refactor: reduce provider sync/async duplication

src/selectools/embeddings/anthropic.py

@@ -139,16 +139,6 @@ def embed_query(self, query: str) -> List[float]:
         )
         return cast(List[float], response.embeddings[0])
 
-    @property
-    def dimension(self) -> int:
-        """
-        Get the embedding vector dimension.
-
-        Returns:
-            Dimension of embedding vectors
-        """
-        return self._dimension
-
 
 __stability__ = "beta"
 

src/selectools/embeddings/cohere.py

@@ -154,16 +154,6 @@ def embed_query(self, query: str) -> List[float]:
         )
         return cast(List[float], response.embeddings[0])
 
-    @property
-    def dimension(self) -> int:
-        """
-        Get the embedding vector dimension.
-
-        Returns:
-            Dimension of embedding vectors
-        """
-        return self._dimension
-
 
 __stability__ = "beta"
 

src/selectools/embeddings/gemini.py

@@ -172,16 +172,6 @@ def embed_query(self, query: str) -> List[float]:
             raise ValueError("No embedding returned")
         return response.embeddings[0].values
 
-    @property
-    def dimension(self) -> int:
-        """
-        Get the embedding vector dimension.
-
-        Returns:
-            Dimension of embedding vectors
-        """
-        return self._dimension
-
 
 __stability__ = "beta"
 

src/selectools/embeddings/openai.py

@@ -146,16 +146,6 @@ def embed_query(self, query: str) -> List[float]:
         """
         return self.embed_text(query)
 
-    @property
-    def dimension(self) -> int:
-        """
-        Get the embedding vector dimension.
-
-        Returns:
-            Dimension of embedding vectors
-        """
-        return self._dimension
-
 
 __stability__ = "beta"
 

src/selectools/embeddings/provider.py

@@ -19,6 +19,11 @@ class EmbeddingProvider(ABC):
     across different backend implementations (OpenAI, Anthropic/Voyage, Gemini, Cohere).
     """
 
+    # Each concrete provider sets this in __init__ (typically via
+    # _get_model_dimension()). Declared here so the shared `dimension`
+    # property below is type-checked against the base class.
+    _dimension: int
+
     @abstractmethod
     def embed_text(self, text: str) -> List[float]:
         """
@@ -63,15 +68,14 @@ def embed_query(self, query: str) -> List[float]:
         pass
 
     @property
-    @abstractmethod
     def dimension(self) -> int:
         """
         Get the embedding vector dimension for this model.
 
         Returns:
             Integer dimension of embedding vectors
         """
-        pass
+        return self._dimension
 
 
 __stability__ = "beta"