Jon
57770fd99d
🎯 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
84 lines
3.0 KiB
JavaScript
84 lines
3.0 KiB
JavaScript
// Test PDF text extraction functionality
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require('ts-node/register');
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const { documentController } = require('./src/controllers/documentController');
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async function testPDFExtraction() {
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try {
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console.log('Testing PDF text extraction...');
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// Get a real document ID from the database
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const { Pool } = require('pg');
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const pool = new Pool({
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connectionString: 'postgresql://postgres:password@localhost:5432/cim_processor'
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});
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// Find a PDF document
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const result = await pool.query(`
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SELECT id, original_file_name, file_path
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FROM documents
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WHERE original_file_name LIKE '%.pdf'
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ORDER BY created_at DESC
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LIMIT 1
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`);
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if (result.rows.length === 0) {
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console.log('❌ No PDF documents found in database');
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await pool.end();
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return;
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}
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const document = result.rows[0];
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console.log(`📄 Testing with document: ${document.original_file_name}`);
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console.log(`📁 File path: ${document.file_path}`);
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// Test text extraction
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console.log('\n🔄 Extracting text from PDF...');
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const startTime = Date.now();
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const extractedText = await documentController.getDocumentText(document.id);
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const extractionTime = Date.now() - startTime;
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console.log('✅ PDF text extraction completed!');
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console.log(`⏱️ Extraction time: ${extractionTime}ms`);
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console.log(`📊 Text length: ${extractedText.length} characters`);
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console.log(`📄 Estimated pages: ${Math.ceil(extractedText.length / 2000)}`);
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// Show first 500 characters as preview
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console.log('\n📋 Text preview (first 500 characters):');
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console.log('=' .repeat(50));
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console.log(extractedText.substring(0, 500) + '...');
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console.log('=' .repeat(50));
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// Check if text contains expected content
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const hasFinancialContent = extractedText.toLowerCase().includes('revenue') ||
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extractedText.toLowerCase().includes('ebitda') ||
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extractedText.toLowerCase().includes('financial');
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const hasCompanyContent = extractedText.toLowerCase().includes('company') ||
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extractedText.toLowerCase().includes('business') ||
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extractedText.toLowerCase().includes('corporate');
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console.log('\n🔍 Content Analysis:');
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console.log(`- Contains financial terms: ${hasFinancialContent ? '✅' : '❌'}`);
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console.log(`- Contains company/business terms: ${hasCompanyContent ? '✅' : '❌'}`);
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if (extractedText.length < 100) {
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console.log('⚠️ Warning: Extracted text seems too short, may indicate extraction issues');
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} else if (extractedText.length > 10000) {
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console.log('✅ Good: Extracted text is substantial in length');
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}
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await pool.end();
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} catch (error) {
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console.error('❌ PDF text extraction test failed:', error);
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console.error('Error details:', {
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name: error.name,
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message: error.message,
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stack: error.stack
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});
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}
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}
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testPDFExtraction();
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