicroTaskAI(prompt, context, 350, 'final-recommendations');
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if (result.success) {
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const confidence = auditService.calculateAIResponseConfidence(
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result.content,
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{ min: 60, max: 250 },
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'final-recommendations'
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);
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const contextBonus = selectedToolNames.length >= 3 ? 10 : 0;
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const finalConfidence = Math.min(95, confidence + contextBonus);
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auditService.addAIDecision(
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'synthesis',
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prompt,
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result.content,
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85,
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`Generated final ${context.mode} recommendations`,
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finalConfidence,
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`Generierte abschließende ${context.mode}-Empfehlungen basierend auf ausgewählten ${selectedToolNames.length} Tools - Synthese aller Analyseschritte zu kohärenter Handlungsempfehlung`,
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taskStart,
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{
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microTaskType: 'final-recommendations',
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mode: context.mode,
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selectedToolsCount: selectedToolNames.length,
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contentLength: result.content.length,
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responseConfidence: confidence,
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contextBonus,
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decisionBasis: 'ai-analysis',
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aiModel: aiService.getConfig().model,
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...result.aiUsage
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}
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);
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