brainy/tests/setup.ts
David Snelling f898f0ce7b feat\!: migrate from TensorFlow.js to Transformers.js with ONNX Runtime
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.
2025-08-05 19:29:59 -07:00

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TypeScript

/**
* Simple test setup for Brainy library
* No direct TensorFlow references - patches are handled internally by Brainy
*/
import { beforeEach } from 'vitest'
// Define the test utilities type for reuse
type TestUtilsType = {
createTestVector: (dimensions: number) => number[]
timeout: number
}
// Extend global type definitions for both global and globalThis
declare global {
let testUtils: TestUtilsType | undefined
let __ENV__: any
}
// Explicitly declare globalThis interface to ensure TypeScript recognizes these properties
declare global {
interface globalThis {
testUtils?: TestUtilsType | undefined
__ENV__?: any
}
}
// Clean up between tests
beforeEach(() => {
// Clear any global state that might interfere with tests
if (typeof globalThis !== 'undefined' && globalThis.__ENV__) {
delete globalThis.__ENV__
}
if (typeof global !== 'undefined' && global.__ENV__) {
delete global.__ENV__
}
})
// Add simple test utilities to both global and globalThis for compatibility
const testUtilsObject = {
// Create a simple test vector with predictable values
createTestVector: (dimensions: number): number[] => {
return Array.from({ length: dimensions }, (_, i) => (i + 1) / dimensions)
},
// Standard timeout for async operations
timeout: 30000
}
global.testUtils = testUtilsObject
globalThis.testUtils = testUtilsObject
// Set a clear test environment flag for embedding system
globalThis.__BRAINY_TEST_ENV__ = true
if (typeof global !== 'undefined') {
(global as any).__BRAINY_TEST_ENV__ = true
}