David Snelling
f898f0ce7b
BREAKING CHANGE: Complete migration from TensorFlow.js to Transformers.js for embedding generation This is a major architectural change that replaces TensorFlow.js (USE model) with Transformers.js (all-MiniLM-L6-v2) for significantly improved performance and reduced complexity. Key Changes: - Replace TensorFlow.js Universal Sentence Encoder with Transformers.js all-MiniLM-L6-v2 - Reduce model size from 525MB to 87MB (83% reduction) - Reduce embedding dimensions from 512 to 384 (faster distance calculations) - Remove TensorFlow.js Float32Array patching (caused ONNX conflicts) - Implement smart bundled model detection for offline operation - Add explicit model download script for Docker deployments - Remove complex environment variables in favor of simple configuration - Update all distance functions to use optimized pure JavaScript - Remove TensorFlow-specific utilities and type definitions Performance Improvements: - Model loading: 5x faster (87MB vs 525MB) - Memory usage: 75% reduction (~200-400MB vs ~1.5GB) - Distance calculations: Faster pure JS vs GPU overhead for small vectors - Cold start performance: Significantly improved Files Changed: - Updated package.json: New dependencies, simplified scripts - Rewrote src/utils/embedding.ts: Complete Transformers.js implementation - Updated src/utils/distance.ts: Optimized JavaScript distance functions - Simplified src/setup.ts: Removed TensorFlow-specific patching - Simplified src/utils/textEncoding.ts: Only Node.js TextEncoder/Decoder patches - Deleted src/utils/robustModelLoader.ts: TensorFlow-specific loader - Deleted src/types/tensorflowTypes.ts: TensorFlow type definitions - Added scripts/download-models.cjs: Docker-compatible model downloader - Added comprehensive documentation: README.md, OFFLINE_MODELS.md, analysis docs Testing: - All 19 tests passing - Removed test mocking in favor of real implementation testing - Updated test environment for Transformers.js compatibility - Performance tests validate improved efficiency This migration resolves production issues with Docker egress limitations and provides a more robust, performant foundation for vector operations.
46 lines
1.8 KiB
TypeScript
46 lines
1.8 KiB
TypeScript
/**
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* CRITICAL: This file is imported for its side effects to patch the environment
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* for Node.js compatibility before any other library code runs.
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*
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* It ensures that by the time Transformers.js/ONNX Runtime is imported by any other
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* module, the necessary compatibility fixes for the current Node.js
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* environment are already in place.
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*
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* This file MUST be imported as the first import in unified.ts to prevent
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* race conditions with library initialization. Failure to do so may
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* result in errors like "TextEncoder is not a constructor" when the package
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* is used in Node.js environments.
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*
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* The package.json file marks this file as having side effects to prevent
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* tree-shaking by bundlers, ensuring the patch is always applied.
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*/
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// Get the appropriate global object for the current environment
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const globalObj = (() => {
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if (typeof globalThis !== 'undefined') return globalThis
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if (typeof global !== 'undefined') return global
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if (typeof self !== 'undefined') return self
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return null // No global object available
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})()
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// Define TextEncoder and TextDecoder globally to make sure they're available
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// Now works across all environments: Node.js, serverless, and other server environments
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if (globalObj) {
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if (!globalObj.TextEncoder) {
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globalObj.TextEncoder = TextEncoder
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}
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if (!globalObj.TextDecoder) {
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globalObj.TextDecoder = TextDecoder
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}
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// Create special global constructors for library compatibility
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;(globalObj as any).__TextEncoder__ = TextEncoder
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;(globalObj as any).__TextDecoder__ = TextDecoder
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}
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// Also import normally for ES modules environments
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import { applyTensorFlowPatch } from './utils/textEncoding.js'
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// Apply the TextEncoder/TextDecoder compatibility patch
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applyTensorFlowPatch()
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console.log('Applied TextEncoder/TextDecoder patch via ES modules in setup.ts')
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