genai: update pyproject as vertexai

libs/genai/langchain_google_genai/_function_utils.py

@@ -21,8 +21,10 @@
 
 import google.ai.generativelanguage as glm
 import google.ai.generativelanguage_v1beta.types as gapic
-import proto  # type: ignore[import]
-from google.generativeai.types.content_types import ToolDict  # type: ignore[import]
+import proto  # type: ignore[import-untyped]
+from google.generativeai.types.content_types import (  # type: ignore[import-untyped]
+    ToolDict,
+)
 from langchain_core.tools import BaseTool
 from langchain_core.tools import tool as callable_as_lc_tool
 from langchain_core.utils.function_calling import (
@@ -144,7 +146,7 @@ def convert_to_genai_function_declarations(
     tools: Sequence[_ToolsType],
 ) -> gapic.Tool:
     if not isinstance(tools, collections.abc.Sequence):
-        logger.warning(
+        logger.warning(  # type: ignore[unreachable]
             "convert_to_genai_function_declarations expects a Sequence "
             "and not a single tool."
         )
@@ -237,7 +239,7 @@ def _format_base_tool_to_function_declaration(
 
     if issubclass(tool.args_schema, BaseModel):
         schema = tool.args_schema.model_json_schema()
-    elif issubclass(tool.args_schema, BaseModelV1):
+    elif issubclass(tool.args_schema, BaseModelV1):  # type: ignore[unreachable]
         schema = tool.args_schema.schema()
     else:
         raise NotImplementedError(
@@ -259,7 +261,7 @@ def _convert_pydantic_to_genai_function(
 ) -> gapic.FunctionDeclaration:
     if issubclass(pydantic_model, BaseModel):
         schema = pydantic_model.model_json_schema()
-    elif issubclass(pydantic_model, BaseModelV1):
+    elif issubclass(pydantic_model, BaseModelV1):  # type: ignore[unreachable]
         schema = pydantic_model.schema()
     else:
         raise NotImplementedError(
@@ -460,7 +462,7 @@ def _tool_choice_to_tool_config(
 def is_basemodel_subclass_safe(tool: Type) -> bool:
     if safe_import("langchain_core.utils.pydantic", "is_basemodel_subclass"):
         from langchain_core.utils.pydantic import (
-            is_basemodel_subclass,  # type: ignore[import]
+            is_basemodel_subclass,
         )
 
         return is_basemodel_subclass(tool)

libs/genai/langchain_google_genai/_genai_extension.py

@@ -21,7 +21,7 @@
 from google.api_core import client_options as client_options_lib
 from google.api_core import exceptions as gapi_exception
 from google.api_core import gapic_v1
-from google.auth import credentials, exceptions  # type: ignore
+from google.auth import credentials, exceptions
 from google.protobuf import timestamp_pb2
 
 _logger = logging.getLogger(__name__)

libs/genai/langchain_google_genai/_image_utils.py

@@ -54,7 +54,7 @@ def load_bytes(self, image_string: str) -> bytes:
                 "Please pass in images as Google Cloud Storage URI, "
                 "b64 encoded image string (data:image/...), or valid image url."
             )
-            return self._bytes_from_file(image_string)
+            return self._bytes_from_file(image_string)  # type: ignore[unreachable]
 
         raise ValueError(
             "Image string must be one of: Google Cloud Storage URI, "

libs/genai/langchain_google_genai/chat_models.py

@@ -25,7 +25,7 @@
 import google.api_core
 
 # TODO: remove ignore once the google package is published with types
-import proto  # type: ignore[import]
+import proto  # type: ignore[import-untyped]
 from google.ai.generativelanguage_v1beta import (
     GenerativeServiceAsyncClient as v1betaGenerativeServiceAsyncClient,
 )
@@ -44,10 +44,10 @@
     ToolConfig,
     VideoMetadata,
 )
-from google.generativeai.caching import CachedContent  # type: ignore[import]
-from google.generativeai.types import Tool as GoogleTool  # type: ignore[import]
+from google.generativeai.caching import CachedContent  # type: ignore[import-untyped]
+from google.generativeai.types import Tool as GoogleTool  # type: ignore[import-untyped]
 from google.generativeai.types import caching_types, content_types
-from google.generativeai.types.content_types import (  # type: ignore[import]
+from google.generativeai.types.content_types import (  # type: ignore[import-untyped]
     FunctionDeclarationType,
     ToolDict,
 )
@@ -212,7 +212,7 @@ async def _achat_with_retry(generation_method: Callable, **kwargs: Any) -> Any:
         Any: The result from the chat generation method.
     """
     retry_decorator = _create_retry_decorator()
-    from google.api_core.exceptions import InvalidArgument  # type: ignore
+    from google.api_core.exceptions import InvalidArgument
 
     @retry_decorator
     async def _achat_with_retry(**kwargs: Any) -> Any:
@@ -787,10 +787,10 @@ class Joke(BaseModel):
     raise an error."""
 
     cached_content: Optional[str] = None
-    """The name of the cached content used as context to serve the prediction. 
+    """The name of the cached content used as context to serve the prediction.
 
