chore(deps): update python-nonmajor (#152)

* chore(deps): update python-nonmajor

* fix for numpy 2

* Update vector_store.py

---------

Co-authored-by: Averi Kitsch <[email protected]>

Author: renovate-bot

pyproject.toml

@@ -36,21 +36,21 @@ Changelog = "https://github.com/googleapis/langchain-google-spanner-python/blob/
 
 [project.optional-dependencies]
 lint = [
-    "black[jupyter]==24.8.0",
+    "black[jupyter]==24.10.0",
     "flake8==6.1.0",
     "isort==5.13.2",
 ]
 
 test = [
-    "black[jupyter]==24.8.0",
+    "black[jupyter]==24.10.0",
     "bs4==0.0.2",
     "flake8==6.1.0",
     "isort==5.13.2",
-    "mypy==1.11.2",
-    "pytest==8.3.3",
-    "pytest-asyncio==0.24.0",
+    "mypy==1.17.0",
+    "pytest==8.4.1",
+    "pytest-asyncio==0.26.0",
     "pytest-cov==5.0.0",
-    "langchain_google_vertexai==2.0.8"
+    "langchain_google_vertexai==2.0.27"
 ]
 
 [build-system]

requirements.txt

@@ -1,4 +1,4 @@
-google-cloud-spanner==3.51.0
-langchain-core==0.3.15
-langchain-community==0.3.1
-pydantic==2.9.1
+google-cloud-spanner==3.55.0
+langchain-core==0.3.71
+langchain-community==0.3.27
+pydantic==2.11.7

src/langchain_google_spanner/vector_store.py

@@ -1122,7 +1122,7 @@ def _generate_sql_for_ANN(
         distance_alias = DISTANCE_SEARCH_QUERY_ALIAS
         sql = (
             f"SELECT {column_names}, {ann_strategy_name}("
-            + f"{embedding_column_type}{embedding}, {embedding_column_name}, options => JSON '"
+            + f"{embedding_column_type}{[float(dimension) for dimension in embedding]}, {embedding_column_name}, options => JSON '"
             + ('{"num_leaves_to_search": %s}\') as %s\n' % (num_leaves, distance_alias))
             + f"FROM {table_name}"
             + "@{FORCE_INDEX="