feat: replace dtype with clearer precision parameter for model selection

- Changed confusing 'dtype' to 'precision' for model variant selection
- Fixed Q8 quantized model loading in transformers.js pipeline
- Added proper model file detection for q8 vs fp32 models
- Updated all references across codebase to use new parameter
- Maintains backward compatibility while providing clearer API

src/embeddings/lightweight-embedder.ts

@@ -113,7 +113,7 @@ export class LightweightEmbedder {
       console.log('⚠️ Loading ONNX model for complex text...')
       const { TransformerEmbedding } = await import('../utils/embedding.js')
       this.onnxEmbedder = new TransformerEmbedding({ 
-        dtype: 'fp32',
+        precision: 'fp32',
         verbose: false 
       })
       await this.onnxEmbedder.init()

src/embeddings/universal-memory-manager.ts

@@ -139,7 +139,7 @@ export class UniversalMemoryManager {
       
       this.embeddingFunction = new TransformerEmbedding({
         verbose: false,
-        dtype: 'fp32',
+        precision: 'fp32',
         localFilesOnly: process.env.BRAINY_ALLOW_REMOTE_MODELS !== 'true'
       })
       

src/embeddings/worker-embedding.ts

@@ -16,7 +16,7 @@ async function initModel(): Promise<void> {
   if (!model) {
     model = new TransformerEmbedding({
       verbose: false,
-      dtype: 'fp32',
+      precision: 'fp32',
       localFilesOnly: process.env.BRAINY_ALLOW_REMOTE_MODELS !== 'true'
     })
     await model.init()