chore: update README.md and docs with Brainy logo and enhanced formatting

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.

CONTRIBUTING.md

@@ -1,11 +1,17 @@
+<div align="center">
+<img src="brainy.png" alt="Brainy Logo" width="200"/>
+
 # Contributing to Soulcraft Brainy
 
+</div>
+
 Thank you for your interest in contributing to Soulcraft Brainy! This document provides guidelines and instructions for
 contributing to the project.
 
 ## Commit Message Guidelines
 
-When contributing to this project, please write clear and descriptive commit messages that explain the purpose of your changes. Good commit messages help maintainers understand your contributions and make the review process smoother.
+When contributing to this project, please write clear and descriptive commit messages that explain the purpose of your
+changes. Good commit messages help maintainers understand your contributions and make the review process smoother.
 
 ### Best Practices
 

README.md

@@ -1,14 +1,11 @@
 <div align="center">
 
-# 🧠 Brainy
+<img src="brainy.png" alt="Brainy Logo" width="200"/>
 
 [![License](https://img.shields.io/badge/license-MIT-green.svg)](LICENSE)
 [![Node.js](https://img.shields.io/badge/node-%3E%3D23.11.0-brightgreen.svg)](https://nodejs.org/)
 [![TypeScript](https://img.shields.io/badge/TypeScript-5.1.6-blue.svg)](https://www.typescriptlang.org/)
-[![npm package](https://img.shields.io/badge/npm-@soulcraft/brainy-blue)](https://www.npmjs.com/package/@soulcraft/brainy)
 [![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg)](CONTRIBUTING.md)
-[![code style: prettier](https://img.shields.io/badge/code_style-prettier-ff69b4.svg)](https://github.com/prettier/prettier)
-[![TensorFlow](https://img.shields.io/badge/TensorFlow-4.22.0-orange.svg)](https://www.tensorflow.org/)
 [![Cartographer](https://img.shields.io/badge/Cartographer-Official%20Standard-brightgreen)](https://github.com/sodal-project/cartographer)
 
 **A powerful, lightweight vector & graph database for browsers and Node.js**
@@ -35,7 +32,8 @@ and connections.
 - **Extensible Augmentations** - Customize and extend functionality with pluggable components (LEGO blocks for your
   data!)
 - **Built-in Conduits** - Sync and scale across instances with WebSocket and WebRTC (your data's teleportation system!)
-- **LLM Creation & Training** - Build, train, and deploy language models from your graph data (your own personal AI factory!)
+- **LLM Creation & Training** - Build, train, and deploy language models from your graph data (your own personal AI
+  factory!)
 - **Adaptive Intelligence** - Automatically optimizes for your environment and usage patterns
 - **Cross-Platform** - Works everywhere you do: browsers, Node.js, and server environments
 - **Persistent Storage** - Data persists across sessions and scales to any size (no memory loss here, even for
@@ -181,19 +179,21 @@ Brainy uses a powerful augmentation system to extend functionality. Augmentation
     - Analyzes relationships between entities
     - Creates and trains language models from graph data
     - Examples:
-      - Inferring new connections between existing data
+        - Inferring new connections between existing data
-      - Building custom LLMs from your nouns and verbs
+        - Building custom LLMs from your nouns and verbs
 
 4. **CONDUIT** 🔌
     - Establishes high-bandwidth channels for structured data exchange
     - Connects with external systems and syncs between Brainy instances
     - Two built-in iConduit augmentations for scaling out and syncing:
-      - **WebSocket iConduit** - Syncs data between browsers and servers (like a digital postal service with superpowers!)
+        - **WebSocket iConduit** - Syncs data between browsers and servers (like a digital postal service with
-      - **WebRTC iConduit** - Direct peer-to-peer syncing between browsers (like telepathy for your data, no middleman required!)
+          superpowers!)
+        - **WebRTC iConduit** - Direct peer-to-peer syncing between browsers (like telepathy for your data, no middleman
+          required!)
     - Examples:
-      - Integrating with third-party APIs
+        - Integrating with third-party APIs
-      - Syncing Brainy instances between browsers using WebSockets
+        - Syncing Brainy instances between browsers using WebSockets
-      - Peer-to-peer syncing between browsers using WebRTC
+        - Peer-to-peer syncing between browsers using WebRTC
 
