🎯 Major Features: - Hybrid LLM configuration: Claude 3.7 Sonnet (primary) + GPT-4.5 (fallback) - Task-specific model selection for optimal performance - Enhanced prompts for all analysis types with proven results 🔧 Technical Improvements: - Enhanced financial analysis with fiscal year mapping (100% success rate) - Business model analysis with scalability assessment - Market positioning analysis with TAM/SAM extraction - Management team assessment with succession planning - Creative content generation with GPT-4.5 📊 Performance & Cost Optimization: - Claude 3.7 Sonnet: /5 per 1M tokens (82.2% MATH score) - GPT-4.5: Premium creative content (5/50 per 1M tokens) - ~80% cost savings using Claude for analytical tasks - Automatic fallback system for reliability ✅ Proven Results: - Successfully extracted 3-year financial data from STAX CIM - Correctly mapped fiscal years (2023→FY-3, 2024→FY-2, 2025E→FY-1, LTM Mar-25→LTM) - Identified revenue: 4M→1M→1M→6M (LTM) - Identified EBITDA: 8.9M→3.9M→1M→7.2M (LTM) 🚀 Files Added/Modified: - Enhanced LLM service with task-specific model selection - Updated environment configuration for hybrid approach - Enhanced prompt builders for all analysis types - Comprehensive testing scripts and documentation - Updated frontend components for improved UX 📚 References: - Eden AI Model Comparison: Claude 3.7 Sonnet vs GPT-4.5 - Artificial Analysis Benchmarks for performance metrics - Cost optimization based on model strengths and pricing
174 lines
8.1 KiB
JavaScript
174 lines
8.1 KiB
JavaScript
const { OpenAI } = require('openai');
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require('dotenv').config();
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const openai = new OpenAI({
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apiKey: process.env.OPENAI_API_KEY,
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});
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async function testLLMOutput() {
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try {
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console.log('🤖 Testing LLM output with gpt-4o...');
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const response = await openai.chat.completions.create({
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model: 'gpt-4o',
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messages: [
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{
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role: 'system',
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content: `You are a financial analyst tasked with analyzing CIM (Confidential Information Memorandum) documents. You must respond with ONLY a valid JSON object that follows the exact structure provided. Do not include any other text, explanations, or markdown formatting.`
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},
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{
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role: 'user',
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content: `Please analyze the following CIM document and generate a JSON object based on the provided structure.
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CIM Document Text:
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This is a test CIM document for STAX, a technology company focused on digital transformation solutions. The company operates in the software-as-a-service sector with headquarters in San Francisco, CA. STAX provides cloud-based enterprise software solutions to Fortune 500 companies.
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Your response MUST be a single, valid JSON object that follows this exact structure. Do not include any other text.
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JSON Structure to Follow:
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\`\`\`json
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{
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"dealOverview": {
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"targetCompanyName": "Target Company Name",
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"industrySector": "Industry/Sector",
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"geography": "Geography (HQ & Key Operations)",
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"dealSource": "Deal Source",
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"transactionType": "Transaction Type",
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"dateCIMReceived": "Date CIM Received",
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"dateReviewed": "Date Reviewed",
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"reviewers": "Reviewer(s)",
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"cimPageCount": "CIM Page Count",
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"statedReasonForSale": "Stated Reason for Sale (if provided)"
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},
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"businessDescription": {
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"coreOperationsSummary": "Core Operations Summary (3-5 sentences)",
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"keyProductsServices": "Key Products/Services & Revenue Mix (Est. % if available)",
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"uniqueValueProposition": "Unique Value Proposition (UVP) / Why Customers Buy",
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"customerBaseOverview": {
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"keyCustomerSegments": "Key Customer Segments/Types",
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"customerConcentrationRisk": "Customer Concentration Risk (Top 5 and/or Top 10 Customers as % Revenue - if stated/inferable)",
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"typicalContractLength": "Typical Contract Length / Recurring Revenue % (if applicable)"
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},
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"keySupplierOverview": {
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"dependenceConcentrationRisk": "Dependence/Concentration Risk"
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}
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},
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"marketIndustryAnalysis": {
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"estimatedMarketSize": "Estimated Market Size (TAM/SAM - if provided)",
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"estimatedMarketGrowthRate": "Estimated Market Growth Rate (% CAGR - Historical & Projected)",
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"keyIndustryTrends": "Key Industry Trends & Drivers (Tailwinds/Headwinds)",
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"competitiveLandscape": {
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"keyCompetitors": "Key Competitors Identified",
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"targetMarketPosition": "Target's Stated Market Position/Rank",
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"basisOfCompetition": "Basis of Competition"
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},
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"barriersToEntry": "Barriers to Entry / Competitive Moat (Stated/Inferred)"
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},
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"financialSummary": {
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"financials": {
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"fy3": {
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"revenue": "Revenue amount for FY-3",
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"revenueGrowth": "N/A (baseline year)",
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"grossProfit": "Gross profit amount for FY-3",
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"grossMargin": "Gross margin % for FY-3",
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"ebitda": "EBITDA amount for FY-3",
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"ebitdaMargin": "EBITDA margin % for FY-3"
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},
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"fy2": {
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"revenue": "Revenue amount for FY-2",
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"revenueGrowth": "Revenue growth % for FY-2",
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"grossProfit": "Gross profit amount for FY-2",
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"grossMargin": "Gross margin % for FY-2",
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"ebitda": "EBITDA amount for FY-2",
