feat(src/utils): add GPU acceleration and improve threading for embeddings and distance calculations

- Integrated GPU acceleration via WebGL in `embedding.ts` and `distance.ts` for optimized performance.
- Enhanced fallback mechanisms for CPU processing when GPU is unavailable or fails to initialize.
- Added threading support for embedding and distance calculations in `embedding.ts` and `distance.ts` to improve performance and avoid blocking the main thread.
- Refactored TensorFlow.js imports to dynamically load modules (`@tensorflow/tfjs-core`, `@tensorflow/tfjs-backend-webgl`, `@tensorflow/tfjs-backend-cpu`) for modular dependency usage.
- Introduced GPU-accelerated batch distance calculations in `distance.ts` with appropriate error handling.
- Applied consistent formatting to improve code readability and maintainability while adhering to project style guidelines.

src/utils/workerUtils.ts

@@ -20,6 +20,18 @@ export function executeInWebWorker<T>(fnString: string, args: any): Promise<T> {
       self.index = {}
       self.index$1 = {}
       self.index$2 = {}
+      self.universalSentenceEncoder_esm = {}
+      self.universalSentenceEncoder = {}
+      self.tfjs = {}
+      self.tfjs_core = {}
+      self.tfjs_backend_cpu = {}
+      self.tfjs_backend_webgl = {}
+
+      // Additional variables that might be generated by bundlers
+      self.use = {}
+      self.tf = {}
+      self.sentenceEncoder = {}
+      self.sentenceEncoderModule = {}
 
       self.onmessage = async function(e) {
         try {