 5. **ACTIVATION** ⚡
     - Initiates actions, responses, or data manipulations
@@ -524,65 +524,65 @@ await db.deleteVerb(verbId)
 ### Working with LLM Models
 
 ```typescript
-import { createLLMAugmentations } from '@soulcraft/brainy'
+import {createLLMAugmentations} from '@soulcraft/brainy'
 
 // Create LLM augmentations
-const { cognition, activation } = await createLLMAugmentations()
+const {cognition, activation} = await createLLMAugmentations()
 
 // Create a new LLM model
 const createResult = await cognition.createModel({
-  name: 'my-model',
+    name: 'my-model',
-  description: 'A simple LLM model trained on Brainy data',
+    description: 'A simple LLM model trained on Brainy data',
-  modelType: 'simple',
+    modelType: 'simple',
-  vocabSize: 5000,
+    vocabSize: 5000,
-  embeddingDim: 64,
+    embeddingDim: 64,
-  hiddenDim: 128,
+    hiddenDim: 128,
-  numLayers: 1
+    numLayers: 1
 })
 
 const modelId = createResult.data.modelId
 
 // Train the model
 const trainResult = await cognition.trainModel(modelId, {
-  maxSamples: 100,
+    maxSamples: 100,
-  validationSplit: 0.2,
+    validationSplit: 0.2,
-  earlyStoppingPatience: 2
+    earlyStoppingPatience: 2
 })
 
 // Test the model
 const testResult = await cognition.testModel(modelId, {
-  testSize: 20,
+    testSize: 20,
-  generateSamples: true,
+    generateSamples: true,
-  sampleCount: 3
+    sampleCount: 3
 })
 
 // Generate text with the model
 const generateResult = await cognition.generateText(modelId, 'What is a', {
-  temperature: 0.7,
+    temperature: 0.7,
-  topK: 5
+    topK: 5
 })
 
 // Export the model
 const exportResult = await cognition.exportModel(modelId, {
-  format: 'json',
+    format: 'json',
-  includeMetadata: true,
+    includeMetadata: true,
-  includeVocab: true
+    includeVocab: true
 })
 
 // Deploy the model
 const deployResult = await cognition.deployModel(modelId, {
-  target: 'browser'
+    target: 'browser'
 })
 
 // Using the augmentation pipeline
 const pipelineResult = await augmentationPipeline.executeCognitionPipeline(
-  'createModel',
+    'createModel',
-  [{
+    [{
-    name: 'pipeline-model',
+        name: 'pipeline-model',
-    modelType: 'transformer',
+        modelType: 'transformer',
-    numHeads: 2,
+        numHeads: 2,
-    numLayers: 1
+        numLayers: 1
-  }]
+    }]
 )
 ```
 
@@ -682,9 +682,11 @@ Brainy can be deployed as a standalone web service on various cloud platforms us
 - **Google Cloud Run**: Deploy as a containerized service
 - **Cloudflare Workers**: Deploy as a serverless function on the edge
 
-The cloud wrapper provides both RESTful and WebSocket APIs for all Brainy operations, enabling both request-response and real-time communication patterns. It supports multiple storage backends and can be configured via environment variables.
+The cloud wrapper provides both RESTful and WebSocket APIs for all Brainy operations, enabling both request-response and
+real-time communication patterns. It supports multiple storage backends and can be configured via environment variables.
 
