**feat(patch): enhance TextEncoder/TextDecoder compatibility for TensorFlow.js**
- Refactored `applyTensorFlowPatch` in `textEncoding.ts` to introduce a unified `Platform` class supporting both Node.js and browser environments with native `TextEncoder`/`TextDecoder`. - Modified global object handling to target `PlatformNode` in Node.js and `PlatformBrowser` in browser environments. - Added `getTextEncoder` and `getTextDecoder` utility functions to simplify text encoding/decoding across platforms. - Introduced `setup.ts` to apply environment patches before other modules load. - Updated CLI entry points (`cli.ts`, `rollup.config.js`) to ensure patching precedes TensorFlow.js usage. - Enhanced test coverage for TextEncoder compatibility with `test-fix.js`. - Adjusted imports in `test-tensorflow-textencoder.ts` to align with the updated `./utils/textEncoding.js`. - Streamlined constructor definitions in `Platform` for improved maintainability. This update ensures robust compatibility for TensorFlow.js by patching and standardizing text encoding/decoding functionality across environments.
This commit is contained in:
parent
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commit
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7 changed files with 142 additions and 84 deletions
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@ -7,6 +7,7 @@ import { terser } from 'rollup-plugin-terser'
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// CLI configuration
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export default {
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input: 'src/cli.ts',
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context: 'this', // Preserve 'this' context to fix TensorFlow.js issue
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output: {
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dir: 'dist',
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entryFileNames: 'cli.js',
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@ -5,6 +5,11 @@
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* A command-line interface for interacting with the Brainy vector database
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*/
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// Import the setup file for its side-effects.
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// This MUST be the very first import to ensure patches are applied
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// before any other module (like TensorFlow.js) is loaded.
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import './setup.js'
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// Log environment information
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console.log('Brainy running in Node.js environment')
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12
cli-package/src/setup.ts
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12
cli-package/src/setup.ts
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@ -0,0 +1,12 @@
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/**
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* This file is imported for its side effects to patch the environment
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* for TensorFlow.js before any other library code runs.
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*
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* It ensures that by the time TensorFlow.js is imported by any other
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* module, the necessary compatibility fixes for the current Node.js
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* environment are already in place.
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*/
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import { applyTensorFlowPatch } from './utils/textEncoding.js'
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// Apply the TensorFlow.js platform patch if needed
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applyTensorFlowPatch()
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@ -7,7 +7,7 @@
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import {
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getTextEncoder,
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getTextDecoder
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} from '@soulcraft/brainy/dist/utils/textEncoding.js'
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} from './utils/textEncoding.js'
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import * as tf from '@tensorflow/tfjs'
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import '@tensorflow/tfjs-backend-cpu'
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@ -1,101 +1,94 @@
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/**
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* Unified Text Encoding Utilities for CLI
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* Unified Text Encoding Utilities
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*
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* This module provides a consistent way to handle text encoding/decoding across all environments
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* using the native TextEncoder/TextDecoder APIs.
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*/
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/**
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* Get a text encoder that works in the current environment
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* @returns A TextEncoder instance
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*/
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export function getTextEncoder(): TextEncoder {
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return new TextEncoder()
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}
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/**
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* Get a text decoder that works in the current environment
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* @returns A TextDecoder instance
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*/
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export function getTextDecoder(): TextDecoder {
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return new TextDecoder()
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}
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/**
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* Apply the TensorFlow.js platform patch if needed
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* This function patches the global object to provide a PlatformNode class
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* that uses native TextEncoder/TextDecoder
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*/
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export function applyTensorFlowPatch(): void {
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// Only apply in Node.js environment
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if (
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typeof global !== 'undefined' &&
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typeof process !== 'undefined' &&
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process.versions &&
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process.versions.node
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) {
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try {
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// Define a custom PlatformNode class
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class PlatformNode {
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util: any
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textEncoder: TextEncoder
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textDecoder: TextDecoder
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try {
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// Define a custom Platform class that works in both Node.js and browser environments
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class Platform {
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util: any
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textEncoder: TextEncoder
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textDecoder: TextDecoder
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constructor() {
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// Create a util object with necessary methods and constructors
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this.util = {
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// Add isFloat32Array and isTypedArray directly to util
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isFloat32Array: (arr: any) => {
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return !!(
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arr instanceof Float32Array ||
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(arr &&
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Object.prototype.toString.call(arr) ===
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'[object Float32Array]')
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)
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},
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isTypedArray: (arr: any) => {
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return !!(ArrayBuffer.isView(arr) && !(arr instanceof DataView))
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},
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// Use native TextEncoder and TextDecoder
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TextEncoder: TextEncoder,
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TextDecoder: TextDecoder
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}
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// Initialize using native constructors
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this.textEncoder = new TextEncoder()
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this.textDecoder = new TextDecoder()
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constructor() {
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// Create a util object with necessary methods and constructors
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this.util = {
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// Use native TextEncoder and TextDecoder
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TextEncoder: globalThis.TextEncoder || TextEncoder,
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TextDecoder: globalThis.TextDecoder || TextDecoder
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}
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// Define isFloat32Array directly on the instance
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isFloat32Array(arr: any) {
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return !!(
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arr instanceof Float32Array ||
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(arr &&
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Object.prototype.toString.call(arr) === '[object Float32Array]')
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)
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}
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// Define isTypedArray directly on the instance
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isTypedArray(arr: any) {
