- **Scripts**:
- Refactored logging within `release-workflow.js` for improved readability and maintainability.
- Added a fallback mechanism in `download-full-models.js` to inject the "format" field into `model.json` for TensorFlow.js compatibility.
- **Documentation**:
- Updated `README.md` with a redesigned structure:
- Enhanced readability using emojis and a cleaner presentation.
- Expanded `Overview`, `Features`, and `Quick Start` sections.
- Refined "Use Cases" and added better explanations for bundled model benefits.
- **Models**:
- Adjusted `model.json` to include the "format" field for compatibility with TensorFlow.js.
- Updated `metadata.json` with a recent download timestamp.
**Purpose
- Introduced `@soulcraft/brainy-models` package with pre-bundled TensorFlow models for enhanced offline reliability.
- Added `index.d.ts` and `index.js` allowing offline embedding workflows with the Universal Sentence Encoder model.
- Included utility scripts for model compression, size retrieval, and availability checks.
- Added `metadata.json` and `model.json` defining the Universal Sentence Encoder configuration with offline bundling.
- Ensured comprehensive model documentation, error handling, and robust logging for seamless integration.
- Supported optional model quantization placeholders for future TensorFlow.js enhancements.
**Purpose**: Enable fully offline-ready embedding workflows via pre-bundled Universal Sentence Encoder models, ensuring maximum reliability and air-gapped environment compatibility.
- Removed `demo-optional-model-bundling.js`:
- Obsolete demonstration of model bundling and offline loading.
- Replaced by comprehensive documentation and tools in `@soulcraft/brainy-models`.
- Added `create-github-release.js`:
- Automates GitHub release creation for `@soulcraft/brainy-models-package`.
- Includes features for generating release notes, tagging, and uploading with GitHub CLI.
- Updated `package-lock.json`:
- Reflects new dependencies and updates for GitHub release automation.
**Purpose**: Streamline repository by removing redundant scripts and introducing automated GitHub release workflows for efficient version management.
- Added new scripts under `brainy-models-package/scripts`:
- **`compress-models.js`**: Implements model compression with float16 and int8 precision to create optimized variants of Universal Sentence Encoder models.
- **`download-full-models.js`**: Downloads the complete Universal Sentence Encoder model for offline usage.
- **`download-model.js`**: Downloads reference files for TensorFlow Hub-based Universal Sentence Encoder.
- Introduced a demonstration script:
- **`demo-optional-model-bundling.js`**: Highlights the solution of bundling models to eliminate network dependency, ensuring reliability and offline capability.
- Key Features:
- **Compression**:
- Reduced model size with float16 (balanced precision and size) and int8 (low-memory environments) options.
- Generated compression summaries for quick insights into model variants and saved space.
- **Offline Reliability**:
- Bundled versions eliminate first-load delays, network dependencies, and failures.
- Ensures rapid initialization in offline and memory-constrained scenarios.
- **Dynamic Optimization**:
- Tailored optimization profiles for various use cases: general, low-memory, and high-performance.
- **Demonstration and Documentation**:
- Comprehensive demo showcasing benefits of bundled models over online loading.
- Examples for usage, testing, and integration with Brainy.
**Purpose**: Introduce essential scripts and tools to enable efficient, offline-ready model usage, streamlining the embedding workflow while ensuring reliability in production and resource-constrained environments.