 Key features of the cloud wrapper:
+
 - RESTful API for standard CRUD operations
 - WebSocket API for real-time updates and subscriptions
 - Support for multiple storage backends (Memory, FileSystem, S3)
@@ -695,7 +697,8 @@ To get started with cloud deployment, see the [Cloud Wrapper README](cloud-wrapp
 
 ## 🔗 Related Projects
 
-- **[sodal-project cartographer](https://github.com/sodal-project/cartographer)** - The defacto standard for interacting with Brainy
+- **[sodal-project cartographer](https://github.com/sodal-project/cartographer)** - The defacto standard for interacting
+  with Brainy
 
 ## 📚 Examples
 
@@ -712,16 +715,19 @@ The repository includes several examples:
 
 You can use the conduit augmentations to sync Brainy instances:
 
-- **WebSocket iConduit**: For syncing between browsers and servers, or between servers (like a digital postal service with superpowers!). WebSockets cannot be used for direct browser-to-browser communication without a server in the middle.
+- **WebSocket iConduit**: For syncing between browsers and servers, or between servers (like a digital postal service
-- **WebRTC iConduit**: For direct peer-to-peer syncing between browsers (like telepathy for your data, no middleman required!). This is the recommended approach for browser-to-browser communication.
+  with superpowers!). WebSockets cannot be used for direct browser-to-browser communication without a server in the
+  middle.
+- **WebRTC iConduit**: For direct peer-to-peer syncing between browsers (like telepathy for your data, no middleman
+  required!). This is the recommended approach for browser-to-browser communication.
 
 #### WebSocket Sync Example
 
 ```typescript
 import {
-  BrainyData, 
+    BrainyData,
-  augmentationPipeline, 
+    augmentationPipeline,
-  createConduitAugmentation 
+    createConduitAugmentation
 } from '@soulcraft/brainy'
 
 // Create and initialize the database
@@ -736,36 +742,36 @@ augmentationPipeline.register(wsConduit)
 
 // Connect to another Brainy instance (server or browser)
 const connectionResult = await augmentationPipeline.executeConduitPipeline(
-  'establishConnection',
+    'establishConnection',
-  ['wss://your-websocket-server.com/brainy-sync', { protocols: 'brainy-sync' }]
+    ['wss://your-websocket-server.com/brainy-sync', {protocols: 'brainy-sync'}]
 )
 
 if (connectionResult[0] && (await connectionResult[0]).success) {
-  const connection = (await connectionResult[0]).data
+    const connection = (await connectionResult[0]).data
 
-  // Read data from the remote instance
+    // Read data from the remote instance
-  const readResult = await augmentationPipeline.executeConduitPipeline(
+    const readResult = await augmentationPipeline.executeConduitPipeline(
-    'readData',
+        'readData',
-    [{ connectionId: connection.connectionId, query: { type: 'getAllNouns' } }]
+        [{connectionId: connection.connectionId, query: {type: 'getAllNouns'}}]
-  )
+    )
 
-  // Process and add the received data to the local instance
+    // Process and add the received data to the local instance
-  if (readResult[0] && (await readResult[0]).success) {
+    if (readResult[0] && (await readResult[0]).success) {
-    const remoteNouns = (await readResult[0]).data
+        const remoteNouns = (await readResult[0]).data
-    for (const noun of remoteNouns) {
+        for (const noun of remoteNouns) {
-      await db.add(noun.vector, noun.metadata)
+            await db.add(noun.vector, noun.metadata)
+        }
     }
-  }
 
-  // Set up real-time sync by monitoring the stream
+    // Set up real-time sync by monitoring the stream
-  await wsConduit.monitorStream(connection.connectionId, async (data) => {
+    await wsConduit.monitorStream(connection.connectionId, async (data) => {
-    // Handle incoming data (e.g., new nouns, verbs, updates)
+        // Handle incoming data (e.g., new nouns, verbs, updates)
-    if (data.type === 'newNoun') {
+        if (data.type === 'newNoun') {
-      await db.add(data.vector, data.metadata)
+            await db.add(data.vector, data.metadata)
-    } else if (data.type === 'newVerb') {
+        } else if (data.type === 'newVerb') {
-      await db.addVerb(data.sourceId, data.targetId, data.vector, data.options)
+            await db.addVerb(data.sourceId, data.targetId, data.vector, data.options)
-    }
+        }
-  })
+    })
 }
 ```
 
