fix: update default embedding models for better performance

- Change WeChat, Browser, and Email RAG examples to use all-MiniLM-L6-v2
- Previous Qwen/Qwen3-Embedding-0.6B was too slow for these use cases
- all-MiniLM-L6-v2 is a fast 384-dim model, ideal for large-scale personal data

examples/browser_rag.py

@@ -18,6 +18,11 @@ class BrowserRAG(BaseRAGExample):
     """RAG example for Chrome browser history."""
 
     def __init__(self):
+        # Set default values BEFORE calling super().__init__
+        self.embedding_model_default = (
+            "sentence-transformers/all-MiniLM-L6-v2"  # Fast 384-dim model
+        )
+
         super().__init__(
             name="Browser History",
             description="Process and query Chrome browser history with LEANN",