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return !!(ArrayBuffer.isView(arr) && !(arr instanceof DataView))
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}
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// Initialize using native constructors directly
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this.textEncoder = new (globalThis.TextEncoder || TextEncoder)()
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this.textDecoder = new (globalThis.TextDecoder || TextDecoder)()
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}
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// Assign the PlatformNode class to the global object
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;(global as any).PlatformNode = PlatformNode
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// Also create an instance and assign it to global.platformNode (lowercase p)
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;(global as any).platformNode = new PlatformNode()
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// Ensure global.util exists and has the necessary methods
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// This is needed because TensorFlow.js might look for these methods in global.util
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if (!(global as any).util) {
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;(global as any).util = {}
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// Define isFloat32Array directly on the instance
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isFloat32Array(arr: any) {
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return !!(
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arr instanceof Float32Array ||
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(arr &&
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Object.prototype.toString.call(arr) === '[object Float32Array]')
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)
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}
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// Add isFloat32Array method if it doesn't exist
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if (!(global as any).util.isFloat32Array) {
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;(global as any).util.isFloat32Array = (arr: any) => {
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return !!(
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arr instanceof Float32Array ||
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(arr &&
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Object.prototype.toString.call(arr) === '[object Float32Array]')
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)
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}
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// Define isTypedArray directly on the instance
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isTypedArray(arr: any) {
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return !!(ArrayBuffer.isView(arr) && !(arr instanceof DataView))
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}
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// Add isTypedArray method if it doesn't exist
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if (!(global as any).util.isTypedArray) {
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;(global as any).util.isTypedArray = (arr: any) => {
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return !!(ArrayBuffer.isView(arr) && !(arr instanceof DataView))
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}
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}
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} catch (error) {
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console.warn('Failed to apply TensorFlow.js platform patch:', error)
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}
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// Get the global object in a way that works in both Node.js and browser
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const globalObj =
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typeof global !== 'undefined'
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? global
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: typeof window !== 'undefined'
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? window
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: typeof self !== 'undefined'
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? self
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: {}
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// Only apply in Node.js environment
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if (
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typeof process !== 'undefined' &&
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process.versions &&
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process.versions.node
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) {
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// Assign the Platform class to the global object as PlatformNode for Node.js
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;(globalObj as any).PlatformNode = Platform
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// Also create an instance and assign it to global.platformNode (lowercase p)
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;(globalObj as any).platformNode = new Platform()
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} else if (typeof window !== 'undefined' || typeof self !== 'undefined') {
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// In browser environments, we might need to provide similar functionality
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// but we'll use a different name to avoid conflicts
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;(globalObj as any).PlatformBrowser = Platform
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;(globalObj as any).platformBrowser = new Platform()
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}
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} catch (error) {
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console.warn('Failed to apply TensorFlow.js platform patch:', error)
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}
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}
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@ -38,13 +38,13 @@ export function applyTensorFlowPatch(): void {
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// Create a util object with necessary methods and constructors
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this.util = {
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// Use native TextEncoder and TextDecoder
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TextEncoder: TextEncoder,
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TextDecoder: TextDecoder
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TextEncoder: globalThis.TextEncoder || TextEncoder,
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TextDecoder: globalThis.TextDecoder || TextDecoder
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}
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// Initialize using native constructors
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this.textEncoder = new TextEncoder()
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this.textDecoder = new TextDecoder()
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// Initialize using native constructors directly
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this.textEncoder = new (globalThis.TextEncoder || TextEncoder)()
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this.textDecoder = new (globalThis.TextDecoder || TextDecoder)()
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}
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// Define isFloat32Array directly on the instance
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47
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@ -0,0 +1,47 @@
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// Test script to verify the TextEncoder fix
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import { applyTensorFlowPatch } from './dist/utils/textEncoding.js'
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console.log('Testing TextEncoder fix...')
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// Apply the TensorFlow.js platform patch
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applyTensorFlowPatch()
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// Check if PlatformNode is defined in the global object
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if (typeof global.PlatformNode === 'function') {
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console.log('PlatformNode is defined in the global object')
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// Create an instance of PlatformNode
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try {
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const platform = new global.PlatformNode()
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console.log('Successfully created PlatformNode instance')
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// Check if textEncoder is defined
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if (platform.textEncoder) {
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console.log('textEncoder is defined')
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// Test encoding a string
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const testString = 'Hello, world! 👋'
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const encoded = platform.textEncoder.encode(testString)
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console.log(`Successfully encoded string: ${testString}`)
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console.log(`Encoded: [${encoded}]`)
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// Test decoding
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const decoded = platform.textDecoder.decode(encoded)
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console.log(`Successfully decoded back to: ${decoded}`)
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if (testString === decoded) {
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console.log('✅ TextEncoder/TextDecoder test passed!')
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} else {
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console.error('❌ TextEncoder/TextDecoder test failed!')
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}
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} else {
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console.error('textEncoder is not defined in the platform instance')
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}
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} catch (error) {
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console.error('Error creating PlatformNode instance:', error)
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}
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} else {
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console.error('PlatformNode is not defined in the global object')
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}
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console.log('Test completed')
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