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d958e80 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 | const PhoneRuntime = {
_loadedModels: new Map(),
_runtimeType: 'mock',
async initializeRuntime() {
this._detectRuntime();
log('Runtime: ' + this._runtimeType);
},
_detectRuntime() {
if (typeof navigator !== 'undefined' && navigator.gpu) {
this._runtimeType = 'webgpu';
} else if (typeof WebAssembly !== 'undefined') {
this._runtimeType = 'wasm';
} else {
this._runtimeType = 'mock';
}
// Native CoreML/MLX only available in native iOS app, not Safari
},
selectBestRuntime() {
return this._runtimeType;
},
async loadTextEmbeddingModel(modelId) {
// v1: mock load; v2 would use transformers.js or ONNX Runtime Web
this._loadedModels.set(modelId || 'text-embedding', { type: 'embedding', loaded: true });
log('Loaded embedding model (mock)');
return true;
},
async loadImageModel(modelId) {
this._loadedModels.set(modelId || 'image-classifier', { type: 'image', loaded: true });
log('Loaded image model (mock)');
return true;
},
async loadRedactionModel(modelId) {
this._loadedModels.set(modelId || 'privacy-redact', { type: 'redaction', loaded: true });
log('Loaded redaction model (mock)');
return true;
},
isModelLoaded(modelId) {
return this._loadedModels.has(modelId);
},
async runTextEmbedding(text) {
if (!this._loadedModels.has('text-embedding')) {
await this.loadTextEmbeddingModel();
}
// v1: return deterministic mock embedding vector
const vec = new Array(384).fill(0);
for (let i = 0; i < text.length && i < 384; i++) {
vec[i] = (text.charCodeAt(i) % 100) / 100;
}
return { embedding: vec, model: 'mock-embedding', runtime: this._runtimeType };
},
async runImageClassification(imageDataUrl) {
if (!this._loadedModels.has('image-classifier')) {
await this.loadImageModel();
}
// v1: mock classification based on image size
const mockLabels = ['cat', 'dog', 'bird', 'car', 'tree'];
const idx = (imageDataUrl.length % mockLabels.length);
return {
labels: [
{ label: mockLabels[idx], score: 0.92 },
{ label: mockLabels[(idx + 1) % mockLabels.length], score: 0.05 },
],
model: 'mock-image',
runtime: this._runtimeType,
};
},
async runPrivacyRedaction(text) {
if (!this._loadedModels.has('privacy-redact')) {
await this.loadRedactionModel();
}
// Simple regex-based redaction for demo
const redacted = text
.replace(/\b[A-Za-z0-9._%+-]+@[A-Za-z0-9.-]+\.[A-Z|a-z]{2,}\b/g, '[EMAIL]')
.replace(/\b\d{3}-\d{2}-\d{4}\b/g, '[SSN]')
.replace(/\b\d{4}[\s-]?\d{4}[\s-]?\d{4}[\s-]?\d{4}\b/g, '[CARD]');
return { redacted, entities_removed: text !== redacted, model: 'mock-redact', runtime: this._runtimeType };
},
async hashModelWeights() {
return 'mock-model-hash-' + this._runtimeType;
},
getRuntimeStatus() {
return {
type: this._runtimeType,
models_loaded: Array.from(this._loadedModels.keys()),
webgpu: !!navigator.gpu,
wasm: typeof WebAssembly !== 'undefined',
};
}
};
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