Introduced `generateRandomGraph` method to create randomized graphs with configurable entity counts and types, supporting automated testing and experimentation. Enhanced metadata vectorization logic to handle various metadata formats reliably, ensuring compatibility and fallback mechanisms during embedding. Updated `README.md` with detailed feature descriptions and usage guides.
Enhanced the installation section with guidance on resolving TensorFlow.js dependency conflicts using `--legacy-peer-deps`. Added CLI autocomplete setup instructions to improve user experience. Suppressed specific TensorFlow.js Node.js backend warnings in the embedding utils. Updated dependencies to the latest versions.
Added a comprehensive command-line interface (CLI) for interacting with the Brainy vector database. The CLI supports various operations, including database initialization, adding/searching nouns, managing relationships, and querying database status. Enhanced type validation logic for nouns and verbs to ensure consistency and enforce default types for invalid inputs. Updated test scripts to verify type validation and edge cases.
Introduced configurable read-only mode for databases to restrict write operations. Added support for S3-compatible storage services, including Cloudflare R2, Amazon S3, and Google Cloud Storage. Updated `README.md` with usage examples and configuration details.
Commented out all Firestore-related code across the project, including sync, storage, and vector search features. Removed Firebase dependencies (`firebase`, `firebase-admin`) from `package.json`. Updated `README.md` to reflect the temporary unavailability of Firestore features.
Introduced Firestore vector search integration using `@firebase/firestore-vector-search`. Added support for restricting searches by specific noun types to optimize performance and relevance. Updated `README.md` to document the new functionality and usage examples.
Introduced `pluginLoader.ts` to enable loading and configuring augmentation plugins from external packages. Added `examples/externalPlugins.js` to demonstrate usage. Enhanced storage status reporting in `opfsStorage` and `BrainyData` with detailed storage capacity and usage methods. Updated README with an external plugin usage guide.
Added a new README section detailing how to import and use augmentation interfaces without pulling the entire library. Updated `package.json` exports to enable direct imports for augmentation types. Included example demonstrating custom augmentation implementation and usage.
Introduced a new README section explaining how to import graph types individually to enable tree shaking. Updated `package.json` exports to support direct graph type imports. Enhanced `GraphNoun` structure by adding optional `label` and `embeddedVerbs` properties while simplifying the `CreatorMetadata` interface.
Enhanced embedding functionality by introducing `createTensorFlowEmbeddingFunction` and `createSimpleEmbeddingFunction` for flexible text vectorization. Updated TensorFlow.js dependencies to be automatically included with the package. Added detailed examples and documentation in `README.md`. Improved error handling and refactored default embedding function implementation. Updated `package.json` dependencies.
Deleted augmentation pipeline examples and `.releaserc.json`, streamlining the repository by eliminating redundant example implementations and release automation files.
Changed `"private"` to `false` in package.json to allow publishing the package to npm. The `"access": "restricted"` setting ensures that access remains limited to @soulcraft organization members. Updated README to reflect the new configuration.
Changed package name and imports to use the @soulcraft scope. Updated `README.md` to reflect the use of a private npm package and added publishing/installing instructions. Configured `package.json` with `private: true` and restricted access for publishing. Updated demo link to the correct GitHub repository.
