fixed deps

libs/community/Makefile

@@ -9,7 +9,7 @@ TEST_FILE ?= tests/unit_tests/
 integration_test integration_tests: TEST_FILE = tests/integration_tests/
 
 test tests integration_test integration_tests:
-	poetry run pytest --release $(TEST_FILE)
+	poetry run pytest $(TEST_FILE)
 
 
 ######################
@@ -20,8 +20,8 @@ test tests integration_test integration_tests:
 PYTHON_FILES=.
 MYPY_CACHE=.mypy_cache
 lint format: PYTHON_FILES=.
-lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/tools --name-only --diff-filter=d main | grep -E '\.py$$|\.ipynb$$')
-lint_package: PYTHON_FILES=langchain_google_tools
+lint_diff format_diff: PYTHON_FILES=$(shell git diff --relative=libs/community --name-only --diff-filter=d main | grep -E '\.py$$|\.ipynb$$')
+lint_package: PYTHON_FILES=langchain_google_community
 lint_tests: PYTHON_FILES=tests
 lint_tests: MYPY_CACHE=.mypy_cache_test
 
@@ -41,7 +41,7 @@ spell_check:
 spell_fix:
 	poetry run codespell --toml pyproject.toml -w
 
-check_imports: $(shell find langchain_google_tools -name '*.py')
+check_imports: $(shell find langchain_google_community -name '*.py')
 	poetry run python ./scripts/check_imports.py $^
 
 ######################

libs/community/langchain_google_community/bigquery_vector_search.py

@@ -11,6 +11,7 @@
 from threading import Lock, Thread
 from typing import Any, Callable, Dict, List, Optional, Tuple, Type
 
+import numpy as np
 from google.api_core.exceptions import ClientError
 from langchain_community.utils.google import get_client_info
 from langchain_community.vectorstores.utils import (
@@ -87,7 +88,7 @@ def __init__(
                 to use. Defaults to None.
         """
         try:
-            from google.cloud import bigquery
+            from google.cloud import bigquery  # type: ignore[import-untyped]
 
             client_info = get_client_info(module="bigquery-vector-search")
             self.bq_client = bigquery.Client(
@@ -101,13 +102,6 @@ def __init__(
                 "Please, install or upgrade the google-cloud-bigquery library: "
                 "pip install google-cloud-bigquery"
             )
-        try:
-            import numpy as np
-        except ModuleNotFoundError:
-            raise ImportError(
-                "Please, install or upgrade the numpy library: "
-                "pip install numpy"
-            )
         self._logger = logging.getLogger(__name__)
         self._creating_index = False
         self._have_index = False
@@ -132,7 +126,7 @@ def __init__(
 
     def _initialize_table(self) -> Any:
         """Validates or creates the BigQuery table."""
-        from google.cloud import bigquery
+        from google.cloud import bigquery  # type: ignore[import-untyped]
 
         table_ref = bigquery.TableReference.from_string(self._full_table_id)
         table = self.bq_client.create_table(table_ref, exists_ok=True)
@@ -198,7 +192,7 @@ def _initialize_vector_index(self) -> Any:
         A vector index in BigQuery table enables efficient
         approximate vector search.
         """
-        from google.cloud import bigquery
+        from google.cloud import bigquery  # type: ignore[import-untyped]
 
         if self._have_index or self._creating_index:
             # Already have an index or in the process of creating one.
@@ -270,7 +264,7 @@ def _create_index(self):  # type: ignore[no-untyped-def]
 
     def _persist(self, data: Dict[str, Any]) -> None:
         """Saves documents and embeddings to BigQuery."""
-        from google.cloud import bigquery
+        from google.cloud import bigquery  # type: ignore[import-untyped]
 
         data_len = len(data[list(data.keys())[0]])
         if data_len == 0:
@@ -363,7 +357,7 @@ def get_documents(
             List of ids from adding the texts into the vectorstore.
         """
         if ids and len(ids) > 0:
-            from google.cloud import bigquery
+            from google.cloud import bigquery  # type: ignore[import-untyped]
 
             job_config = bigquery.QueryJobConfig(
                 query_parameters=[
@@ -430,7 +424,7 @@ def delete(self, ids: Optional[List[str]] = None, **kwargs: Any) -> Optional[boo
         """
         if not ids or len(ids) == 0:
             return True
-        from google.cloud import bigquery
+        from google.cloud import bigquery  # type: ignore[import-untyped]
 
         job_config = bigquery.QueryJobConfig(
             query_parameters=[
@@ -471,7 +465,7 @@ def _search_with_score_and_embeddings_by_vector(
         brute_force: bool = False,
         fraction_lists_to_search: Optional[float] = None,
     ) -> List[Tuple[Document, List[float], float]]:
-        from google.cloud import bigquery
+        from google.cloud import bigquery  # type: ignore[import-untyped]
 
         # Create an index if no index exists.
         if not self._have_index and not self._creating_index:
@@ -735,8 +729,6 @@ def max_marginal_relevance_search(
         Returns:
             List of Documents selected by maximal marginal relevance.
         """
-        import numpy as np
-
         query_embedding = self.embedding_model.embed_query(  # type: ignore
             query
         )
@@ -785,8 +777,6 @@ def max_marginal_relevance_search_by_vector(
         Returns:
             List of Documents selected by maximal marginal relevance.
         """
-        import numpy as np
-
         doc_tuples = self._search_with_score_and_embeddings_by_vector(
             embedding, fetch_k, filter, brute_force, fraction_lists_to_search
         )

libs/community/langchain_google_community/documentai_warehouse.py

@@ -9,12 +9,12 @@
 from langchain_core.utils import get_from_dict_or_env
 
 if TYPE_CHECKING:
-    from google.cloud.contentwarehouse_v1 import (
+    from google.cloud.contentwarehouse_v1 import (  # type: ignore[import-untyped]
         DocumentServiceClient,
         RequestMetadata,
         SearchDocumentsRequest,
     )
-    from google.cloud.contentwarehouse_v1.services.document_service.pagers import (
+    from google.cloud.contentwarehouse_v1.services.document_service.pagers import (  # type: ignore[import-untyped]
         SearchDocumentsPager,
     )
 

libs/community/langchain_google_community/gmail/loader.py

@@ -2,7 +2,7 @@
 import re
 from typing import Any, Iterator
 
-from googleapiclient.discovery import build
+from googleapiclient.discovery import build  # type: ignore[import-untyped]
 from langchain_community.chat_loaders.base import BaseChatLoader
 from langchain_core.chat_sessions import ChatSession
 from langchain_core.messages import HumanMessage

libs/community/langchain_google_community/gmail/toolkit.py

@@ -14,7 +14,7 @@
 
 if TYPE_CHECKING:
     # This is for linting and IDE typehints
-    from googleapiclient.discovery import Resource
+    from googleapiclient.discovery import Resource  # type: ignore[import-untyped]
 else:
     try:
         # We do this so pydantic can resolve the types when instantiating

libs/community/langchain_google_community/vertex_ai_search.py

@@ -22,7 +22,7 @@
 from langchain_core.utils import get_from_dict_or_env
 
 if TYPE_CHECKING:
-    from google.cloud.discoveryengine_v1beta import (
+    from google.cloud.discoveryengine_v1beta import (  # type: ignore[import-untyped]
         ConversationalSearchServiceClient,
         SearchRequest,
         SearchResult,