fix: remove dead model config code for true zero-config

- Remove unused model.type validation that caused Workshop error
- Remove model config from BrainyConfig type (never used)
- Simplify modelAutoConfig.ts (always Q8 WASM)
- Clean up zeroConfig.ts model references

This fixes the "Invalid model type: balanced" error and removes
unnecessary configuration options that did nothing.

src/brainy.ts

@@ -177,7 +177,6 @@ export class Brainy<T = any> implements BrainyInterface<T> {
         ...this.config,
         ...configOverrides,
         storage: { ...this.config.storage, ...configOverrides.storage },
-        model: { ...this.config.model, ...configOverrides.model },
         index: { ...this.config.index, ...configOverrides.index },
         augmentations: { ...this.config.augmentations, ...configOverrides.augmentations },
         verbose: configOverrides.verbose ?? this.config.verbose,
@@ -4972,11 +4971,6 @@ export class Brainy<T = any> implements BrainyInterface<T> {
       // Both 'gcs' and 'gcs-native' can now use either gcsStorage or gcsNativeStorage
     }
 
-    // Validate model configuration
-    if (config?.model?.type && !['fast', 'accurate', 'custom'].includes(config.model.type)) {
-      throw new Error(`Invalid model type: ${config.model.type}. Must be one of: fast, accurate, custom`)
-    }
-
     // Validate numeric configurations
     if (config?.index?.m && (config.index.m < 1 || config.index.m > 128)) {
       throw new Error(`Invalid index m parameter: ${config.index.m}. Must be between 1 and 128`)
@@ -4995,7 +4989,6 @@ export class Brainy<T = any> implements BrainyInterface<T> {
 
     return {
       storage: config?.storage || { type: 'auto' },
-      model: config?.model || { type: 'fast' },
       index: config?.index || {},
       cache: config?.cache ?? true,
       augmentations: config?.augmentations || {},

src/config/index.ts

@@ -3,19 +3,13 @@
  * Main entry point for all auto-configuration features
  */
 
-// Model configuration
+// Model configuration (simplified - always Q8 WASM)
-export { 
+export {
-  autoSelectModelPrecision, 
+  getModelPrecision,
-  ModelPrecision as ModelPrecisionType,  // Avoid conflict
-  ModelPreset,
   shouldAutoDownloadModels,
-  getModelPath,
+  getModelPath
-  logModelConfig
 } from './modelAutoConfig.js'
 
-// Model precision - Always Q8 now (99% accuracy, 75% smaller)
-export const getModelPrecision = () => 'q8' as const
-
 // Storage configuration
 export { 
   autoDetectStorage, 

src/config/modelAutoConfig.ts

@@ -1,49 +1,24 @@
 /**
- * Model Configuration Auto-Selection
+ * Model Configuration
- * Always uses Q8 for optimal size/performance balance (99% accuracy, 75% smaller)
+ * Brainy uses Q8 WASM embeddings - no configuration needed (zero-config)
  */
 
 import { isBrowser, isNode } from '../utils/environment.js'
 
-export type ModelPrecision = 'q8'
-export type ModelPreset = 'small' | 'auto'
-
 interface ModelConfigResult {
-  precision: ModelPrecision
+  precision: 'q8'
   reason: string
   autoSelected: boolean
 }
 
 /**
- * Auto-select model precision - Always returns Q8
+ * Get model precision configuration
- * Q8 provides 99% accuracy with 75% smaller size
+ * Always returns Q8 - the optimal balance of size and accuracy
- * @param override - For backward compatibility, ignored
  */
-export function autoSelectModelPrecision(override?: ModelPrecision | ModelPreset): ModelConfigResult {
+export function getModelPrecision(): ModelConfigResult {
-  // Always use Q8 regardless of override for simplicity
-  // Q8 is optimal: 33MB vs 130MB, 99% accuracy retained
-  
-  // Log deprecation notice if FP32 was requested
-  if (typeof override === 'string' && override.toLowerCase().includes('fp32')) {
-    console.log('Note: FP32 precision is deprecated. Using Q8 (99% accuracy, 75% smaller).')
-  }
-  
   return {
     precision: 'q8',
-    reason: 'Q8 precision (99% accuracy, 75% smaller)',
+    reason: 'Q8 WASM (23MB bundled, no downloads)',
-    autoSelected: true
-  }
-}
-
-/**
- * Automatically detect the best model precision for the environment
- * DEPRECATED: Always returns Q8 now
- */
-function autoDetectBestPrecision(): ModelConfigResult {
-  // Always return Q8 - deprecated function kept for backward compatibility
-  return {
-    precision: 'q8',
-    reason: 'Q8 precision (99% accuracy, 75% smaller)',
     autoSelected: true
   }
 }
@@ -53,7 +28,7 @@ function autoDetectBestPrecision(): ModelConfigResult {
  */
 function isServerlessEnvironment(): boolean {
   if (!isNode()) return false
-  
+
   return !!(
     process.env.AWS_LAMBDA_FUNCTION_NAME ||
     process.env.VERCEL ||
@@ -65,104 +40,42 @@ function isServerlessEnvironment(): boolean {
 }
 
