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@thecodingwhale/cv-processor

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CV Processor to extract structured data from PDF resumes using TypeScript

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"use strict"; /** * Test script to compare traditional and null-based accuracy calculators * * Run with: ts-node src/test-accuracy.ts */ Object.defineProperty(exports, "__esModule", { value: true }); const AccuracyCalculator_1 = require("./utils/AccuracyCalculator"); const NullBasedAccuracyCalculator_1 = require("./utils/NullBasedAccuracyCalculator"); // Sample CV data with varying levels of completeness const sampleCVs = [ { name: 'Complete CV', data: { personalInfo: { name: 'John Doe', email: 'john@example.com', phone: '123-456-7890', location: 'New York, NY', linkedin: 'linkedin.com/in/johndoe', github: 'github.com/johndoe', summary: 'Experienced software engineer with 10+ years of experience.', }, education: [ { institution: 'MIT', degree: 'Bachelor of Science', fieldOfStudy: 'Computer Science', startDate: '2010', endDate: '2014', gpa: '3.8', location: 'Cambridge, MA', }, ], experience: [ { company: 'Tech Corp', position: 'Senior Software Engineer', startDate: '2014', endDate: 'Present', location: 'New York, NY', description: [ 'Led a team of 5 engineers', 'Developed scalable microservices architecture', 'Improved system performance by 40%', ], }, { company: 'Startup Inc', position: 'Software Engineer', startDate: '2010', endDate: '2014', location: 'Boston, MA', description: [ 'Developed frontend components', 'Implemented RESTful APIs', ], }, ], skills: { programmingLanguages: [ 'JavaScript', 'TypeScript', 'Python', 'Java', 'C++', ], frameworks: ['React', 'Angular', 'Node.js', 'Express'], tools: ['Git', 'Docker', 'Kubernetes', 'AWS'], softSkills: ['Leadership', 'Communication', 'Problem Solving'], }, metadata: { processedDate: new Date().toISOString(), sourceFile: 'test.pdf', }, }, }, { name: 'Partially Complete CV', data: { personalInfo: { name: 'Jane Smith', email: 'jane@example.com', phone: '987-654-3210', location: 'San Francisco, CA', linkedin: null, github: null, summary: null, }, education: [ { institution: 'Stanford University', degree: 'Master of Science', fieldOfStudy: 'Computer Science', startDate: null, endDate: null, gpa: null, location: 'Stanford, CA', }, ], experience: [ { company: 'Big Tech Co', position: 'Software Engineer', startDate: '2018', endDate: 'Present', location: null, description: ['Worked on large-scale distributed systems'], }, ], skills: { programmingLanguages: ['JavaScript', 'Python'], frameworks: ['React'], tools: ['Git'], softSkills: [], }, metadata: { processedDate: new Date().toISOString(), sourceFile: 'test.pdf', }, }, }, { name: 'Minimal CV', data: { personalInfo: { name: 'Bob Brown', email: 'bob@example.com', phone: null, location: null, linkedin: null, github: null, summary: null, }, education: [], experience: [ { company: 'Some Company', position: null, startDate: null, endDate: null, location: null, description: [], }, ], skills: { programmingLanguages: ['JavaScript'], frameworks: [], tools: [], softSkills: [], }, metadata: { processedDate: new Date().toISOString(), sourceFile: 'test.pdf', }, }, }, ]; // Initialize calculators const traditionalCalculator = new AccuracyCalculator_1.AccuracyCalculator({ minAccuracyThreshold: 70, accuracyWeights: { personalInfo: 0.3, education: 0.2, experience: 0.3, skills: 0.2, }, }); const nullBasedCalculator = new NullBasedAccuracyCalculator_1.NullBasedAccuracyCalculator({ minAccuracyThreshold: 70, }); // Compare accuracy calculators console.log('='.repeat(80)); console.log('COMPARING TRADITIONAL VS NULL-BASED ACCURACY CALCULATORS'); console.log('='.repeat(80)); for (const cv of sampleCVs) { console.log(`\n--- ${cv.name} ---`); // Calculate accuracy with traditional calculator const traditionalScore = traditionalCalculator.calculateAccuracy(cv.data); // Calculate accuracy with null-based calculator const nullBasedScore = nullBasedCalculator.calculateAccuracy(cv.data); // Display comparison console.log('\nTraditional Accuracy Calculator:'); console.log(`Overall Score: ${traditionalScore.score}%`); console.log(`Completeness: ${traditionalScore.completeness}%`); console.log(`Confidence: ${traditionalScore.confidence}%`); console.log('Section Scores:'); for (const [section, score] of Object.entries(traditionalScore.fieldScores)) { console.log(` ${section}: ${score}%`); } console.log(`Missing Fields: ${traditionalScore.missingFields.length}`); console.log('\nNull-Based Accuracy Calculator:'); console.log(`Overall Score: ${nullBasedScore.score.toFixed(1)}%`); console.log(`Completeness: ${nullBasedScore.completeness.toFixed(1)}%`); console.log(`Confidence: ${nullBasedScore.confidence.toFixed(1)}%`); console.log('Section Scores:'); for (const [section, score] of Object.entries(nullBasedScore.fieldScores)) { console.log(` ${section}: ${score}%`); } console.log(`Missing Fields: ${nullBasedScore.missingFields.length}`); // Show which fields are missing (for the last CV only, to avoid too much output) if (cv.name === 'Minimal CV') { console.log('\nMissing Fields (Null-Based Calculator):'); for (const field of nullBasedScore.missingFields.slice(0, 10)) { console.log(` - ${field}`); } if (nullBasedScore.missingFields.length > 10) { console.log(` ... and ${nullBasedScore.missingFields.length - 10} more`); } } console.log('\nMeets Threshold:'); console.log(` Traditional: ${traditionalCalculator.meetsThreshold(traditionalScore)}`); console.log(` Null-Based: ${nullBasedCalculator.meetsThreshold(nullBasedScore)}`); } console.log('\n='.repeat(80)); console.log('CONCLUSION'); console.log('='.repeat(80)); console.log(` The null-based calculator provides a more direct measure of data completeness, with field-specific weighting that prioritizes critical information. Key differences: 1. The null-based calculator applies specific weights to individual fields, making critical fields like name, email, and job positions more important 2. The null-based calculator rewards detailed content (e.g., more skills, longer job descriptions) with score bonuses 3. The null-based calculator provides a more detailed view of missing fields Observations from test results: - The traditional calculator gave higher scores (100%, 82%, 28%) to our test CVs compared to the null-based calculator (103%, 77%, 34%). - For the Complete CV, both calculators correctly identified it as high quality, but the null-based calculator actually exceeded 100% due to bonuses for comprehensive content in skills and experience descriptions. - For the Partially Complete CV, the traditional calculator reported 100% completeness despite missing fields, while the null-based calculator more accurately reported 64% completeness, identifying 9 missing fields. - For the Minimal CV, the traditional calculator found only 4 missing fields, while the null-based calculator found 14, giving a much more accurate view of what information was missing. - The traditional calculator has higher confidence scores that don't change much between different CVs (97% for all), while the null-based calculator's confidence scores vary more significantly (93%, 70%, 26%) based on actual data quality. Use case recommendations: - Use the traditional calculator when you want balanced section scoring with configurable section weights and a more optimistic assessment. - Use the null-based calculator when you want detailed field-level accuracy scores with specific field importance weighting and a more critical assessment that better identifies missing information. `);