Introduced `encode-image.js` to convert images to Base64 and create corresponding HTML `<img>` tags. Outputs a sample encoded result to `encoded-image.html`.
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`.
Added several badges for TypeScript, TensorFlow, and Cartographer. Expanded on iConduit augmentations with WebSocket and WebRTC details, revised feature descriptions, and introduced a related projects section. Updated examples for improved clarity.
Implemented a WebSocket API for real-time communication and REST API routes for CRUD operations on nouns and verbs. Added a server initialization script with WebSocket server integration and improved application structure with modularized routing and services.
Introduced a cloud deployment wrapper for Brainy supporting AWS Lambda, Google Cloud Run, and Cloudflare Workers. Added configuration options, deployment scripts, and API reference. Updated `README.md` with contribution guidelines and cloud deployment documentation.
Implemented WebSocketConduitAugmentation and WebRTCConduitAugmentation for syncing Brainy instances. Added comprehensive usage examples to showcase data synchronization via WebSocket and WebRTC.
Incremented version to 0.7.5 across `version.ts` and `README.md`. Introduced WebSocket and WebRTC conduit augmentations in codebase and documented usage examples thoroughly in `README.md`.
Rebranded from "Soulcraft Brainy" to "Brainy" throughout `README.md`. Improved readability by reformatting long paragraphs and restructuring lists for better clarity.
Upgraded minimum Node.js version from 18.0.0 to 23.11.0 across `README.md`, `package.json`, and `version.ts`. Optimized distance utilities and pipelines to leverage Node.js 23.11+ native performance improvements (e.g., `array.reduce`, WebStreams API). Incremented version to 0.7.4 for consistency.
Updated `README.md` to reflect version `0.7.3` with improved feature descriptions and scaling highlights. Enhanced the versioning script to automatically update the version badge in `README.md` for consistency. Incremented `version.ts` to `0.7.3`.
Enhanced the `README.md` with more engaging and user-friendly descriptions, highlighting Brainy's adaptability and intelligence. Introduced new sections detailing adaptive intelligence, data pipeline enhancements, and use case expansion. Removed outdated dependencies from `package-lock.json`. Updated `version.ts` to `0.7.2`.
Introduced a script to generate a `version.ts` file exporting the package version from `package.json`. This simplifies accessing version data in the CLI, especially for global installations. Included auto-generated `version.ts` in the project structure.
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.
Updated search methods to support `includeVerbs` for retrieving associated verbs in results. Enhanced edge creation to allow metadata embedding when no vector is provided. Improved query handling and vectorization logic for consistent processing.
Expanded the documentation to include comprehensive usage scenarios, advanced configurations, and clearer explanations of Brainy's capabilities. Improved formatting and structure for better readability and accessibility.
Added extensive configuration support for storage adapters, including S3-compatible storage (R2, Amazon S3, Google Cloud Storage). Introduced environment variable fallback for seamless cloud integration. Updated createStorage logic for improved compatibility. Implemented read-only mode to restrict write operations and provide a safer database configuration.
Added the `SequentialPipeline` class for structured augmentation execution. Integrated threading capabilities via the `THREADED` execution mode in `augmentationPipeline`. Enhanced WebSocket support for real-time data processing through pipelines.
Introduced new utilities for detecting execution environments (browser, Node.js, Web Worker) and checking threading availability. Added `workerUtils` for executing functions in Web Workers or Worker Threads seamlessly based on the environment.