 /**
- * Get available memory in MB
+ * Check if models need to be downloaded
- */
+ * With bundled WASM model, this is rarely needed
-function getAvailableMemoryMB(): number {
-  if (isBrowser()) {
-    // @ts-ignore - navigator.deviceMemory is experimental
-    if (navigator.deviceMemory) {
-      // @ts-ignore
-      return navigator.deviceMemory * 1024 // Device memory in GB
-    }
-    return 256 // Conservative default for browsers
-  }
-  
-  if (isNode()) {
-    try {
-      // Try to get memory info synchronously for Node.js
-      // This will be available in Node.js environments
-      if (typeof process !== 'undefined' && process.memoryUsage) {
-        // Use RSS (Resident Set Size) as a proxy for available memory
-        const rss = process.memoryUsage().rss
-        // Assume we can use up to 4GB or 50% more than current usage
-        return Math.min(4096, Math.floor(rss / (1024 * 1024) * 1.5))
-      }
-    } catch {
-      // Fall through to default
-    }
-    return 1024 // Default 1GB for Node.js
-  }
-  
-  return 512 // Conservative default
-}
-
-/**
- * Convenience function to check if models need to be downloaded
- * This replaces the need for BRAINY_ALLOW_REMOTE_MODELS
  */
 export function shouldAutoDownloadModels(): boolean {
-  // Always allow downloads unless explicitly disabled
+  // Model is bundled - no downloads needed in normal operation
-  // This eliminates the need for BRAINY_ALLOW_REMOTE_MODELS
+  // This flag exists for edge cases only
   const explicitlyDisabled = process.env.BRAINY_ALLOW_REMOTE_MODELS === 'false'
-  
+  return !explicitlyDisabled
-  if (explicitlyDisabled) {
-    console.warn('Model downloads disabled via BRAINY_ALLOW_REMOTE_MODELS=false')
-    return false
-  }
-  
-  // In production, always allow downloads for seamless operation
-  if (process.env.NODE_ENV === 'production') {
-    return true
-  }
-  
-  // In development, allow downloads with a one-time notice
-  if (process.env.NODE_ENV === 'development') {
-    return true
-  }
-  
-  // Default: allow downloads
-  return true
 }
 
 /**
- * Get the model path with intelligent defaults
+ * Get the model path
- * This replaces the need for BRAINY_MODELS_PATH env var
+ * With bundled WASM model, this points to the package assets
  */
 export function getModelPath(): string {
-  // Check if user explicitly set a path (keeping this for advanced users)
+  // Check if user explicitly set a path (for advanced users)
   if (process.env.BRAINY_MODELS_PATH) {
     return process.env.BRAINY_MODELS_PATH
   }
-  
+
-  // Browser - use cache API or IndexedDB (handled by transformers.js)
+  // Browser - use cache API or IndexedDB
   if (isBrowser()) {
     return 'browser-cache'
   }
-  
+
   // Serverless - use /tmp for ephemeral storage
   if (isServerlessEnvironment()) {
     return '/tmp/.brainy/models'
   }
-  
+
   // Node.js - use home directory for persistent storage
   if (isNode()) {
-    // Use process.env.HOME as a fallback
     const homeDir = process.env.HOME || process.env.USERPROFILE || '~'
     return `${homeDir}/.brainy/models`
   }
-  
+
   // Fallback
   return './.brainy/models'
 }
-
-/**
- * Log model configuration decision (only in verbose mode)
- */
-export function logModelConfig(config: ModelConfigResult, verbose: boolean = false): void {
-  if (!verbose && process.env.NODE_ENV === 'production') {
-    return // Silent in production unless verbose
-  }
-  
-  const icon = config.autoSelected ? '🤖' : '👤'
-  console.log(`${icon} Model: ${config.precision.toUpperCase()} - ${config.reason}`)
-}

src/config/sharedConfigManager.ts

@@ -3,14 +3,13 @@
  * Ensures configuration consistency across multiple instances using shared storage
  */
 