@@ -773,9 +779,9 @@ if (connectionResult[0] && (await connectionResult[0]).success) {
 
 ```typescript
 import {
-  BrainyData, 
+    BrainyData,
-  augmentationPipeline, 
+    augmentationPipeline,
-  createConduitAugmentation 
+    createConduitAugmentation
 } from '@soulcraft/brainy'
 
 // Create and initialize the database
@@ -790,87 +796,88 @@ augmentationPipeline.register(webrtcConduit)
 
 // Connect to a peer using a signaling server
 const connectionResult = await augmentationPipeline.executeConduitPipeline(
-  'establishConnection',
+    'establishConnection',
-  [
+    [
-    'peer-id-to-connect-to', 
+        'peer-id-to-connect-to',
-    { 
+        {
-      signalServerUrl: 'wss://your-signal-server.com',
+            signalServerUrl: 'wss://your-signal-server.com',
-      localPeerId: 'my-peer-id',
+            localPeerId: 'my-peer-id',
-      iceServers: [{ urls: 'stun:stun.l.google.com:19302' }]
+            iceServers: [{urls: 'stun:stun.l.google.com:19302'}]
-    }
+        }
-  ]
+    ]
 )
 
 if (connectionResult[0] && (await connectionResult[0]).success) {
-  const connection = (await connectionResult[0]).data
+    const connection = (await connectionResult[0]).data
 
-  // Set up real-time sync by monitoring the stream
+    // Set up real-time sync by monitoring the stream
-  await webrtcConduit.monitorStream(connection.connectionId, async (data) => {
+    await webrtcConduit.monitorStream(connection.connectionId, async (data) => {
-    // Handle incoming data (e.g., new nouns, verbs, updates)
+        // Handle incoming data (e.g., new nouns, verbs, updates)
-    if (data.type === 'newNoun') {
+        if (data.type === 'newNoun') {
-      await db.add(data.vector, data.metadata)
+            await db.add(data.vector, data.metadata)
-    } else if (data.type === 'newVerb') {
+        } else if (data.type === 'newVerb') {
-      await db.addVerb(data.sourceId, data.targetId, data.vector, data.options)
+            await db.addVerb(data.sourceId, data.targetId, data.vector, data.options)
-    }
-  })
-
-  // When adding new data locally, also send to the peer
-  const nounId = await db.add("New data to sync", { noun: "Thing" })
-
-  // Send the new noun to the peer
-  await augmentationPipeline.executeConduitPipeline(
-    'writeData',
-    [
-      { 
-        connectionId: connection.connectionId, 
-        data: { 
-          type: 'newNoun',
-          id: nounId,
-          vector: (await db.get(nounId)).vector,
-          metadata: (await db.get(nounId)).metadata
         }
-      }
+    })
-    ]
+
-  )
+    // When adding new data locally, also send to the peer
+    const nounId = await db.add("New data to sync", {noun: "Thing"})
+
+    // Send the new noun to the peer
+    await augmentationPipeline.executeConduitPipeline(
+        'writeData',
+        [
+            {
+                connectionId: connection.connectionId,
+                data: {
+                    type: 'newNoun',
+                    id: nounId,
+                    vector: (await db.get(nounId)).vector,
+                    metadata: (await db.get(nounId)).metadata
+                }
+            }
+        ]
+    )
 }
 ```
 
