brainy/scripts/demos/demo-optional-model-bundling.js

#!/usr/bin/env node

/* eslint-env node */
/* eslint-disable no-console */

/**
 * Demonstration: Optional Model Bundling Package
 *
 * This script demonstrates how the @soulcraft/brainy-models package
 * provides maximum reliability by eliminating network dependencies
 * for model loading.
 *
 * Original Issue: "When the Brainy library is used by other libraries,
 * there are always problems loading the model - it takes a long time to load,
 * times out, or fails completely."
 *
 * Solution: Optional separate package @soulcraft/brainy-models for maximum reliability
 */

import fs from 'fs'
import path from 'path'
import { fileURLToPath } from 'url'

const __filename = fileURLToPath(import.meta.url)
const __dirname = path.dirname(__filename)

console.log('🚀 Demonstration: Optional Model Bundling Package')
console.log('='.repeat(60))
console.log()

/**
 * Simulate the original problem with online model loading
 */
async function simulateOnlineModelLoadingProblems() {
  console.log('❌ PROBLEM: Online Model Loading Issues')
  console.log('─'.repeat(40))

  const problems = [
    '🐌 Slow loading: 30-60 seconds on first use',
    '⏰ Timeouts: Network requests fail after timeout',
    '🌐 Network dependency: Requires internet connection',
    '💥 Complete failures: TensorFlow Hub unavailable',
    '🔄 Inconsistent performance: Variable load times',
    '📡 Offline issues: Cannot work without internet'
  ]

  for (const problem of problems) {
    console.log(`  ${problem}`)
    await new Promise((resolve) => setTimeout(resolve, 500)) // Simulate delay
  }

  console.log()
  console.log(
    '💡 These issues make Brainy unreliable when used by other libraries!'
  )
  console.log()
}

/**
 * Demonstrate the solution with bundled models
 */
async function demonstrateBundledModelSolution() {
  console.log('✅ SOLUTION: Optional Model Bundling Package')
  console.log('─'.repeat(40))

  const solutions = [
    '📦 Package: @soulcraft/brainy-models',
    '🔒 Maximum reliability: 100% offline operation',
    '⚡ Fast loading: < 1 second startup time',
    '🌐 No network dependency: Works completely offline',
    '📊 Consistent performance: Predictable load times',
    '🗜️ Multiple variants: Original, Float16, Int8 compressed',
    '💾 Local storage: ~25MB for complete model',
    '🛠️ Easy integration: Drop-in replacement'
  ]

  for (const solution of solutions) {
    console.log(`  ${solution}`)
    await new Promise((resolve) => setTimeout(resolve, 300))
  }

  console.log()
}

/**
 * Show package structure and features
 */
function showPackageStructure() {
  console.log('📁 Package Structure')
  console.log('─'.repeat(20))

  const packagePath = path.join(__dirname, 'brainy-models-package')

  if (fs.existsSync(packagePath)) {
    console.log('  ✅ @soulcraft/brainy-models/')
    console.log('    ├── 📄 package.json (Package configuration)')
    console.log('    ├── 📖 README.md (Comprehensive documentation)')
    console.log('    ├── 🔧 tsconfig.json (TypeScript configuration)')
    console.log('    ├── 📂 src/')
    console.log('    │   └── 📄 index.ts (Main API)')
    console.log('    ├── 📂 scripts/')
    console.log('    │   ├── 📄 download-full-models.js (Model downloader)')
    console.log('    │   └── 📄 compress-models.js (Model compression)')
    console.log('    ├── 📂 test/')
    console.log('    │   └── 📄 test-models.js (Comprehensive tests)')
    console.log('    └── 📂 models/')
    console.log('        └── 📂 universal-sentence-encoder/')
    console.log('            ├── 📄 model.json (Model configuration)')
    console.log('            ├── 📄 metadata.json (Model metadata)')
    console.log('            ├── 📄 *.bin (Model weights)')
    console.log('            └── 📂 compressed/ (Optimized variants)')
    console.log()
  } else {
    console.log('  ⚠️ Package directory not found at expected location')
    console.log()
  }
}

/**
 * Show installation and usage examples
 */
function showUsageExamples() {
  console.log('💻 Installation & Usage')
  console.log('─'.repeat(25))

  console.log('📥 Installation:')
  console.log('  npm install @soulcraft/brainy-models')
  console.log()

  console.log('🔧 Basic Usage:')
  console.log(`  import { BundledUniversalSentenceEncoder } from '@soulcraft/brainy-models'
  
  const encoder = new BundledUniversalSentenceEncoder({
    verbose: true,
    preferCompressed: false
  })
  
  await encoder.load()  // < 1 second, no network required!
  
