- **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- Removed outdated installation hints from `package.json` and streamlined scripts by including `test:size` for package size validation.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.
- **Vector Handling Updates**:
- Added a `dimensions` property to `BrainyDataConfig` for specifying vector dimensions.
- Introduced validation for vector dimensions during database creation and insertion to ensure consistency.
- Enhanced error handling and logging for dimension mismatches.
- **Model Loading Improvements**:
- Implemented retry logic for Universal Sentence Encoder model loading to handle network instability and JSON parsing errors gracefully.
- Improved logging and debugging support for failures during model initialization and embedding operations.
- **Compatibility Enhancements**:
- Updated polyfills to support TensorFlow.js compatibility across diverse server environments (Node.js, serverless, etc.).
- Introduced and refactored global `TextEncoder`/`TextDecoder` definitions for seamless operation in non-browser environments.
- Simplified TensorFlow.js backend setup with streamlined imports and logging for GPU/WebGL fallback.
- **Purpose**:
- These updates improve BrainyData's robustness, enforce correct vector usage, and extend compatibility with varied runtime environments. The changes enhance the usability, reliability, and cross-platform readiness of core functionalities.
- Removed obsolete scripts: `test-all-environments.js`, `test-fallback-function.js`, `test-fallback-simple.js`, `test-fix.js`, `test-tensorflow-textencoder.js`, `test-unified-encoding.js`, and `test-worker-utils.js`.
- Introduced `scripts/comprehensive-test.js` as a unified testing script covering all environments: Browser, Node.js, and CLI.
- Added `examples/cli-wrapper-example.js` to demonstrate a proper CLI implementation with TensorFlow.js initialization.
This refactor simplifies the testing structure by consolidating redundant scripts into a single comprehensive script while ensuring robust cross-environment coverage.
- 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.
- Removed outdated Node.js v24 compatibility patches for `TextEncoder` and `TextDecoder` in `cli-wrapper.js` and other modules since TensorFlow.js now supports Node.js v24+ natively.
- Introduced a utility module `src/utils/tensorflowUtils.ts` for TensorFlow.js compatibility, defining global `PlatformNode` and related utilities.
- Enhanced `fileSystemStorage.ts` with improved Node.js module loading mechanisms for better compatibility across environments.
- Simplified dependency requirements by reducing the minimum Node.js version to `>=23.0.0`.
- Updated `package.json`, `cli-package/package.json`, and `README.md` versions to `0.9.25`.
- Harmonized `cli-package` and main package dependencies to ensure version alignment.
- Improved global compatibility with TensorFlow.js in mixed Node.js environments.
This update modernizes TensorFlow.js integration, reduces maintenance efforts, and aligns compatibility with current Node.js and TensorFlow.js capabilities.
- Refactored function signature to include line breaks for enhanced readability and adherence to style guidelines.
- No functional changes introduced, ensuring consistent behavior.
These adjustments improve code clarity and maintain alignment with project formatting standards.
- Updated `findUSELoadFunction` return type for better type safety and clarity.
- Enhanced load function detection logic with improved readability and consistency.
- Applied formatting adjustments, such as line breaks and removal of redundant semicolons, to adhere to coding standards.
These changes ensure stronger type enforcement, align with project style guidelines, and improve maintainability of Universal Sentence Encoder initialization logic.
- Added batch embedding support with `defaultBatchEmbeddingFunction`, leveraging shared model instances for optimized performance.
- Integrated `isInitializing` flag to prevent recursive initialization and ensure smooth concurrent operation handling during `BrainyData` initialization.
- Pre-loaded Universal Sentence Encoder in `BrainyData` to prevent delays during embedding.
- Introduced fallback mechanisms in embedding initialization for better error resiliency and model reusability.
- Updated `addBatch` with support for batchSize and refactored text/vector processing logic for clearer separation and memory management.
- Improved GPU and CPU backend selection in Universal Sentence Encoder for compatibility across environments.
- Enhanced memory management by cleaning tensors after embedding operations.
- Updated README with instructions for batch embedding, threading updates, and GPU/CPU optimizations.
- Integrated GPU acceleration via WebGL in `embedding.ts` and `distance.ts` for optimized performance.
- Enhanced fallback mechanisms for CPU processing when GPU is unavailable or fails to initialize.
- Added threading support for embedding and distance calculations in `embedding.ts` and `distance.ts` to improve performance and avoid blocking the main thread.
- Refactored TensorFlow.js imports to dynamically load modules (`@tensorflow/tfjs-core`, `@tensorflow/tfjs-backend-webgl`, `@tensorflow/tfjs-backend-cpu`) for modular dependency usage.
- Introduced GPU-accelerated batch distance calculations in `distance.ts` with appropriate error handling.
- Applied consistent formatting to improve code readability and maintainability while adhering to project style guidelines.
