- Added `getFile` method to `FileSystemHandle` interface for enhanced TypeScript compatibility with File System Access API.
- Improved maintainability by reformatting and aligning imports in `brainyData.ts`.
- Standardized spacing and indentation across structured comments and interface fields.
Purpose: Improve TypeScript support for file system operations and enhance code readability with consistent formatting and import management.
- Refactor embedding functions to support customizable verbosity through new helper methods (`getDefaultEmbeddingFunction`, `getDefaultBatchEmbeddingFunction`).
- Ensure metadata initialization with default values when null during search results.
- **Logging Cleanup**:
- Removed redundant `console.log` statements in `brainyData.ts` and `embedding.ts` related to Universal Sentence Encoder initialization and load function detection.
- Replaced detailed logs with concise comments to streamline debugging and reduce noisy outputs.
- **Purpose**:
- Improves code readability, reduces runtime logging noise, and aligns logging verbosity with the project's streamlined debugging 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.
- Applied consistent formatting improvements, including line breaks, parentheses usage, and object destructuring, to enhance code readability and maintainability.
- Enhanced the fallback mechanism during Universal Sentence Encoder initialization by implementing a retry approach with error handling.
- Refactored `addBatch` processing for both vector and text items to improve clarity and adhere to project coding standards.
- Optimized initialization safeguards with structured retry implementations, ensuring robust error resiliency.
These changes align the codebase with established formatting guidelines and improve the reliability of embedding initialization processes.
- 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.
Applied consistent formatting adjustments across `src/brainyData.ts`, including line breaks, parentheses, and object destructuring. These changes enhance code readability, maintainability, and alignment with the project's style guidelines without altering functionality.
