### Changes:
- **README Enhancements**:
- Added detection capabilities for browser, Node.js, and serverless environments with optimized configuration.
- Expanded details on adaptive storage strategies based on the detected environment.
- Included new information on the Model Control Protocol (MCP), including components like `BrainyMCPAdapter` and `MCPAugmentationToolset`.
- **Terminology Updates**:
- Replaced "restore sparse data" terminology with "import sparse data" in code samples and CLI commands for clarity (e.g., `importSparseData` method and `brainy import-sparse` command).
- Updated related examples for consistency with new term usage.
- **Cross-Environment Compatibility**:
- Highlighted dynamic imports and storage migration for seamless operation in different environments.
- Described augmented browser support and streamlined development practices.
- **MCP Documentation**:
- Detailed REST and WebSocket APIs for interacting with Brainy through MCP.
- Outlined configuration options like rate limiting and authentication for MCP services.
- **cloud-wrapper/README.md**:
- Added configuration details for MCP services, including specific usage of ports, API keys, and CORS settings.
- Expanded API scopes by introducing MCP-related endpoints for real-time and batch interactions.
### Purpose:
Enhanced documentation to reflect recent updates to environment detection, storage optimization, and MCP services. The changes improve clarity, usability, and developer understanding across environments and interaction protocols.
### Changes:
- Expanded cloud deployment section in `README.md`:
- Added detailed npm scripts for deploying to AWS, Google Cloud, and Cloudflare.
- Described script usage for each cloud platform.
- Included instructions for configuring environment variables in `cloud-wrapper/.env`.
- Linked to the Cloud Wrapper README for additional setup and API documentation.
### Purpose:
Improved clarity and usability of cloud deployment instructions by providing specific npm script commands and configuration guidance. This helps streamline the deployment process for users across multiple cloud platforms.
### Changes:
- Updated README.md:
- Refined the project description to highlight its lightweight and powerful nature.
- Enhanced feature list, replacing outdated entries with modern updates (e.g., TensorFlow integration replacing LLM creation).
- Included detailed installation and usage instructions for TensorFlow.js support and embedding workflows.
- Added "Usage Options" section to define different import methods and supported environments.
- Expanded "Backup and Restore" details, showcasing CLI and scripting examples.
- Introduced optimized HNSW indexing for large datasets.
- Replaced examples with a unified and simplified demonstration approach.
- Embedded advanced build and environment-specific configurations for better clarity.
- Removed outdated content related to language model generation, including LLM-related commands and examples.
- Added README.demo.md with full instructions for running the interactive demo.
### Purpose:
This update modernizes the documentation and focuses on Brainy’s current capabilities, simplifying onboarding for new users while removing deprecated features. It also streamlines project understanding, enabling developers to better utilize its features in diverse environments.
### Changes:
- Adjusted the main project description in `README.md` for a more engaging tone by adding "A fun" to emphasize the platform's appeal.
### Purpose:
This update aims to make the project description more approachable and engaging for potential users while maintaining clarity about its capabilities.
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.
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.
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.
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 `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.
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.
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.
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.
Deleted `examples/externalPlugins.js` and `pluginLoader.ts` as they are no longer used. Updated all `.ts` imports to `.js` across the codebase. Added `MemberOf` to `VerbType` and filtered disabled augmentations in `executeAugmentationPipeline`. Updated documentation to reflect new augmentation registration process. Removed deprecated `allowImportingTsExtensions` from `tsconfig.json`.
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 README to clarify the transition from a vector database to a combined Graph and Vector database, detailing support for graph entities, relationships, and full capabilities of the new data model. Updated examples and documentation accordingly.
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.
Introduced an augmentation event pipeline supporting multiple execution modes (e.g., SEQUENTIAL, PARALLEL). Added new Memory Augmentation type for versatile data storage/retrieval (e.g., fileSystem, in-memory, Firestore). Updated `README.md` with pipeline usage, examples, and augmentations reorganization. Included new demo files for augmentation examples.
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.
