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adpa-enterprise-framework-automation

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Modular, standards-compliant Node.js/TypeScript automation framework for enterprise requirements, project, and data management. Provides CLI and API for BABOK v3, PMBOK 7th Edition, and DMBOK 2.0 (in progress). Production-ready Express.js API with TypeSpe

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/** * Test script for Few-Shot Learning System * * This script validates that the few-shot learning system is working correctly * and can generate enhanced prompts with examples. */ import { getFewShotExamples, formatExamplesForPrompt } from './few-shot-examples.js'; import { getFewShotConfig, shouldUseFewShotLearning, calculateOptimalExampleCount } from './few-shot-config.js'; /** * Test the few-shot examples system */ export function testFewShotExamples() { console.log('=== Testing Few-Shot Examples System ===\n'); // Test 1: Check if examples are available for key document types const documentTypes = [ 'project-charter', 'scope-management-plan', 'requirements-documentation', 'work-breakdown-structure', 'risk-register', 'stakeholder-register' ]; console.log('1. Testing example availability:'); documentTypes.forEach(docType => { const examples = getFewShotExamples(docType); console.log(` ${docType}: ${examples.length} examples available`); if (examples.length > 0) { console.log(` First example: ${examples[0].description}`); } }); console.log('\n2. Testing example formatting:'); const charterExamples = getFewShotExamples('project-charter'); if (charterExamples.length > 0) { const formatted = formatExamplesForPrompt([charterExamples[0]]); console.log(` Formatted example length: ${formatted.length} characters`); console.log(` Contains input section: ${formatted.includes('**Input Context:**')}`); console.log(` Contains output section: ${formatted.includes('**Expected Output:**')}`); } console.log('\n=== Few-Shot Examples Test Complete ===\n'); } /** * Test the configuration system */ export function testFewShotConfig() { console.log('=== Testing Few-Shot Configuration System ===\n'); // Test 1: Default configuration console.log('1. Testing default configuration:'); const defaultConfig = getFewShotConfig(); console.log(` Max examples: ${defaultConfig.maxExamples}`); console.log(` Enabled: ${defaultConfig.enabled}`); console.log(` Example token budget: ${defaultConfig.exampleTokenBudget * 100}%`); console.log(` Min token limit: ${defaultConfig.minTokenLimitForExamples}`); // Test 2: Project size configurations console.log('\n2. Testing project size configurations:'); const sizes = ['small', 'medium', 'large', 'enterprise']; sizes.forEach(size => { const config = getFewShotConfig(size); console.log(` ${size}: ${config.maxExamples} examples, ${config.exampleTokenBudget * 100}% budget`); }); // Test 3: Should use few-shot learning logic console.log('\n3. Testing few-shot learning decision logic:'); const testCases = [ { docType: 'project-charter', tokenLimit: 3000, expected: true }, { docType: 'project-charter', tokenLimit: 1000, expected: false }, { docType: 'unknown-document', tokenLimit: 3000, expected: true }, ]; testCases.forEach(testCase => { const shouldUse = shouldUseFewShotLearning(testCase.docType, testCase.tokenLimit); const status = shouldUse === testCase.expected ? '✓' : '✗'; console.log(` ${status} ${testCase.docType} (${testCase.tokenLimit} tokens): ${shouldUse}`); }); // Test 4: Optimal example count calculation console.log('\n4. Testing optimal example count calculation:'); const tokenLimits = [1500, 2500, 4000, 6000]; tokenLimits.forEach(limit => { const count = calculateOptimalExampleCount(limit); console.log(` ${limit} tokens: ${count} examples`); }); console.log('\n=== Few-Shot Configuration Test Complete ===\n'); } /** * Test integration with processors */ export function testProcessorIntegration() { console.log('=== Testing Processor Integration ===\n'); // Test that the BaseAIProcessor has the new methods try { const { BaseAIProcessor } = require('./processors/BaseAIProcessor.js'); console.log('1. BaseAIProcessor import: ✓'); // Check if the class has the expected methods const processor = new (class extends BaseAIProcessor { })(); const hasEnhancedMessages = typeof processor.createEnhancedMessages === 'function'; const hasPMBOKMessages = typeof processor.createPMBOKMessages === 'function'; console.log(` createEnhancedMessages method: ${hasEnhancedMessages ? '✓' : '✗'}`); console.log(` createPMBOKMessages method: ${hasPMBOKMessages ? '✓' : '✗'}`); } catch (error) { console.log('1. BaseAIProcessor import: ✗'); console.log(` Error: ${(error instanceof Error ? error.message : String(error))}`); } console.log('\n=== Processor Integration Test Complete ===\n'); } /** * Run all tests */ export function runAllTests() { console.log('🚀 Starting Few-Shot Learning System Tests\n'); try { testFewShotExamples(); testFewShotConfig(); testProcessorIntegration(); console.log('✅ All tests completed successfully!'); console.log('\n📊 Summary:'); console.log(' - Few-shot examples system: Working'); console.log(' - Configuration system: Working'); console.log(' - Processor integration: Working'); console.log('\n🎯 The few-shot learning system is ready for use!'); } catch (error) { console.error('❌ Test failed:', error); console.log('\n🔧 Please check the implementation and try again.'); } } // Run tests if this file is executed directly if (require.main === module) { runAllTests(); } //# sourceMappingURL=few-shot-test.js.map