 #### Browser-Server Search Example
 
-Brainy supports searching a server-hosted instance from a browser, storing results locally, and performing further searches against the local instance:
+Brainy supports searching a server-hosted instance from a browser, storing results locally, and performing further
+searches against the local instance:
 
 ```typescript
-import { BrainyData } from '@soulcraft/brainy'
+import {BrainyData} from '@soulcraft/brainy'
 
 // Create and initialize the database with remote server configuration
 const db = new BrainyData({
-  remoteServer: {
+    remoteServer: {
-    url: 'wss://your-brainy-server.com/ws',
+        url: 'wss://your-brainy-server.com/ws',
-    protocols: 'brainy-sync',
+        protocols: 'brainy-sync',
-    autoConnect: true // Connect automatically during initialization
+        autoConnect: true // Connect automatically during initialization
-  }
+    }
 })
 await db.init()
 
 // Or connect manually after initialization
 if (!db.isConnectedToRemoteServer()) {
-  await db.connectToRemoteServer('wss://your-brainy-server.com/ws', 'brainy-sync')
+    await db.connectToRemoteServer('wss://your-brainy-server.com/ws', 'brainy-sync')
 }
 
 // Search the remote server (results are stored locally)
-const remoteResults = await db.searchText('machine learning', 5, { searchMode: 'remote' })
+const remoteResults = await db.searchText('machine learning', 5, {searchMode: 'remote'})
 
 // Search the local database (includes previously stored results)
-const localResults = await db.searchText('machine learning', 5, { searchMode: 'local' })
+const localResults = await db.searchText('machine learning', 5, {searchMode: 'local'})
 
 // Perform a combined search (local first, then remote if needed)
-const combinedResults = await db.searchText('neural networks', 5, { searchMode: 'combined' })
+const combinedResults = await db.searchText('neural networks', 5, {searchMode: 'combined'})
 
 // Add data to both local and remote instances
 const id = await db.addToBoth('Deep learning is a subset of machine learning', {
-  noun: 'Concept',
+    noun: 'Concept',
-  category: 'AI',
+    category: 'AI',
-  tags: ['deep learning', 'neural networks']
+    tags: ['deep learning', 'neural networks']
 })
 
 // Clean up when done
@@ -890,51 +897,52 @@ For a complete example with HTML interface, see the [browser-server-search examp
 Brainy follows a specific code style to maintain consistency throughout the codebase:
 
 1. **No Semicolons**: All code in the project should avoid using semicolons wherever possible. This applies to:
-   - Source code files (.ts, .js)
+    - Source code files (.ts, .js)
-   - Generated code
+    - Generated code
-   - Code examples in documentation
+    - Code examples in documentation
-   - Templates and snippets
+    - Templates and snippets
 
 2. **Formatting**: The project uses Prettier for code formatting with the following settings:
-   - No semicolons (`"semi": false`)
+    - No semicolons (`"semi": false`)
-   - Single quotes for strings (`"singleQuote": true`)
+    - Single quotes for strings (`"singleQuote": true`)
-   - 2-space indentation (`"tabWidth": 2`)
+    - 2-space indentation (`"tabWidth": 2`)
-   - Always use parentheses around arrow function parameters (`"arrowParens": "always"`)
+    - Always use parentheses around arrow function parameters (`"arrowParens": "always"`)
-   - Place the closing bracket of JSX elements on the same line (`"bracketSameLine": true`)
+    - Place the closing bracket of JSX elements on the same line (`"bracketSameLine": true`)
-   - Add spaces between brackets and object literals (`"bracketSpacing": true`)
+    - Add spaces between brackets and object literals (`"bracketSpacing": true`)
-   - Line width of 80 characters (`"printWidth": 80`)
+    - Line width of 80 characters (`"printWidth": 80`)
-   - No trailing commas (`"trailingComma": "none"`)
+    - No trailing commas (`"trailingComma": "none"`)
-   - Use spaces instead of tabs (`"useTabs": false`)
+    - Use spaces instead of tabs (`"useTabs": false`)
 
 3. **Linting**: ESLint is configured with the following rules:
-   - No semicolons:
+    - No semicolons:
-     ```json
+      ```json
-     "semi": ["error", "never"],
+      "semi": ["error", "never"],
-     "@typescript-eslint/semi": ["error", "never"]
+      "@typescript-eslint/semi": ["error", "never"]
-     ```
+      ```
-   - Unused variables handling:
+    - Unused variables handling:
-     ```json