-import { ModelPrecision } from './modelAutoConfig.js'
 import { StorageType } from './storageAutoConfig.js'
 import { getBrainyVersion } from '../utils/version.js'
 
 export interface SharedConfig {
   // Critical parameters that MUST match across instances
   version: string
-  precision: ModelPrecision
+  precision: 'q8'
   dimensions: number
   hnswM: number
   hnswEfConstruction: number

src/config/zeroConfig.ts

@@ -3,7 +3,7 @@
  * Provides intelligent defaults while preserving full control
  */
 
-import { autoSelectModelPrecision, ModelPrecision, ModelPreset, getModelPath, shouldAutoDownloadModels } from './modelAutoConfig.js'
+import { getModelPrecision, getModelPath, shouldAutoDownloadModels } from './modelAutoConfig.js'
 import { autoDetectStorage, StorageType, StoragePreset } from './storageAutoConfig.js'
 import { AutoConfiguration } from '../utils/autoConfiguration.js'
 
@@ -23,16 +23,6 @@ export interface BrainyZeroConfig {
    */
   mode?: 'production' | 'development' | 'minimal' | 'zero' | 'writer' | 'reader'
   
-  /**
-   * Model precision configuration
-   * - 'fp32': Full precision (best quality, larger size)
-   * - 'q8': Quantized 8-bit (smaller size, slightly lower quality)
-   * - 'fast': Alias for fp32
-   * - 'small': Alias for q8
-   * - 'auto': Auto-detect based on environment (default)
-   */
-  model?: ModelPrecision | ModelPreset
-  
   /**
    * Storage configuration  
    * - 'memory': In-memory only (no persistence)
@@ -72,31 +62,26 @@ export interface BrainyZeroConfig {
 const PRESETS = {
   production: {
     storage: 'disk' as const,
-    model: 'auto' as const,
     features: 'default' as const,
     verbose: false
   },
   development: {
     storage: 'memory' as const,
-    model: 'q8' as const,  // Q8 is now the default for all presets
     features: 'full' as const,
     verbose: true
   },
   minimal: {
     storage: 'memory' as const,
-    model: 'q8' as const,
     features: 'minimal' as const,
     verbose: false
   },
   zero: {
     storage: 'auto' as const,
-    model: 'auto' as const,
     features: 'default' as const,
     verbose: false
   },
   writer: {
     storage: 'auto' as const,
-    model: 'auto' as const,
     features: 'minimal' as const,
     verbose: false,
     // Writer-specific settings
@@ -107,7 +92,6 @@ const PRESETS = {
   },
   reader: {
     storage: 'auto' as const,
-    model: 'auto' as const,
     features: 'default' as const,
     verbose: false,
     // Reader-specific settings
@@ -180,18 +164,17 @@ export async function processZeroConfig(input?: string | BrainyZeroConfig): Prom
       ...preset,
       ...config,
       // Preserve explicit overrides
-      model: config.model ?? preset.model,
       storage: config.storage ?? preset.storage,
       features: config.features ?? preset.features,
       verbose: config.verbose ?? preset.verbose
     }
   }
-  
+
   // Auto-detect environment if not in preset mode
   const environment = detectEnvironmentMode()
-  
+
-  // Process model configuration
+  // Get model configuration (always Q8 WASM)
-  const modelConfig = autoSelectModelPrecision(config.model)
+  const modelConfig = getModelPrecision()
   
   // Process storage configuration
   const storageConfig = await autoDetectStorage(config.storage)
@@ -376,15 +359,14 @@ function logConfigurationSummary(config: any): void {
 }
 
 /**
- * Create embedding function with specified precision
+ * Create embedding function (always Q8 WASM)
- * This ensures the model precision is respected
  */
-export async function createEmbeddingFunctionWithPrecision(precision: ModelPrecision): Promise<any> {
+export async function createEmbeddingFunctionWithPrecision(): Promise<any> {
   const { createEmbeddingFunction } = await import('../utils/embedding.js')
-  
+
-  // Create embedding function with specified precision
+  // Create embedding function - always Q8 WASM
   return createEmbeddingFunction({
-    precision: precision,
+    precision: 'q8',
     verbose: false // Silent by default in zero-config
   })
 }

src/types/brainy.types.ts

@@ -632,14 +632,7 @@ export interface BrainyConfig {
     options?: any
     branch?: string              // COW branch name (default: 'main')
   }
-  
+
-  // Model configuration
-  model?: {
-    type: 'fast' | 'accurate' | 'balanced' | 'custom'
-    name?: string           // Custom model name
-    precision?: 'q8'
-  }
-  
   // Index configuration
   index?: {
     m?: number              // HNSW M parameter