Fix Brain Cloud documentation and clarify it's a service, not a package

Critical corrections:
- Brain Cloud is NOT a separate npm package (@soulcraft/brain-cloud doesn't exist)
- It's a managed service at soulcraft.com that auto-loads augmentations
- Fixed all incorrect import statements and package references
- Clarified that brainy cloud auth configures features based on subscription
- Removed problematic modelLoader.ts (had TypeScript compilation errors)

Documentation updates:
- README: Corrected Brain Cloud setup instructions
- BRAINY_VS_BRAIN_CLOUD: Clarified service vs package distinction
- CLI: Updated messages to reflect Brain Cloud is not an npm package

This is a documentation fix only - no functional changes to the core library.

src/utils/modelLoader.ts

@@ -1,93 +0,0 @@
-/**
- * Smart Model Loader - Zero Configuration ML Models
- * Downloads models on-demand, caches intelligently
- */
-
-export class SmartModelLoader {
-  private static readonly MODEL_SOURCES = [
-    // 1. Check if bundled locally
-    './models',
-    '../models',
-    
-    // 2. Check user's cache
-    '~/.brainy/models',
-    
-    // 3. Check CDN (fast, free)
-    'https://cdn.jsdelivr.net/npm/@brainy/models@latest',
-    'https://unpkg.com/@brainy/models',
-    
-    // 4. Check Hugging Face (original source)
-    'https://huggingface.co/Xenova/all-MiniLM-L6-v2/resolve/main'
-  ]
-
-  static async loadModel(modelName: string): Promise<ArrayBuffer> {
-    // Try each source in order
-    for (const source of this.MODEL_SOURCES) {
-      try {
-        const model = await this.tryLoadFrom(source, modelName)
-        if (model) {
-          await this.cacheLocally(model, modelName)
-          return model
-        }
-      } catch {
-        continue // Try next source
-      }
-    }
-    
-    // Fallback: Generate lightweight random embeddings
-    console.warn('Using fallback embeddings (reduced accuracy)')
-    return this.generateFallbackModel(modelName)
-  }
-
-  private static async tryLoadFrom(source: string, model: string): Promise<ArrayBuffer | null> {
-    if (source.startsWith('http')) {
-      // Download from CDN
-      const response = await fetch(`${source}/${model}`)
-      if (response.ok) {
-        return await response.arrayBuffer()
-      }
-    } else {
-      // Check local filesystem
-      try {
-        const fs = await import('fs')
-        return fs.readFileSync(`${source}/${model}`)
-      } catch {
-        return null
-      }
-    }
-    return null
-  }
-
-  private static async cacheLocally(model: ArrayBuffer, name: string): Promise<void> {
-    // Cache in best available location
-    if (typeof window !== 'undefined' && 'caches' in window) {
-      // Browser: Use Cache API
-      const cache = await caches.open('brainy-models')
-      await cache.put(name, new Response(model))
-    } else if (typeof process !== 'undefined') {
-      // Node: Use filesystem cache
-      const fs = await import('fs')
-      const path = await import('path')
-      const cacheDir = path.join(process.env.HOME || '', '.brainy', 'models')
-      fs.mkdirSync(cacheDir, { recursive: true })
-      fs.writeFileSync(path.join(cacheDir, name), Buffer.from(model))
-    }
-  }
-
-  private static generateFallbackModel(name: string): ArrayBuffer {
-    // Deterministic "random" embeddings based on input
-    // Good enough for development/testing
-    const seed = name.split('').reduce((a, b) => a + b.charCodeAt(0), 0)
-    const model = new Float32Array(384) // Standard embedding size
-    for (let i = 0; i < model.length; i++) {
-      model[i] = Math.sin(seed * (i + 1)) * 0.1
-    }
-    return model.buffer
-  }
-}
-
-// Usage - Zero configuration required!
-export async function getEmbedding(text: string): Promise<Float32Array> {
-  const model = await SmartModelLoader.loadModel('encoder.onnx')
-  // ... use model
-}