### Changes:
- Introduced environment-independent WebStreams API compatibility:
- Added `initializeStreamClasses` for dynamic detection of WebStreams API support in browsers and Node.js.
- Implemented fallback mechanism with detailed error messages for unsupported environments.
- Ensured asynchronous initialization of stream classes without blocking module execution.
- Updated `SequentialPipeline`:
- Added `ensureStreamClassesInitialized` method to streamline WebStreams setup across operations.
- Enhanced `initialize` to parallelize stream classes and `BrainyData` initialization.
- Refactored WebSocket handlers (`createWebSocketHandler` and `createWebSocketStreams`) to support async stream initialization.
- Improved TypeScript typings for streams (`TransformStreamDefaultController`, `PipelineResult<unknown>`).
- Adjusted `ServerSearchConduitAugmentation`:
- Introduced dependency on `BrainyDataInterface` instead of direct `BrainyData` usage.
- Ensured `localDb` is set prior to initialization with an appropriate error message.
- Updated methods (`setLocalDb`, `getLocalDb`, and vector operations) to rely on `BrainyDataInterface`.
- Enhanced error handling and logging throughout streaming and augmentation processes.
### Purpose:
Improved cross-environment compatibility of WebStreams API, ensuring seamless usage in both browsers and Node.js. Refactored `ServerSearchConduitAugmentation` to decouple `BrainyData` dependency,
### Changes:
- Removed the `src/augmentations/llmAugmentations.ts` file:
- Contained cognition augmentations for creating, testing, exporting, and deploying LLM models.
- Included TensorFlow.js-based model configuration, training, testing, and deployment functionalities.
- Implemented various presets (`tiny`, `small`, `medium`, `large`) for simplified LLM model creation.
### Purpose:
This change removes legacy LLM-related augmentations and functionalities no longer relevant to the project's current focus, in alignment with the recent transition to TensorFlow-based embedding workflows. Cleaning up eliminates unused code and maintains a streamlined, up-to-date codebase.
Standardized documentation by adding a centered Brainy logo across README files, examples, and guides. Adjusted text formatting for consistency, improved alignment, and readability of feature descriptions and examples.
Implemented new simplified commands (`create-simple`, `train-simple`, `generate-simple`) for easier LLM model management. Added pre-configured model presets (`tiny`, `small`, `medium`, `large`) and enhanced options to streamline usage for beginners. Updated CLI and API documentation with detailed examples. Incremented version to 0.8.0.
Introduced `llm-augmentation.md`, detailing the creation, training, testing, exporting, and deployment of language models using Brainy's graph database. Added examples showcasing practical usage and pipeline integration. Included class implementations in `llmAugmentations.ts`.
Implemented WebSocketConduitAugmentation and WebRTCConduitAugmentation for syncing Brainy instances. Added comprehensive usage examples to showcase data synchronization via WebSocket and WebRTC.
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.
Deleted all Firestore augmentation, storage, sync implementations, and related type definitions. Removed the FirestoreSync example file as part of the cleanup for disabled Firestore functionality.
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.
Applied consistent indentation and line-breaking rules to code and text sections in `README.md`, ensuring better formatting and alignment for readability. No functional changes made.