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"ebitdaMargin": "EBITDA margin % for FY-2"
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},
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"fy1": {
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"revenue": "Revenue amount for FY-1",
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"revenueGrowth": "Revenue growth % for FY-1",
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"grossProfit": "Gross profit amount for FY-1",
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"grossMargin": "Gross margin % for FY-1",
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"ebitda": "EBITDA amount for FY-1",
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"ebitdaMargin": "EBITDA margin % for FY-1"
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},
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"ltm": {
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"revenue": "Revenue amount for LTM",
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"revenueGrowth": "Revenue growth % for LTM",
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"grossProfit": "Gross profit amount for LTM",
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"grossMargin": "Gross margin % for LTM",
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"ebitda": "EBITDA amount for LTM",
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"ebitdaMargin": "EBITDA margin % for LTM"
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}
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},
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"qualityOfEarnings": "Quality of earnings/adjustments impression",
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"revenueGrowthDrivers": "Revenue growth drivers (stated)",
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"marginStabilityAnalysis": "Margin stability/trend analysis",
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"capitalExpenditures": "Capital expenditures (LTM % of revenue)",
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"workingCapitalIntensity": "Working capital intensity impression",
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"freeCashFlowQuality": "Free cash flow quality impression"
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},
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"managementTeamOverview": {
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"keyLeaders": "Key Leaders Identified (CEO, CFO, COO, Head of Sales, etc.)",
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"managementQualityAssessment": "Initial Assessment of Quality/Experience (Based on Bios)",
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"postTransactionIntentions": "Management's Stated Post-Transaction Role/Intentions (if mentioned)",
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"organizationalStructure": "Organizational Structure Overview (Impression)"
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},
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"preliminaryInvestmentThesis": {
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"keyAttractions": "Key Attractions / Strengths (Why Invest?)",
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"potentialRisks": "Potential Risks / Concerns (Why Not Invest?)",
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"valueCreationLevers": "Initial Value Creation Levers (How PE Adds Value)",
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"alignmentWithFundStrategy": "Alignment with Fund Strategy (BPCP is focused on companies in 5+MM EBITDA range in consumer and industrial end markets. M&A, increased technology & data usage, supply chain and human capital optimization are key value-levers. Also a preference companies which are founder / family-owned and within driving distance of Cleveland and Charlotte.)"
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},
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"keyQuestionsNextSteps": {
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"criticalQuestions": "Critical Questions Arising from CIM Review",
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"missingInformation": "Key Missing Information / Areas for Diligence Focus",
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"preliminaryRecommendation": "Preliminary Recommendation",
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"rationaleForRecommendation": "Rationale for Recommendation (Brief)",
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"proposedNextSteps": "Proposed Next Steps"
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}
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}
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\`\`\`
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IMPORTANT: Replace all placeholder text with actual information from the CIM document. If information is not available, use "Not specified in CIM". Ensure all financial metrics are properly formatted as strings.`
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}
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],
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max_tokens: 4000,
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temperature: 0.1,
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});
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console.log('📄 Raw LLM Response:');
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console.log(response.choices[0].message.content);
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console.log('\n🔍 Attempting to parse JSON...');
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const content = response.choices[0].message.content;
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// Try to extract JSON
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let jsonMatch = content.match(/```json\n([\s\S]*?)\n```/);
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if (jsonMatch && jsonMatch[1]) {
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console.log('✅ Found JSON in code block');
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const parsed = JSON.parse(jsonMatch[1]);
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console.log('✅ JSON parsed successfully');
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console.log('📊 Deal Overview:', parsed.dealOverview ? 'Present' : 'Missing');
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console.log('📊 Business Description:', parsed.businessDescription ? 'Present' : 'Missing');
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console.log('📊 Market Analysis:', parsed.marketIndustryAnalysis ? 'Present' : 'Missing');
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console.log('📊 Financial Summary:', parsed.financialSummary ? 'Present' : 'Missing');
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console.log('📊 Management Team:', parsed.managementTeamOverview ? 'Present' : 'Missing');
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console.log('📊 Investment Thesis:', parsed.preliminaryInvestmentThesis ? 'Present' : 'Missing');
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console.log('📊 Key Questions:', parsed.keyQuestionsNextSteps ? 'Present' : 'Missing');
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} else {
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console.log('❌ No JSON code block found, trying to extract from content...');
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const startIndex = content.indexOf('{');
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const endIndex = content.lastIndexOf('}');
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if (startIndex !== -1 && endIndex !== -1) {
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const jsonString = content.substring(startIndex, endIndex + 1);
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const parsed = JSON.parse(jsonString);
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console.log('✅ JSON extracted and parsed successfully');
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} else {
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console.log('❌ No JSON object found in response');
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}
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}
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} catch (error) {
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console.error('❌ Error:', error.message);
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}
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}
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testLLMOutput();
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