feat: enhance EmbeddingFunc with model_name support

Why this change is needed:
To support vector storage model isolation, we need to track which model is used for embeddings and generate unique identifiers for collections/tables.

How it solves it:
- Added model_name field to EmbeddingFunc
- Added get_model_identifier() method to generate sanitized suffix
- Added unit tests to verify behavior

Impact:
Enables subsequent changes in storage backends to isolate data by model.

Testing:
Added tests/test_embedding_func.py passing.

lightrag/utils.py

@@ -370,6 +370,19 @@ class EmbeddingFunc:
     send_dimensions: bool = (
         False  # Control whether to send embedding_dim to the function
     )
+    model_name: str | None = None
+
+    def get_model_identifier(self) -> str:
+        """Generates model identifier for collection/table suffix.
+
+        Returns:
+            str: Format "{model_name}_{dim}d", e.g. "text_embedding_3_large_3072d"
+                 If model_name is not specified, returns "unknown_{dim}d"
+        """
+        model_part = self.model_name if self.model_name else "unknown"
+        # Clean model name: remove special chars, convert to lower, replace - with _
+        safe_model_name = re.sub(r'[^a-zA-Z0-9_]', '_', model_part.lower())
+        return f"{safe_model_name}_{self.embedding_dim}d"
 
     async def __call__(self, *args, **kwargs) -> np.ndarray:
         # Only inject embedding_dim when send_dimensions is True

tests/test_embedding_func.py

@@ -0,0 +1,37 @@
+import pytest
+from lightrag.utils import EmbeddingFunc
+
+def dummy_func(*args, **kwargs):
+    pass
+
+def test_embedding_func_with_model_name():
+    func = EmbeddingFunc(
+        embedding_dim=1536,
+        func=dummy_func,
+        model_name="text-embedding-ada-002"
+    )
+    assert func.get_model_identifier() == "text_embedding_ada_002_1536d"
+
+def test_embedding_func_without_model_name():
+    func = EmbeddingFunc(
+        embedding_dim=768,
+        func=dummy_func
+    )
+    assert func.get_model_identifier() == "unknown_768d"
+
+def test_model_name_sanitization():
+    func = EmbeddingFunc(
+        embedding_dim=1024,
+        func=dummy_func,
+        model_name="models/text-embedding-004"  # Contains special chars
+    )
+    assert func.get_model_identifier() == "models_text_embedding_004_1024d"
+
+def test_model_name_with_uppercase():
+    func = EmbeddingFunc(
+        embedding_dim=512,
+        func=dummy_func,
+        model_name="My-Model-V1"
+    )
+    assert func.get_model_identifier() == "my_model_v1_512d"
+