- Introduced `CONCURRENCY_ANALYSIS.md` to outline identified concurrency issues, including statistics handling, index synchronization, and storage contention.
- Added `CONCURRENCY_IMPLEMENTATION_SUMMARY.md` to summarize concurrency improvements, such as distributed locking and change log mechanisms.
- Created `STORAGE_CONCURRENCY_ANALYSIS.md` to evaluate concurrency risks and applied solutions for different storage adapters (`S3CompatibleStorage`, `FileSystemStorage`, `OPFSStorage`, and `MemoryStorage`).
- Updated codebase with changes related to concurrency, including distributed locking, atomic updates, event-driven synchronization, and change log support.
- Refactored tests to verify behavior of new concurrency mechanisms, including robust error handling and cleanup functions.
**Purpose**: Provides comprehensive documentation and implementation details to ensure robust concurrency handling in multi-instance, high-throughput environments.
- **Removed Files**:
- Deleted outdated statistics documentation files (`statistics.md`, `statistics-flush-solution.md`, `statistics-summary.md`) to clean up the repository and avoid confusion.
- **Added Standards**:
- Introduced `DOCUMENTATION_STANDARDS.md` to outline naming conventions and troubleshooting practices for more consistent and maintainable project documentation.
- **Tests**:
- Added a new test file `edge-cases.test.ts` to verify handling of edge cases, ensuring robust behavior against boundary values and invalid inputs.
**Purpose**: Cleans up deprecated documentation while introducing concrete standards for maintaining and updating documentation. Enhances test coverage for unusual or boundary inputs, improving overall system resilience.
- **Core**:
- Added `check-database.js` to verify database status and validate search functionality.
- Created `fix-dimension-mismatch.js` to handle re-embedding of existing data to resolve dimension mismatch from 3 to 512.
- Improved test cases by updating vector operations to support 512 dimensions, replacing previously hardcoded dimensions.
- **Migration**:
- Developed `DIMENSION_MISMATCH_SUMMARY.md`, detailing the root cause, solution, and preventive strategies for dimension mismatch issues.
- Added `production-migration-guide.md` for structured production migration with detailed steps on re-embedding strategies, batching, and error handling.
- **Tests**:
- Enhanced test coverage with 512-dimensional vector validation.
- Introduced helper functions for consistent vector testing behavior and streamlined search test cases.
- **Documentation**:
- Updated project documentation to highlight the resolution process for dimension mismatches, emphasizing preventive mechanisms such as auto-migration and version tracking.
**Purpose**: Address critical dimension mismatch issues caused by embedding changes, restore functionality, and provide a roadmap for robust prevention strategies and migration processes.
- **Examples**: Added a new `flush-statistics-example.js` script to demonstrate the usage of the `flushStatistics` method for ensuring updated statistics after data insertion.
- **Core**:
- Implemented `flushStatistics` in the `BrainyData` class to allow immediate flushing of statistics to storage.
- Updated `BaseStorageAdapter` with `flushStatisticsToStorage` to support flushing cached statistics.
- Modified the `shutDown` method to ensure statistics are flushed before database shutdown.
- **Documentation**: Added `statistics-flush-solution.md` to explain the batch update mechanism, the issue with delayed statistics updates, and how to manually flush statistics in storage.
**Purpose**: Provide users with the ability to manually flush statistics for real-time accuracy, particularly useful for systems relying on immediate updates. Improved documentation and examples to guide developers in implementing and using this functionality effectively.
- **Core**: Improved verb creation logic by adding `createdAt`, `updatedAt`, and `createdBy` attributes. These fields include timestamped metadata (`seconds`, `nanoseconds`) and source augmentation/service information for better tracking.
- **Storage**: Refactored `BaseStorage` methods to utilize internal variants (e.g., `saveVerb_internal`, `getNoun_internal`). Added support for new verb attributes while maintaining backward compatibility with existing data structures.
- **Tests**:
- Updated `s3-storage.test.ts` and `opfs-storage.test.ts` to validate changes in verb attributes such as timestamps and augmentation metadata.
- Added assertions for `createdAt`, `updatedAt`, and `createdBy` fields in test cases.
- **Cleanup**: Replaced ambiguous type aliases like `Edge` and `HNSWNode` with clearer equivalents (`Verb` and `HNSWNoun_internal`) for consistency across storage adapters.
**Purpose**: Enhance metadata tracking and standardize attribute handling across storage and core modules to ensure accurate and consistent data throughout the system.
- **Code Cleanup**: Removed unnecessary trailing whitespaces across `src/brainyData.ts`. Adjusted formatting for inline object spreads to maintain a consistent coding style.
- **Purpose**: Enhance code readability and ensure adherence to formatting standards without altering functionality.
- **Core**: Introduced a `getCurrentAugmentation` method for detecting active augmentation names. Updated metadata handling to include `createdBy`, `createdAt`, and `updatedAt` attributes for improved tracking.
- **Storage**: Added support for service-based statistics tracking with new methods such as `incrementStatistic`, `decrementStatistic`, and `updateHnswIndexSize`. Implemented persistence for statistics in storage adapters.
- **Statistics**: Enhanced `getStatistics` functionality to provide service-specific breakdowns and support filtering by services. Improved noun, verb, and metadata tracking mechanisms.
- **Search**: Added `service` option to filter results during searches for nouns, verbs, and metadata, ensuring accurate service-based query results.
- **Refactor**: Simplified search logic by integrating HNSW index filtering for better performance when retrieving service-specific results.
- **Tests**: Added comprehensive test coverage for service-level statistics and filtering by service.
**Purpose**: Improve service-level data tracking and analytics while enhancing functionality for filtering and maintaining metadata accuracy to support detailed insights for diverse use cases.
- **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.
- **New Method**:
- Introduced a new `getStatistics` method in `brainyData.ts` to retrieve key database metrics:
- Counts for nouns, verbs, metadata entries, and HNSW index size.
- **Error Handling**:
- Added try-catch blocks to ensure robust error management when fetching metadata or logging failures.
- **Purpose**:
- Enhances observability of the database state, providing valuable insights for diagnostics and monitoring.
- Added `autoCreateMissingNouns` and `missingNounMetadata` options to the `addVerb` method in `brainyData.ts`, enabling automatic creation of missing source or target nouns.
- Improved error handling and logging for auto-creation failures, ensuring better feedback during runtime.
- Reformatted existing code for storage options validation to improve readability and maintain consistency.
**Purpose**: Simplify the addition of relationships by automating the process for non-existing nouns and enhance developer experience with better error handling and logging.
- 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.
