- Refactored `applyTensorFlowPatch` in `textEncoding.ts` to introduce a unified `Platform` class supporting both Node.js and browser environments with native `TextEncoder`/`TextDecoder`.
- Modified global object handling to target `PlatformNode` in Node.js and `PlatformBrowser` in browser environments.
- Added `getTextEncoder` and `getTextDecoder` utility functions to simplify text encoding/decoding across platforms.
- Introduced `setup.ts` to apply environment patches before other modules load.
- Updated CLI entry points (`cli.ts`, `rollup.config.js`) to ensure patching precedes TensorFlow.js usage.
- Enhanced test coverage for TextEncoder compatibility with `test-fix.js`.
- Adjusted imports in `test-tensorflow-textencoder.ts` to align with the updated `./utils/textEncoding.js`.
- Streamlined constructor definitions in `Platform` for improved maintainability.
This update ensures robust compatibility for TensorFlow.js by patching and standardizing text encoding/decoding functionality across environments.
- Introduced `test-fallback-function.js` and `test-fallback-simple.js` to validate `executeInThread` fallback functionality with both named and anonymous compute-intensive functions.
- Added `test-tensorflow-textencoder.js` for TensorFlow.js and TextEncoder tests in a Node.js environment.
- Created `test-tensorflow-textencoder.html` for browser-based TensorFlow.js and TextEncoder tests.
- Implemented cross-environment test support in `cli-package/src/test-tensorflow-textencoder.ts` for CLI functionality.
- Enhanced `src/utils/embedding.ts`, `textEncoding.ts`, and `brainy-wrapper.js` to include updated global `TextEncoder` and `TextDecoder` utilities for compatibility and worker improvements.
- Standardized and expanded utility methods in `PlatformNode` for broader support, including `isFloat32Array` and `isTypedArray` checks.
- Updated Node.js requirement to `>= 24.4.0` across documentation and configuration files for compatibility improvements.
This update introduces comprehensive testing for fallback mechanisms, TensorFlow.js, and TextEncoder across multiple environments, ensuring robustness and compatibility.
