formatting and linting

redisvl/index/index.py

@@ -65,7 +65,7 @@ def process_results(
     unpack_json = (
         (storage_type == StorageType.JSON)
         and isinstance(query, FilterQuery)
-        and not query._return_fields
+        and not query._return_fields # type: ignore
     )
 
     # Process records

redisvl/query/__init__.py

@@ -13,5 +13,5 @@
     "FilterQuery",
     "RangeQuery",
     "VectorRangeQuery",
-    "CountQuery"
+    "CountQuery",
 ]

redisvl/query/query.py

@@ -28,7 +28,7 @@ def __str__(self) -> str:
 
     def _build_query_string(self) -> str:
         """Build the full Redis query string."""
-        pass
+        raise NotImplementedError("Must be implemented by subclasses")
 
     def set_filter(self, filter_expression: Optional[FilterExpression] = None):
         """Set the filter expression for the query.
@@ -45,12 +45,13 @@ def set_filter(self, filter_expression: Optional[FilterExpression] = None):
         elif isinstance(filter_expression, FilterExpression):
             self._filter_expression = filter_expression
         else:
-            raise TypeError("filter_expression must be of type FilterExpression or None")
+            raise TypeError(
+                "filter_expression must be of type FilterExpression or None"
+            )
 
         # Reset the query string
         self._query_string = self._build_query_string()
 
-
     @property
     def filter(self) -> FilterExpression:
         """The filter expression for the query."""
@@ -167,16 +168,16 @@ def _build_query_string(self) -> str:
         return str(self._filter_expression)
 
 
-class BaseVectorQuery(BaseQuery):
-    DTYPES: Dict[str, np.dtype] = {
+class BaseVectorQuery:
+    DTYPES: Dict[str, Any] = {
         "float32": np.float32,
         "float64": np.float64,
     }
     DISTANCE_ID: str = "vector_distance"
     VECTOR_PARAM: str = "vector"
 
 
-class VectorQuery(BaseVectorQuery):
+class VectorQuery(BaseVectorQuery, BaseQuery):
     def __init__(
         self,
         vector: Union[List[float], bytes],
@@ -268,7 +269,7 @@ def params(self) -> Dict[str, Any]:
         return {self.VECTOR_PARAM: vector}
 
 
-class VectorRangeQuery(BaseVectorQuery):
+class VectorRangeQuery(BaseVectorQuery, BaseQuery):
     DISTANCE_THRESHOLD_PARAM: str = "distance_threshold"
 
     def __init__(

tests/integration/test_llmcache.py

@@ -19,7 +19,9 @@ def vectorizer():
 @pytest.fixture
 def cache(vectorizer, redis_url):
     cache_instance = SemanticCache(
-        vectorizer=vectorizer, distance_threshold=0.2, redis_url="redis://localhost:6379"
+        vectorizer=vectorizer,
+        distance_threshold=0.2,
+        redis_url="redis://localhost:6379",
     )
     yield cache_instance
     cache_instance._index.delete(True)  # Clean up index

tests/integration/test_session_manager.py

@@ -464,8 +464,7 @@ def test_semantic_add_and_get_relevant(semantic_session):
     default_context = semantic_session.get_relevant("list of fruits and vegetables")
     assert len(default_context) == 5  # 2 pairs of prompt:response, and system
     assert default_context == semantic_session.get_relevant(
-        "list of fruits and vegetables",
-        distance_threshold=0.5
+        "list of fruits and vegetables", distance_threshold=0.5
     )
 
     # test tool calls can also be returned

tests/unit/test_query_types.py

@@ -1,5 +1,4 @@
 import pytest
-
 from redis.commands.search.query import Query
 from redis.commands.search.result import Result
 
@@ -124,10 +123,11 @@ def test_vector_query():
         ["field1", "field2"],
         dialect=3,
         num_results=10,
-        in_order=True
+        in_order=True,
     )
     assert vector_query._in_order
 
+
 def test_range_query():
     # Create a filter expression
     filter_expression = Tag("brand") == "Nike"
@@ -182,7 +182,7 @@ def test_range_query():
         ["field1"],
         filter_expression,
         num_results=10,
-        in_order=True
+        in_order=True,
     )
     assert range_query._in_order
 
@@ -193,7 +193,7 @@ def test_range_query():
         CountQuery(),
         FilterQuery(),
         VectorQuery(vector=[1, 2, 3], vector_field_name="vector"),
-        RangeQuery(vector=[1, 2, 3], vector_field_name="vector")
+        RangeQuery(vector=[1, 2, 3], vector_field_name="vector"),
     ],
 )
 def test_query_modifiers(query):