+      ```json
-     "no-unused-vars": "off",
+      "no-unused-vars": "off",
-     "@typescript-eslint/no-unused-vars": ["warn", {
+      "@typescript-eslint/no-unused-vars": ["warn", {
-       "args": "after-used",
+        "args": "after-used",
-       "argsIgnorePattern": "^_"
+        "argsIgnorePattern": "^_"
-     }]
+      }]
-     ```
+      ```
-   - Extends recommended ESLint and TypeScript ESLint configurations
+    - Extends recommended ESLint and TypeScript ESLint configurations
 
 4. **TypeScript Configuration**:
-   - Strict type checking enabled (`"strict": true`)
+    - Strict type checking enabled (`"strict": true`)
-   - Consistent casing in file names enforced (`"forceConsistentCasingInFileNames": true`)
+    - Consistent casing in file names enforced (`"forceConsistentCasingInFileNames": true`)
-   - ES2020 target with Node.js module system
+    - ES2020 target with Node.js module system
-   - Source maps generated for debugging
+    - Source maps generated for debugging
 
 5. **Commit Messages**:
-   - Use the imperative mood ("Add feature" not "Added feature")
+    - Use the imperative mood ("Add feature" not "Added feature")
-   - Keep the first line concise (under 50 characters)
+    - Keep the first line concise (under 50 characters)
-   - Reference issues and pull requests where appropriate
+    - Reference issues and pull requests where appropriate
-   - Provide detailed explanations in the commit body when necessary
+    - Provide detailed explanations in the commit body when necessary
 
-When contributing to the project, please ensure your code follows these guidelines. The project's CI/CD pipeline will automatically check for style violations.
+When contributing to the project, please ensure your code follows these guidelines. The project's CI/CD pipeline will
+automatically check for style violations.
 
 ### Development Workflow
 

cloud-wrapper/README.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../brainy.png" alt="Brainy Logo" width="200"/>
+
 # Brainy Cloud Wrapper
+</div>
 
 A standalone web service wrapper for the [Brainy](https://github.com/soulcraft/brainy) vector graph database. This wrapper allows you to deploy Brainy as a RESTful API service on various cloud platforms including AWS, Google Cloud, and Cloudflare.
 

docs/build-time-augmentations.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../brainy.png" alt="Brainy Logo" width="200"/>
+
 # Build-Time Augmentation Registration
+</div>
 
 This document explains how to register custom augmentations at build time using the Brainy library's augmentation
 registry system.

docs/llm-augmentation.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../brainy.png" alt="Brainy Logo" width="200"/>
+
 # LLM Augmentation for Brainy
+</div>
 
 This document describes the LLM (Language Learning Model) augmentation for Brainy, which enables creating, training, testing, exporting, and deploying language models from the data in Brainy's graph database.
 

examples/README.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../brainy.png" alt="Brainy Logo" width="200"/>
+
 # Brainy Examples
+</div>
 
 This directory contains examples demonstrating various features and use cases of the Brainy vector graph database.
 

examples/browser-server-search/README.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../../brainy.png" alt="Brainy Logo" width="200"/>
+
 # Brainy Browser-Server Search Example
+</div>
 
 This example demonstrates how to use Brainy in a browser, call a server-hosted version for search, store the results locally, and then perform further searches against the local instance.
 

examples/browser-server-search/index.html

@@ -59,7 +59,10 @@
     </style>
 </head>
 <body>
-    <h1>Brainy Browser-Server Search Example</h1>
+    <div style="display: flex; align-items: center; margin-bottom: 20px;">
+        <img src="../../brainy.png" alt="Brainy Logo" width="100" style="margin-right: 20px;"/>
+        <h1>Brainy Browser-Server Search Example</h1>
+    </div>
 
     <p>
         This example demonstrates how to use Brainy in a browser, call a server-hosted version for search,

src/augmentations/README.md

@@ -1,4 +1,8 @@
+<div align="center">
+<img src="../../brainy.png" alt="Brainy Logo" width="200"/>
+
 # Brainy Augmentations
+</div>
 
 This directory contains the augmentation implementations for Brainy. Augmentations are pluggable components that extend Brainy's functionality in various ways.