**feat(models): add pre-bundled Universal Sentence Encoder for offline use**

- Introduced `@soulcraft/brainy-models` package with pre-bundled TensorFlow models for enhanced offline reliability.
- Added `index.d.ts` and `index.js` allowing offline embedding workflows with the Universal Sentence Encoder model.
- Included utility scripts for model compression, size retrieval, and availability checks.
- Added `metadata.json` and `model.json` defining the Universal Sentence Encoder configuration with offline bundling.
- Ensured comprehensive model documentation, error handling, and robust logging for seamless integration.
- Supported optional model quantization placeholders for future TensorFlow.js enhancements.

**Purpose**: Enable fully offline-ready embedding workflows via pre-bundled Universal Sentence Encoder models, ensuring maximum reliability and air-gapped environment compatibility.

brainy-models-package/reproduce-error.js

@@ -0,0 +1,28 @@
+#!/usr/bin/env node
+
+/**
+ * Reproduction script for the TensorFlow.js isNullOrUndefined error
+ */
+
+import * as tf from '@tensorflow/tfjs-node'
+import * as use from '@tensorflow-models/universal-sentence-encoder'
+
+console.log('🔍 Loading Universal Sentence Encoder model...')
+
+try {
+  const model = await use.load()
+  console.log('✅ Model loaded successfully')
+
+  console.log('🧪 Testing model functionality...')
+  const testEmbedding = await model.embed(['Hello world'])
+  const testArray = await testEmbedding.array()
+  console.log(
+    `✅ Model test passed - embedding dimensions: ${testArray[0].length}`
+  )
+  testEmbedding.dispose()
+  model.dispose()
+} catch (error) {
+  console.error('❌ Error:', error)
+  console.error('Stack trace:', error.stack)
+  process.exit(1)
+}