pinecone[patch]: release 0.0.2rc0, remove simsimd dep (#17469)

libs/partners/pinecone/langchain_pinecone/_utilities.py

@@ -2,7 +2,6 @@ from enum import Enum
 from typing import List, Union
 
 import numpy as np
-import simsimd  # type: ignore
 
 Matrix = Union[List[List[float]], List[np.ndarray], np.ndarray]
 
@@ -62,10 +61,20 @@ def cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray:
             f"Number of columns in X and Y must be the same. X has shape {X.shape} "
             f"and Y has shape {Y.shape}."
         )
+    try:
+        import simsimd as simd  # type: ignore
 
-    X = np.array(X, dtype=np.float32)
-    Y = np.array(Y, dtype=np.float32)
-    Z = 1 - simsimd.cdist(X, Y, metric="cosine")
-    if isinstance(Z, float):
-        return np.array([Z])
-    return Z
+        X = np.array(X, dtype=np.float32)
+        Y = np.array(Y, dtype=np.float32)
+        Z = 1 - simd.cdist(X, Y, metric="cosine")
+        if isinstance(Z, float):
+            return np.array([Z])
+        return Z
+    except ImportError:
+        X_norm = np.linalg.norm(X, axis=1)
+        Y_norm = np.linalg.norm(Y, axis=1)
+        # Ignore divide by zero errors run time warnings as those are handled below.
+        with np.errstate(divide="ignore", invalid="ignore"):
+            similarity = np.dot(X, Y.T) / np.outer(X_norm, Y_norm)
+        similarity[np.isnan(similarity) | np.isinf(similarity)] = 0.0
+        return similarity