diff --git a/libs/community/langchain_community/utils/math.py b/libs/community/langchain_community/utils/math.py index 99d4736819..2522c1255c 100644 --- a/libs/community/langchain_community/utils/math.py +++ b/libs/community/langchain_community/utils/math.py @@ -29,7 +29,7 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray: Z = 1 - simd.cdist(X, Y, metric="cosine") if isinstance(Z, float): return np.array([Z]) - return Z + return np.array(Z) except ImportError: logger.info( "Unable to import simsimd, defaulting to NumPy implementation. If you want " diff --git a/libs/partners/elasticsearch/langchain_elasticsearch/_utilities.py b/libs/partners/elasticsearch/langchain_elasticsearch/_utilities.py index 0280708736..33b302241e 100644 --- a/libs/partners/elasticsearch/langchain_elasticsearch/_utilities.py +++ b/libs/partners/elasticsearch/langchain_elasticsearch/_utilities.py @@ -79,7 +79,7 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray: Z = 1 - simd.cdist(X, Y, metric="cosine") if isinstance(Z, float): return np.array([Z]) - return Z + return np.array(Z) except ImportError: X_norm = np.linalg.norm(X, axis=1) Y_norm = np.linalg.norm(Y, axis=1) diff --git a/libs/partners/mongodb/langchain_mongodb/utils.py b/libs/partners/mongodb/langchain_mongodb/utils.py index feb34ad1c2..854b2bc939 100644 --- a/libs/partners/mongodb/langchain_mongodb/utils.py +++ b/libs/partners/mongodb/langchain_mongodb/utils.py @@ -38,7 +38,7 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray: Z = 1 - simd.cdist(X, Y, metric="cosine") if isinstance(Z, float): return np.array([Z]) - return Z + return np.array(Z) except ImportError: logger.info( "Unable to import simsimd, defaulting to NumPy implementation. If you want " diff --git a/libs/partners/pinecone/langchain_pinecone/_utilities.py b/libs/partners/pinecone/langchain_pinecone/_utilities.py index 37d61e9fb1..5ad9e407fc 100644 --- a/libs/partners/pinecone/langchain_pinecone/_utilities.py +++ b/libs/partners/pinecone/langchain_pinecone/_utilities.py @@ -69,7 +69,7 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray: Z = 1 - simd.cdist(X, Y, metric="cosine") if isinstance(Z, float): return np.array([Z]) - return Z + return np.array(Z) except ImportError: X_norm = np.linalg.norm(X, axis=1) Y_norm = np.linalg.norm(Y, axis=1)