- Added support for field-specific and prioritized searches in `brainyData`:
- Introduced `searchField` option to enable targeted field-level searches.
- Implemented `priorityFields` option for weighted vectorization and query relevance.
- Developed utilities in `jsonProcessing.ts` and `fieldNameTracking.ts`:
- `extractTextFromJson` for text extraction with customizable depth and field prioritization.
- `extractFieldFromJson` to target specific fields in JSON documents.
- `prepareJsonForVectorization` for optimized JSON vectorization.
- Enhanced management of field names and mappings:
- Integrated `trackFieldNames` to associate fields with their services.
- Supported cross-service consistency through `standardFieldMappings`.
- Updated documentation:
- Added detailed guides for JSON search enhancements and HNSW limitations.
- Extended usage examples in `README.md` and `json-search-test.js`.
- Verified improvements with comprehensive tests:
- Created unit and integration tests demonstrating search behavior improvements.
- Addressed previous TypeScript errors related to search parameters.
**Purpose**: Improve search accuracy and usability when working with complex JSON documents by enabling field-specific searches and enhancing contextual relevance.
- **Core**: Introduced a new `getStatistics` utility function in `statistics.ts` for fetching database statistics at the root level of the library. Enhanced `BrainyData` methods to ensure metadata includes `id` field and refined statistics calculations, excluding verbs from the noun count.
- **Tests**: Added comprehensive test coverage in `statistics.test.ts` for the new utility function, validating proper error handling, statistics accuracy, and consistent results between instance methods and standalone function.
- **Storage Config**: Enabled dynamic support for AWS S3, Cloudflare R2, and Google Cloud Storage in web service configuration, utilizing environment variables for adapter setup. Addressed a race condition in `FileSystemStorage` initialization by deferring path module imports.
**Purpose**: Enhance database analytics by introducing a reusable `getStatistics` function, improve flexibility in storage configuration, and ensure robust testing for reliability and accuracy.
- 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.
