**feat(docs): add comprehensive documentation for model bundling and robust loading**
- Introduced new documentation files under `docs/`: - `model-bundling-analysis.md`: Provides detailed analysis of current, bundled, hybrid, and dynamic model loading approaches, including pros, cons, and recommendations. - `model-management.md`: Explains how Brainy manages Universal Sentence Encoder models, including setup, usage, and troubleshooting. - `optional-model-bundling.md`: Details the `@soulcraft/brainy-models` package for offline reliability with pre-bundled models. - Added `src/utils/robustModelLoader.ts`: - Implements enhanced model loading with retry mechanisms, timeout handling, fallback URLs, and optional local model bundling. - Supports Node.js and browser environments with exponential backoff logic. - Key Updates: - **Hybrid Loading Strategy**: Recommended for balancing reliability and flexibility via hybrid online/offline mechanisms. - **Enhanced Fallback Scenarios**: Robust loader improves network-dependent reliability for embedding workflows. - **Offline Reliability Support**: Optional model bundling eliminates dependency on external services, supporting air-gapped and edge environments. **Purpose**: Introduce a hybrid model loading approach with robust options for
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src/utils/robustModelLoader.ts
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src/utils/robustModelLoader.ts
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/**
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* Robust Model Loader - Enhanced model loading with retry mechanisms and fallbacks
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*
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* This module provides a more reliable way to load TensorFlow models with:
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* - Exponential backoff retry mechanisms
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* - Timeout handling
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* - Multiple fallback strategies
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* - Better error handling and logging
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* - Optional local model bundling support
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*/
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import { EmbeddingModel } from '../coreTypes.js'
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export interface ModelLoadOptions {
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/** Maximum number of retry attempts */
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maxRetries?: number
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/** Initial retry delay in milliseconds */
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initialRetryDelay?: number
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/** Maximum retry delay in milliseconds */
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maxRetryDelay?: number
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/** Request timeout in milliseconds */
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timeout?: number
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/** Whether to use exponential backoff */
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useExponentialBackoff?: boolean
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/** Fallback model URLs to try if primary fails */
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fallbackUrls?: string[]
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/** Whether to enable verbose logging */
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verbose?: boolean
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/** Whether to prefer local bundled model if available */
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preferLocalModel?: boolean
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}
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export interface RetryConfig {
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attempt: number
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maxRetries: number
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delay: number
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error: Error
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}
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export class RobustModelLoader {
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private options: Required<ModelLoadOptions>
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private loadAttempts: Map<string, number> = new Map()
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constructor(options: ModelLoadOptions = {}) {
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this.options = {
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maxRetries: options.maxRetries ?? 3,
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initialRetryDelay: options.initialRetryDelay ?? 1000,
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maxRetryDelay: options.maxRetryDelay ?? 30000,
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timeout: options.timeout ?? 60000, // 60 seconds
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useExponentialBackoff: options.useExponentialBackoff ?? true,
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fallbackUrls: options.fallbackUrls ?? [],
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verbose: options.verbose ?? false,
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preferLocalModel: options.preferLocalModel ?? true
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}
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}
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/**
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* Load a model with robust retry and fallback mechanisms
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*/
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async loadModel(
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primaryLoadFunction: () => Promise<EmbeddingModel>,
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modelIdentifier: string = 'default'
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): Promise<EmbeddingModel> {
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const startTime = Date.now()
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this.log(`Starting robust model loading for: ${modelIdentifier}`)
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// Try local bundled model first if preferred
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if (this.options.preferLocalModel) {
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try {
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const localModel = await this.tryLoadLocalBundledModel()
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if (localModel) {
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this.log(`Successfully loaded local bundled model in ${Date.now() - startTime}ms`)
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return localModel
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}
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} catch (error) {
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this.log(`Local bundled model not available: ${error}`)
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}
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}
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// Try primary load function with retries
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try {
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const model = await this.loadWithRetries(
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primaryLoadFunction,
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`primary-${modelIdentifier}`
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)
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this.log(`Successfully loaded model via primary method in ${Date.now() - startTime}ms`)
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return model
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} catch (primaryError) {
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this.log(`Primary model loading failed: ${primaryError}`)
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// Try fallback URLs if available
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for (let i = 0; i < this.options.fallbackUrls.length; i++) {
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const fallbackUrl = this.options.fallbackUrls[i]
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this.log(`Trying fallback URL ${i + 1}/${this.options.fallbackUrls.length}: ${fallbackUrl}`)
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try {
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const fallbackModel = await this.loadWithRetries(
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() => this.loadFromUrl(fallbackUrl),
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`fallback-${i}-${modelIdentifier}`
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)
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this.log(`Successfully loaded model via fallback ${i + 1} in ${Date.now() - startTime}ms`)
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return fallbackModel
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} catch (fallbackError) {
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this.log(`Fallback ${i + 1} failed: ${fallbackError}`)
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}
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}
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// All attempts failed
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const totalTime = Date.now() - startTime
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const errorMessage = `All model loading attempts failed after ${totalTime}ms. Primary error: ${primaryError}`
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this.log(errorMessage)
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throw new Error(errorMessage)
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}
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}
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/**
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* Load a model with retry logic and exponential backoff
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*/
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private async loadWithRetries(
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loadFunction: () => Promise<EmbeddingModel>,
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identifier: string
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): Promise<EmbeddingModel> {
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let lastError: Error
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const currentAttempts = this.loadAttempts.get(identifier) || 0
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for (let attempt = currentAttempts; attempt <= this.options.maxRetries; attempt++) {
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this.loadAttempts.set(identifier, attempt)
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try {
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this.log(`Attempt ${attempt + 1}/${this.options.maxRetries + 1} for ${identifier}`)
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// Apply timeout to the load function
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const model = await this.withTimeout(loadFunction(), this.options.timeout)
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// Success - clear attempt counter
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this.loadAttempts.delete(identifier)
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return model
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} catch (error) {
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lastError = error as Error
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this.log(`Attempt ${attempt + 1} failed: ${lastError.message}`)
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// Don't retry on the last attempt
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if (attempt === this.options.maxRetries) {
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break
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}
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// Calculate delay for next attempt
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const delay = this.calculateRetryDelay(attempt)
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this.log(`Retrying in ${delay}ms...`)
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// Wait before next attempt
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await this.sleep(delay)
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}
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}
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// All retries exhausted
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this.loadAttempts.delete(identifier)
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throw lastError!
