**feat(core): enhance vector handling, model loading, and compatibility**

- **Vector Handling Updates**:
  - Added a `dimensions` property to `BrainyDataConfig` for specifying vector dimensions.
  - Introduced validation for vector dimensions during database creation and insertion to ensure consistency.
  - Enhanced error handling and logging for dimension mismatches.

- **Model Loading Improvements**:
  - Implemented retry logic for Universal Sentence Encoder model loading to handle network instability and JSON parsing errors gracefully.
  - Improved logging and debugging support for failures during model initialization and embedding operations.

- **Compatibility Enhancements**:
  - Updated polyfills to support TensorFlow.js compatibility across diverse server environments (Node.js, serverless, etc.).
  - Introduced and refactored global `TextEncoder`/`TextDecoder` definitions for seamless operation in non-browser environments.
  - Simplified TensorFlow.js backend setup with streamlined imports and logging for GPU/WebGL fallback.

- **Purpose**:
  - These updates improve BrainyData's robustness, enforce correct vector usage, and extend compatibility with varied runtime environments. The changes enhance the usability, reliability, and cross-platform readiness of core functionalities.

src/utils/environment.ts

@@ -13,6 +13,12 @@ export function isBrowser(): boolean {
  * Check if code is running in a Node.js environment
  */
 export function isNode(): boolean {
+  // If browser environment is detected, prioritize it over Node.js
+  // This handles cases like jsdom where both window and process exist
+  if (isBrowser()) {
+    return false
+  }
+
   return (
     typeof process !== 'undefined' &&
     process.versions != null &&