-    Note: only used in explicit caching, where users can have control over caching 
-    (e.g. what content to cache) and enjoy guaranteed cost savings. Format: 
+    Note: only used in explicit caching, where users can have control over caching
+    (e.g. what content to cache) and enjoy guaranteed cost savings. Format:
     ``cachedContents/{cachedContent}``.
     """
 
@@ -1275,7 +1275,7 @@ def bind_tools(
                 f"both:\n\n{tool_choice=}\n\n{tool_config=}"
             )
         try:
-            formatted_tools: list = [convert_to_openai_tool(tool) for tool in tools]  # type: ignore[arg-type]
+            formatted_tools: list = [convert_to_openai_tool(tool) for tool in tools]
         except Exception:
             formatted_tools = [
                 tool_to_dict(convert_to_genai_function_declarations(tools))
@@ -1381,4 +1381,4 @@ def _get_tool_name(
     tool: Union[ToolDict, GoogleTool],
 ) -> str:
     genai_tool = tool_to_dict(convert_to_genai_function_declarations([tool]))
-    return [f["name"] for f in genai_tool["function_declarations"]][0]  # type: ignore[index]
+    return [f["name"] for f in genai_tool["function_declarations"]][0]

libs/genai/langchain_google_genai/llms.py

@@ -4,7 +4,7 @@
 from typing import Any, Callable, Dict, Iterator, List, Optional, Union
 
 import google.api_core
-import google.generativeai as genai  # type: ignore[import]
+import google.generativeai as genai  # type: ignore[import-untyped]
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
@@ -16,10 +16,7 @@
 from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
-from langchain_google_genai._enums import (
-    HarmBlockThreshold,
-    HarmCategory,
-)
+from langchain_google_genai._enums import HarmBlockThreshold, HarmCategory
 
 
 class GoogleModelFamily(str, Enum):
@@ -170,9 +167,9 @@ class _BaseGoogleGenerativeAI(BaseModel):
     )
 
     safety_settings: Optional[Dict[HarmCategory, HarmBlockThreshold]] = None
-    """The default safety settings to use for all generations. 
-    
-        For example: 
+    """The default safety settings to use for all generations.
+
+        For example:
 
             from google.generativeai.types.safety_types import HarmBlockThreshold, HarmCategory
 

libs/genai/pyproject.toml

@@ -15,6 +15,7 @@ python = ">=3.9,<4.0"
 langchain-core = ">=0.3.15,<0.4"
 google-generativeai = "^0.8.0"
 pydantic = ">=2,<3"
+grpcio = "^1.66.2"
 
 [tool.poetry.group.test]
 optional = true
@@ -26,8 +27,14 @@ pytest-mock = "^3.10.0"
 syrupy = "^4.0.2"
 pytest-watcher = "^0.3.4"
 pytest-asyncio = "^0.21.1"
-numpy = "^1.26.2"
+types-requests = "^2.31.0.20231231"
+types-protobuf = "^4.24.0.4"
+numpy = [
+  { version = "^1", python = "<3.12" },
+  { version = "^1.26.2", python = ">=3.12" },
+]
 langchain-tests = "0.3.1"
+google-generativeai = "^0.8.0"
 
 [tool.codespell]
 ignore-words-list = "rouge"
@@ -59,7 +66,6 @@ mypy = "^1.10"
 types-requests = "^2.28.11.5"
 types-google-cloud-ndb = "^2.2.0.1"
 types-protobuf = "^4.24.0.20240302"
-numpy = "^1.26.2"
 
 
 [tool.poetry.group.dev]
@@ -68,6 +74,7 @@ optional = true
 [tool.poetry.group.dev.dependencies]
 types-requests = "^2.31.0.10"
 types-google-cloud-ndb = "^2.2.0.1"
+langchain-core = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core" }
 
 [tool.ruff.lint]
 select = [
@@ -77,7 +84,17 @@ select = [
 ]
 
 [tool.mypy]
-disallow_untyped_defs = "True"
+disallow_untyped_defs = true
+check_untyped_defs = true
+error_summary = false
+pretty = true
+show_column_numbers = true
+show_error_codes = true
+show_error_context = true
+warn_redundant_casts = true
+warn_unreachable = true
+warn_unused_configs = true
+warn_unused_ignores = true
 
 [tool.coverage.run]
 omit = ["tests/*"]

libs/genai/tests/integration_tests/test_chat_models.py

@@ -17,11 +17,8 @@
 from langchain_core.tools import tool
 from pydantic import BaseModel
 
