- 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.
