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.
- **Core Improvements**:
- Refactored logging functions into a unified `logger` method for consistent output across the library.
- Enabled the `forceMemoryStorage` option in `BrainyData` initialization for improved storage flexibility in tests and specific use cases.
- **TensorFlow.js and Environment Updates**:
- Clarified the dependency structure in `README.md` to emphasize bundled dependencies and remove legacy peer dependency instructions.
- Simplified and reformatted environment detection logic for better maintainability and readability.
- **Testing Enhancements**:
- Added `tests/package-size-limit.test.ts` to monitor and validate npm package size against defined thresholds.
- Updated `tests/environment.node.test.ts` and core tests to leverage `forceMemoryStorage` for better test setup standardization.
- Improved test isolation with expanded `globalThis` utility definitions and cleanup logic.
- **Documentation**:
- Added detailed best practices for debugging and organizing tests in `DEVELOPERS.md`.
- Removed outdated installation hints from `package.json` and streamlined scripts by including `test:size` for package size validation.
**Purpose**: These changes unify core logging mechanisms, expand configurability of storage options, and improve testing reliability and coverage. Documentation and clarity are enhanced to align with updated functionality and best practices.
- **Test Improvements**:
- Introduced data-clearing steps (`.clear()`) across critical test cases for ensuring better test isolation and preventing state leakage.
- Extended support for overriding global utilities (`testUtils`) and added fallback behaviors for test vector creation.
- **Configuration Updates**:
- Added support for `distanceFunction` as an alternative to `metric` in vector operations for consistency.
- Adjusted and unified asynchronous `timeout` handling across test suites for predictability.
- **Purpose**:
- These updates improve reliability, maintainability, and clarity in test cases while ensuring compatibility across diverse test environments.
- **New Tests Added**:
- Introduced multiple test suites covering core functionalities (`core.test.ts`), vector operations (`vector-operations.test.ts`), Node.js environment (`environment.node.test.ts`), browser setup (`environment.browser.test.ts`), and TensorFlow.js-specific behaviors (`tensorflow-patch.test.ts`).
- Added performance, scalability, and error-handling tests to ensure robust validation of vector addition, search, and text embedding functionalities.
- Introduced setup utilities (`tests/setup.ts`) and standardized test utilities for creating predictable test cases.
- **Configuration**:
- Created `vitest.config.ts` for custom test configurations, including support for modern test environments (`jsdom`, `happy-dom`) and extended timeouts for asynchronous operations.
- **Validation**:
- Includes compatibility checks for TensorFlow.js imports and ensures proper handling of `TextEncoder`/`TextDecoder` in Node.js environments.
This commit significantly enhances the testing coverage and structure, ensuring Brainy functionality is robust, cross-platform, and aligned with evolving reliability standards.