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}
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/**
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* Try to load a locally bundled model
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*/
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private async tryLoadLocalBundledModel(): Promise<EmbeddingModel | null> {
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try {
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// Check if we're in Node.js environment
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const isNode = typeof process !== 'undefined' &&
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process.versions != null &&
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process.versions.node != null
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if (isNode) {
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// Try to load from bundled model directory
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const path = await import('path')
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const fs = await import('fs')
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const { fileURLToPath } = await import('url')
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const __filename = fileURLToPath(import.meta.url)
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const __dirname = path.dirname(__filename)
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// Look for bundled model in multiple possible locations
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const possiblePaths = [
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path.join(__dirname, '..', '..', 'models', 'bundled', 'universal-sentence-encoder'),
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path.join(__dirname, '..', '..', 'node_modules', '@soulcraft', 'brainy-models', 'universal-sentence-encoder'),
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path.join(process.cwd(), 'node_modules', '@soulcraft', 'brainy-models', 'universal-sentence-encoder')
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]
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for (const modelPath of possiblePaths) {
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const modelJsonPath = path.join(modelPath, 'model.json')
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if (fs.existsSync(modelJsonPath)) {
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this.log(`Found bundled model at: ${modelJsonPath}`)
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// Load TensorFlow.js if not already loaded
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const tf = await import('@tensorflow/tfjs')
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const model = await tf.loadLayersModel(`file://${modelJsonPath}`)
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// Return a wrapper that matches the Universal Sentence Encoder interface
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return this.createModelWrapper(model)
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}
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}
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}
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return null
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} catch (error) {
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this.log(`Error checking for bundled model: ${error}`)
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return null
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}
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}
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/**
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* Load model from a specific URL
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*/
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private async loadFromUrl(url: string): Promise<EmbeddingModel> {
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// This would need to be implemented based on the specific model type
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// For now, we'll throw an error indicating this needs implementation
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throw new Error(`Loading from custom URL not yet implemented: ${url}`)
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}
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/**
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* Create a model wrapper that matches the Universal Sentence Encoder interface
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*/
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private createModelWrapper(tfModel: any): EmbeddingModel {
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return {
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init: async () => {
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// Model is already loaded
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},
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embed: async (sentences: string | string[]) => {
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const input = Array.isArray(sentences) ? sentences : [sentences]
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// This is a simplified implementation - would need proper preprocessing
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const inputTensors = tfModel.predict(input)
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return inputTensors
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},
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dispose: async () => {
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if (tfModel && tfModel.dispose) {
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tfModel.dispose()
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}
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}
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}
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}
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/**
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* Apply timeout to a promise
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*/
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private async withTimeout<T>(promise: Promise<T>, timeoutMs: number): Promise<T> {
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const timeoutPromise = new Promise<never>((_, reject) => {
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setTimeout(() => {
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reject(new Error(`Operation timed out after ${timeoutMs}ms`))
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}, timeoutMs)
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})
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return Promise.race([promise, timeoutPromise])
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}
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/**
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* Calculate retry delay with exponential backoff
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*/
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private calculateRetryDelay(attempt: number): number {
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if (!this.options.useExponentialBackoff) {
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return this.options.initialRetryDelay
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}
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// Exponential backoff: delay = initialDelay * (2 ^ attempt) + jitter
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const exponentialDelay = this.options.initialRetryDelay * Math.pow(2, attempt)
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// Add jitter (random factor) to prevent thundering herd
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const jitter = Math.random() * 1000
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// Cap at maximum delay
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const delay = Math.min(exponentialDelay + jitter, this.options.maxRetryDelay)
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return Math.floor(delay)
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}
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/**
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* Sleep for specified milliseconds
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*/
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private sleep(ms: number): Promise<void> {
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return new Promise(resolve => setTimeout(resolve, ms))
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}
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/**
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* Log message if verbose mode is enabled
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*/
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private log(message: string): void {
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if (this.options.verbose) {
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console.log(`[RobustModelLoader] ${message}`)
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}
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}
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/**
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* Get loading statistics
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*/
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getLoadingStats(): { [key: string]: number } {
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const stats: { [key: string]: number } = {}
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for (const [identifier, attempts] of this.loadAttempts.entries()) {
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stats[identifier] = attempts
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}
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return stats
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}
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/**
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* Reset loading statistics
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*/
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resetStats(): void {
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this.loadAttempts.clear()
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}
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}
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/**
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* Create a robust model loader with sensible defaults
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*/
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export function createRobustModelLoader(options?: ModelLoadOptions): RobustModelLoader {
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return new RobustModelLoader(options)
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}
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/**
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* Utility function to create fallback URLs for Universal Sentence Encoder
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*/
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export function getUniversalSentenceEncoderFallbacks(): string[] {
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return [
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'https://tfhub.dev/tensorflow/tfjs-model/universal-sentence-encoder/1/default/1',
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'https://storage.googleapis.com/tfjs-models/savedmodel/universal_sentence_encoder/1/model.json',
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// Add more fallback URLs as they become available
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]
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}
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