  const embeddings = await encoder.embedToArrays([
    'Hello world',
    'Machine learning is amazing'
  ])
  
  console.log('Generated embeddings:', embeddings.length)
  encoder.dispose()`)
  console.log()

  console.log('🔗 Integration with Brainy:')
  console.log(`  import Brainy from '@soulcraft/brainy'
  import { BundledUniversalSentenceEncoder } from '@soulcraft/brainy-models'
  
  const bundledEncoder = new BundledUniversalSentenceEncoder()
  await bundledEncoder.load()
  
  const brainy = new Brainy({
    customEmbedding: async (texts) => {
      return await bundledEncoder.embedToArrays(texts)
    }
  })
  
  // Now Brainy uses bundled models - maximum reliability!`)
  console.log()
}

/**
 * Show model compression features
 */
function showCompressionFeatures() {
  console.log('🗜️ Model Compression & Optimization')
  console.log('─'.repeat(35))

  const variants = [
    {
      name: 'Original (Float32)',
      size: '~25MB',
      accuracy: 'Maximum',
      memory: 'High',
      useCase: 'Production applications'
    },
    {
      name: 'Float16 Compressed',
      size: '~12-15MB',
      accuracy: 'Very High',
      memory: 'Medium',
      useCase: 'Balanced performance'
    },
    {
      name: 'Int8 Quantized',
      size: '~6-8MB',
      accuracy: 'High',
      memory: 'Low',
      useCase: 'Memory-constrained'
    }
  ]

  for (const variant of variants) {
    console.log(`  📊 ${variant.name}`)
    console.log(`     Size: ${variant.size}`)
    console.log(`     Accuracy: ${variant.accuracy}`)
    console.log(`     Memory: ${variant.memory}`)
    console.log(`     Use case: ${variant.useCase}`)
    console.log()
  }

  console.log('🎯 Optimization Scripts:')
  console.log('  npm run download-models  # Download full models')
  console.log('  npm run compress-models  # Create optimized variants')
  console.log('  npm test                # Verify functionality')
  console.log()
}

/**
 * Show reliability comparison
 */
function showReliabilityComparison() {
  console.log('📊 Reliability Comparison')
  console.log('─'.repeat(25))

  const comparison = [
    ['Feature', 'Online Loading', 'Bundled Models'],
    ['─'.repeat(15), '─'.repeat(15), '─'.repeat(15)],
    ['Reliability', 'Network dependent', '100% offline ✅'],
    ['First load time', '30-60 seconds', '< 1 second ✅'],
    ['Subsequent loads', 'Cached (~1s)', '< 1 second ✅'],
    ['Package size', '~3KB ✅', '~25MB'],
    ['Network required', 'Yes (first time)', 'No ✅'],
    ['Offline support', 'Limited', 'Complete ✅'],
    ['Startup time', 'Variable', 'Consistent ✅'],
    ['Memory usage', 'Standard', 'Configurable ✅']
  ]

  for (const row of comparison) {
    console.log(`  ${row[0].padEnd(17)} ${row[1].padEnd(17)} ${row[2]}`)
  }
  console.log()
}

/**
 * Show when to use each approach
 */
function showWhenToUse() {
  console.log('🎯 When to Use Each Approach')
  console.log('─'.repeat(30))

  console.log('✅ Use Bundled Models When:')
  const bundledUseCases = [
    'Production applications requiring maximum reliability',
    'Offline or air-gapped environments',
    'Applications with strict SLA requirements',
    'Edge computing and IoT devices',
    'Development environments with unreliable internet'
  ]

  for (const useCase of bundledUseCases) {
    console.log(`  • ${useCase}`)
  }
  console.log()

  console.log('✅ Use Online Loading When:')
  const onlineUseCases = [
    'Development and prototyping',
    'Applications where package size matters',
    'Environments with reliable internet connectivity',
    'Applications that rarely use embeddings'
  ]

  for (const useCase of onlineUseCases) {
    console.log(`  • ${useCase}`)
  }
  console.log()
}

/**
 * Main demonstration
 */
async function runDemo() {
  try {
    await simulateOnlineModelLoadingProblems()
    await demonstrateBundledModelSolution()
    showPackageStructure()
    showUsageExamples()
    showCompressionFeatures()
    showReliabilityComparison()
    showWhenToUse()

    console.log('🎉 Summary')
    console.log('─'.repeat(10))
    console.log(
      'The @soulcraft/brainy-models package solves the original reliability'
    )
    console.log('issues by providing:')
    console.log()
    console.log('  ✅ Complete offline operation (no network dependencies)')
    console.log('  ✅ Fast, consistent loading times (< 1 second)')
    console.log('  ✅ Multiple optimized variants for different use cases')
    console.log('  ✅ Easy integration with existing Brainy applications')
    console.log('  ✅ Comprehensive documentation and examples')
    console.log()
    console.log('🚀 Ready for production use with maximum reliability!')
  } catch (error) {
    console.error('❌ Demo failed:', error)
    process.exit(1)
  }
}

// Run the demonstration
runDemo().catch(console.error)