David Snelling
52a43d51d4
- Remove Rollup bundling in favor of direct TypeScript compilation - Move from bundled models to dynamic model loading with configurable paths - Add Docker deployment examples and documentation - Implement robust model loader with fallback mechanisms - Update storage adapters for better cross-environment compatibility - Add comprehensive tests for model loading and package installation - Simplify package.json scripts and remove complex build configurations - Clean up deprecated demo files and old bundling scripts BREAKING CHANGE: Models are no longer bundled with the package. They are now loaded dynamically from CDN or custom paths.
86 lines
No EOL
2.7 KiB
JavaScript
86 lines
No EOL
2.7 KiB
JavaScript
#!/usr/bin/env node
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/**
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* Example Brainy application for Docker deployment
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* Demonstrates custom models path usage
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*/
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import { BrainyData } from '@soulcraft/brainy'
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async function main() {
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console.log('🚀 Starting Brainy Docker Example App...')
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console.log(`Environment: ${process.env.NODE_ENV || 'development'}`)
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console.log(`Models Path: ${process.env.BRAINY_MODELS_PATH || 'default (node_modules)'}`)
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const db = new BrainyData({
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forceMemoryStorage: true,
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dimensions: 512,
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// Don't skip embeddings - let it try to load models
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skipEmbeddings: false
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})
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try {
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console.log('\n📊 Initializing BrainyData...')
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await db.init()
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console.log('✅ BrainyData initialized successfully!')
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// Add some test data
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console.log('\n📝 Adding test data...')
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const testItems = [
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'Artificial intelligence is transforming the world',
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'Machine learning enables computers to learn without being explicitly programmed',
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'Docker containers provide a consistent environment for applications',
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'Cloud deployment makes applications scalable and reliable'
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]
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const ids = []
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for (const text of testItems) {
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const id = await db.add({ content: text })
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ids.push(id)
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console.log(` Added: "${text}" (ID: ${id})`)
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}
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// Search for similar content
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console.log('\n🔍 Searching for AI-related content...')
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const searchResults = await db.search('artificial intelligence and machine learning', 2)
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console.log(`Found ${searchResults.length} results:`)
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searchResults.forEach((result, index) => {
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console.log(` ${index + 1}. "${result.content}" (Score: ${result.similarity?.toFixed(3)})`)
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})
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// Get database statistics
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console.log('\n📈 Database Statistics:')
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const stats = await db.getStatistics()
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console.log(` Total items: ${stats.totalVectors}`)
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console.log(` Storage type: ${stats.storageType}`)
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console.log(` Index type: ${stats.indexType}`)
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} catch (error) {
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console.error('❌ Error:', error.message)
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console.error('\n💡 Troubleshooting tips:')
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console.error(' 1. Ensure models are available in BRAINY_MODELS_PATH')
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console.error(' 2. Check that @soulcraft/brainy-models is installed')
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console.error(' 3. Verify network connectivity for remote model loading')
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process.exit(1)
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}
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console.log('\n🎉 Example completed successfully!')
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}
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// Handle graceful shutdown
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process.on('SIGINT', () => {
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console.log('\n👋 Shutting down gracefully...')
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process.exit(0)
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})
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process.on('SIGTERM', () => {
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console.log('\n👋 Received SIGTERM, shutting down...')
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process.exit(0)
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})
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// Run the example
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main().catch(error => {
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console.error('Fatal error:', error)
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process.exit(1)
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}) |