brainy/scripts
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
..
development **chore(scripts): add utility scripts and demo for database checks, CLI handling, and model bundling** 2025-08-01 16:23:15 -07:00
maintenance **chore(scripts): add utility scripts and demo for database checks, CLI handling, and model bundling** 2025-08-01 16:23:15 -07:00
check-code-style.js feat(scripts, project): add comprehensive code style enforcement script and update style-related workflows 2025-06-30 09:51:53 -07:00
claude-commit.sh feat(tools): add claude-commit AI-powered git commit tool 2025-08-04 10:14:33 -07:00
create-favicon.js **feat(cli, workers): introduce text encoding patches and worker improvements** 2025-07-04 14:42:33 -07:00
create-github-release.js **chore(release): bump version to 0.10.0 and refactor project structure** 2025-07-07 10:19:04 -07:00
download-model.js **feat(models): add scripts for model compression, bundling, and optimization** 2025-08-01 15:35:08 -07:00
download-models.cjs feat\!: migrate from TensorFlow.js to Transformers.js with ONNX Runtime 2025-08-05 19:29:59 -07:00
encode-image.js Initial commit 2025-06-24 11:41:30 -07:00
extract-models.js refactor: simplify build system and improve model loading flexibility 2025-08-05 16:09:30 -07:00
patch-textencoder.js **chore(release): bump version to 0.10.0 and refactor project structure** 2025-07-07 10:19:04 -07:00
publish-cli.js **chore: remove unused CLI and utility files** 2025-08-02 17:22:49 -07:00
release-workflow.js **refactor(scripts): improve readability and consistency in release-workflow.js** 2025-08-01 17:33:28 -07:00
update-readme.js Initial commit 2025-06-24 11:41:30 -07:00