changed numpy import (langchain-ai#77)

* modified github actions

* fixed deps

.github/scripts/check_diff.py

@@ -5,6 +5,7 @@
 LANGCHAIN_DIRS = {
     "libs/genai",
     "libs/vertexai",
+    "libs/community"
 }
 
 if __name__ == "__main__":
@@ -30,6 +31,8 @@
             dirs_to_run.update({"libs/genai"})
         elif "libs/vertexai" in file:
             dirs_to_run.update({"libs/vertexai"})
+        elif "libs/community" in file:
+            dirs_to_run.update({"libs/community"})
         else:
             pass
     json_output = json.dumps(list(dirs_to_run))

.github/workflows/_all_ci.yml

@@ -17,6 +17,7 @@ on:
         options:
         - libs/genai
         - libs/vertexai
+        - libs/community
 
 
 # If another push to the same PR or branch happens while this workflow is still running,

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

@@ -88,7 +88,7 @@ def __init__(
                 to use. Defaults to None.
         """
         try:
-            from google.cloud import bigquery
+            from google.cloud import bigquery  # type: ignore[attr-defined]
 
             client_info = get_client_info(module="bigquery-vector-search")
             self.bq_client = bigquery.Client(
@@ -126,7 +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[attr-defined]
 
         table_ref = bigquery.TableReference.from_string(self._full_table_id)
         table = self.bq_client.create_table(table_ref, exists_ok=True)
@@ -192,7 +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[attr-defined]
 
         if self._have_index or self._creating_index:
             # Already have an index or in the process of creating one.
@@ -264,7 +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[attr-defined]
 
         data_len = len(data[list(data.keys())[0]])
         if data_len == 0:
@@ -357,7 +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[attr-defined]
 
             job_config = bigquery.QueryJobConfig(
                 query_parameters=[
@@ -424,7 +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[attr-defined]
 
         job_config = bigquery.QueryJobConfig(
             query_parameters=[
@@ -465,7 +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[attr-defined]
 
         # Create an index if no index exists.
         if not self._have_index and not self._creating_index:

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]
         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]
         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]
 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]
 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]
         ConversationalSearchServiceClient,
         SearchRequest,
         SearchResult,