Revert changes for vector retriever prefiltering

src/neo4j_genai/retrievers/hybrid.py

@@ -54,9 +54,7 @@ def __init__(
                 return_properties=return_properties,
             )
         except ValidationError as e:
-            msg = f"Validation failed: {e.errors()}"
-            logger.error(msg)
-            raise ValueError(msg)
+            raise ValueError(f"Validation failed: {e.errors()}")
 
         super().__init__(validated_data.driver_model.driver)
         self.vector_index_name = validated_data.vector_index_name
@@ -101,9 +99,7 @@ def search(
                 query_text=query_text,
             )
         except ValidationError as e:
-            msg = f"Validation failed: {e.errors()}"
-            logger.error(msg)
-            raise ValueError(msg)
+            raise ValueError(f"Validation failed: {e.errors()}")
 
         parameters = validated_data.model_dump(exclude_none=True)
 
@@ -142,9 +138,7 @@ def __init__(
                 embedder_model=embedder_model,
             )
         except ValidationError as e:
-            msg = f"Validation failed: {e.errors()}"
-            logger.error(msg)
-            raise ValueError(msg)
+            raise ValueError(f"Validation failed: {e.errors()}")
 
         super().__init__(validated_data.driver_model.driver)
         self.vector_index_name = validated_data.vector_index_name
@@ -192,9 +186,7 @@ def search(
                 query_params=query_params,
             )
         except ValidationError as e:
-            msg = f"Validation failed: {e.errors()}"
-            logger.error(msg)
-            raise ValueError(msg)
+            raise ValueError(f"Validation failed: {e.errors()}")
 
         parameters = validated_data.model_dump(exclude_none=True)
 

src/neo4j_genai/retrievers/vector.py

@@ -43,17 +43,23 @@ def __init__(
         index_name: str,
         embedder: Optional[Embedder] = None,
         return_properties: Optional[list[str]] = None,
+        filters: Optional[dict[str, Any]] = None,
     ) -> None:
         super().__init__(driver)
         self.index_name = index_name
         self.return_properties = return_properties
         self.embedder = embedder
+        self._node_label = None
+        self._embedding_node_property = None
+        self._embedding_dimension = None
+        self._fetch_index_infos()
 
     def search(
         self,
         query_vector: Optional[list[float]] = None,
         query_text: Optional[str] = None,
         top_k: int = 5,
+        filters: Optional[dict[str, Any]] = None,
     ) -> list[VectorSearchRecord]:
         """Get the top_k nearest neighbor embeddings for either provided query_vector or query_text.
         See the following documentation for more details:
@@ -75,7 +81,7 @@ def search(
         """
         try:
             validated_data = VectorSearchModel(
-                index_name=self.index_name,
+                vector_index_name=self.index_name,
                 top_k=top_k,
                 query_vector=query_vector,
                 query_text=query_text,
@@ -93,7 +99,15 @@ def search(
             parameters["query_vector"] = query_vector
             del parameters["query_text"]
 
-        search_query = get_search_query(SearchType.VECTOR, self.return_properties)
+        search_query, search_params = get_search_query(
+            SearchType.VECTOR,
+            self.return_properties,
+            node_label=self._node_label,
+            embedding_node_property=self._embedding_node_property,
+            embedding_dimension=self._embedding_dimension,
+            filters=filters,
+        )
+        parameters.update(search_params)
 
         logger.debug("VectorRetriever Cypher parameters: %s", parameters)
         logger.debug("VectorRetriever Cypher query: %s", search_query)
@@ -129,13 +143,18 @@ def __init__(
         self.index_name = index_name
         self.retrieval_query = retrieval_query
         self.embedder = embedder
+        self._node_label = None
+        self._node_embedding_property = None
+        self._embedding_dimension = None
+        self._fetch_index_infos()
 
     def search(
         self,
         query_vector: Optional[list[float]] = None,
         query_text: Optional[str] = None,
         top_k: int = 5,
         query_params: Optional[dict[str, Any]] = None,
+        filters: Optional[dict[str, Any]] = None,
     ) -> list[neo4j.Record]:
         """Get the top_k nearest neighbor embeddings for either provided query_vector or query_text.
         See the following documentation for more details:
@@ -158,7 +177,7 @@ def search(
         """
         try:
             validated_data = VectorCypherSearchModel(
-                index_name=self.index_name,
+                vector_index_name=self.index_name,
                 top_k=top_k,
                 query_vector=query_vector,
                 query_text=query_text,
@@ -181,9 +200,15 @@ def search(
                     parameters[key] = value
             del parameters["query_params"]
 
-        search_query = get_search_query(
-            SearchType.VECTOR, retrieval_query=self.retrieval_query
+        search_query, search_params = get_search_query(
+            SearchType.VECTOR,
+            retrieval_query=self.retrieval_query,
+            node_label=self._node_label,
+            embedding_node_property=self._node_embedding_property,
+            embedding_dimension=self._embedding_dimension,
+            filters=filters,
         )
+        parameters.update(search_params)
 
         logger.debug("VectorCypherRetriever Cypher parameters: %s", parameters)
         logger.debug("VectorCypherRetriever Cypher query: %s", search_query)

tests/unit/retrievers/test_vector.py

@@ -36,9 +36,7 @@ def test_vector_retriever_bad_data_validation(driver):
 
 def test_vector_cypher_retriever_bad_data_validation(driver):
     with pytest.raises(ValueError):
-        VectorCypherRetriever(
-            driver=driver, index_name="my-index", retrieval_query=42
-        )
+        VectorCypherRetriever(driver=driver, index_name="my-index", retrieval_query=42)
 
 
 def test_vector_cypher_retriever_initialization(driver):