-from langchain_google_genai import (
-    ChatGoogleGenerativeAI,
-    HarmBlockThreshold,
-    HarmCategory,
-)
+from langchain_google_genai import ChatGoogleGenerativeAI
+from langchain_google_genai._enums import HarmBlockThreshold, HarmCategory
 from langchain_google_genai.chat_models import ChatGoogleGenerativeAIError
 
 _MODEL = "models/gemini-1.0-pro-001"  # TODO: Use nano when it's available.

libs/genai/tests/integration_tests/test_llms.py

@@ -23,7 +23,7 @@ def test_google_generativeai_call(model_name: str) -> None:
     if model_name:
         llm = GoogleGenerativeAI(max_tokens=10, model=model_name)
     else:
-        llm = GoogleGenerativeAI(max_tokens=10)  # type: ignore[call-arg]
+        llm = GoogleGenerativeAI(max_tokens=10, model=model_names[0])
     output = llm("Say foo:")
     assert isinstance(output, str)
     assert llm._llm_type == "google_palm"

libs/genai/tests/unit_tests/test_chat_models.py

@@ -37,7 +37,7 @@ def test_integration_initialization() -> None:
     """Test chat model initialization."""
     llm = ChatGoogleGenerativeAI(
         model="gemini-nano",
-        google_api_key=SecretStr("..."),  # type: ignore[call-arg]
+        google_api_key=SecretStr("..."),
         top_k=2,
         top_p=1,
         temperature=0.7,
@@ -53,7 +53,7 @@ def test_integration_initialization() -> None:
 
     llm = ChatGoogleGenerativeAI(
         model="gemini-nano",
-        google_api_key=SecretStr("..."),  # type: ignore[call-arg]
+        google_api_key=SecretStr("..."),
         max_output_tokens=10,
     )
     ls_params = llm._get_ls_params()
@@ -67,7 +67,7 @@ def test_integration_initialization() -> None:
 
     ChatGoogleGenerativeAI(
         model="gemini-nano",
-        api_key=SecretStr("..."),
+        google_api_key=SecretStr("..."),
         top_k=2,
         top_p=1,
         temperature=0.7,
@@ -81,14 +81,14 @@ def test_initialization_inside_threadpool() -> None:
         executor.submit(
             ChatGoogleGenerativeAI,
             model="gemini-nano",
-            google_api_key=SecretStr("secret-api-key"),  # type: ignore[call-arg]
+            google_api_key=SecretStr("secret-api-key"),
         ).result()
 
 
 def test_initalization_without_async() -> None:
     chat = ChatGoogleGenerativeAI(
         model="gemini-nano",
-        google_api_key=SecretStr("secret-api-key"),  # type: ignore[call-arg]
+        google_api_key=SecretStr("secret-api-key"),
     )
     assert chat.async_client is None
 
@@ -97,7 +97,7 @@ def test_initialization_with_async() -> None:
     async def initialize_chat_with_async_client() -> ChatGoogleGenerativeAI:
         model = ChatGoogleGenerativeAI(
             model="gemini-nano",
-            google_api_key=SecretStr("secret-api-key"),  # type: ignore[call-arg]
+            google_api_key=SecretStr("secret-api-key"),
         )
         _ = model.async_client
         return model
@@ -110,15 +110,15 @@ async def initialize_chat_with_async_client() -> ChatGoogleGenerativeAI:
 def test_api_key_is_string() -> None:
     chat = ChatGoogleGenerativeAI(
         model="gemini-nano",
-        google_api_key=SecretStr("secret-api-key"),  # type: ignore[call-arg]
+        google_api_key=SecretStr("secret-api-key"),
     )
     assert isinstance(chat.google_api_key, SecretStr)
 
 
 def test_api_key_masked_when_passed_via_constructor(capsys: CaptureFixture) -> None:
     chat = ChatGoogleGenerativeAI(
         model="gemini-nano",
-        google_api_key=SecretStr("secret-api-key"),  # type: ignore[call-arg]
+        google_api_key=SecretStr("secret-api-key"),
     )
     print(chat.google_api_key, end="")  # noqa: T201
     captured = capsys.readouterr()
@@ -271,7 +271,7 @@ def test_additional_headers_support(headers: Optional[Dict[str, str]]) -> None:
     ):
         chat = ChatGoogleGenerativeAI(
             model="gemini-pro",
-            google_api_key=param_secret_api_key,  # type: ignore[call-arg]
+            google_api_key=param_secret_api_key,
             client_options=param_client_options,
             transport=param_transport,
             additional_headers=headers,
@@ -547,7 +547,7 @@ def test_parse_response_candidate(raw_candidate: Dict, expected: AIMessage) -> N
 
 
 def test_serialize() -> None:
-    llm = ChatGoogleGenerativeAI(model="gemini-pro-1.5", google_api_key="test-key")  # type: ignore[call-arg]
+    llm = ChatGoogleGenerativeAI(model="gemini-pro-1.5", api_key=SecretStr("test-key"))
     serialized = dumps(llm)
     llm_loaded = loads(
         serialized,