fix tests

Author: lkuligin

libs/vertexai/langchain_google_vertexai/functions_utils.py

@@ -248,15 +248,21 @@ def _format_to_gapic_function_declaration(
     tool: _FunctionDeclarationLike,
 ) -> gapic.FunctionDeclaration:
     "Format tool into the Vertex function declaration."
+    print("_format_to_gapic_function_declaration")
+    print(tool)
     if isinstance(tool, BaseTool):
         return _format_base_tool_to_function_declaration(tool)
     elif isinstance(tool, type) and issubclass(tool, BaseModel):
         return _format_pydantic_to_function_declaration(tool)
-    elif callable(tool):
+    elif callable(tool) and not (
+        isinstance(tool, type) and hasattr(tool, "__annotations__")
+    ):
         return _format_base_tool_to_function_declaration(callable_as_lc_tool()(tool))
     elif isinstance(tool, vertexai.FunctionDeclaration):
         return _format_vertex_to_function_declaration(tool)
-    elif isinstance(tool, dict):
+    elif isinstance(tool, dict) or (
+        isinstance(tool, type) and hasattr(tool, "__annotations__")
+    ):
         # this could come from
         # 'langchain_core.utils.function_calling.convert_to_openai_tool'
         function = convert_to_openai_tool(cast(dict, tool))["function"]

libs/vertexai/poetry.lock

@@ -12,7 +12,7 @@ license = "MIT"
 
 [tool.poetry.dependencies]
 python = ">=3.9,<4.0"
-langchain-core = ">=0.3.27,<0.4"
+langchain-core = ">=0.3.31,<0.4"
 google-cloud-aiplatform = "^1.76.0"
 google-cloud-storage = "^2.18.0"
 # optional dependencies

libs/vertexai/pyproject.toml

@@ -5,7 +5,6 @@
 import pytest
 from langchain_core.language_models import BaseChatModel
 from langchain_core.rate_limiters import InMemoryRateLimiter
-from langchain_core.tools import BaseTool
 from langchain_tests.integration_tests import ChatModelIntegrationTests
 
 from langchain_google_vertexai import ChatVertexAI
@@ -41,28 +40,6 @@ def supports_audio_inputs(self) -> bool:
         return True
 
 
-@pytest.mark.first
-class TestGeminiAIStandard(ChatModelIntegrationTests):
-    @property
-    def chat_model_class(self) -> Type[BaseChatModel]:
-        return ChatVertexAI
-
-    @property
-    def chat_model_params(self) -> dict:
-        return {
-            "model_name": "gemini-1.0-pro-001",
-            "rate_limiter": rate_limiter,
-            "temperature": 0,
-            "api_transport": None,
-        }
-
-    @pytest.mark.xfail(reason="Gemini 1.0 doesn't support tool_choice='any'")
-    def test_structured_few_shot_examples(
-        self, model: BaseChatModel, my_adder_tool: BaseTool
-    ) -> None:
-        super().test_structured_few_shot_examples(model, my_adder_tool)
-
-
 class TestGemini_15_AIStandard(ChatModelIntegrationTests):
     @property
     def chat_model_class(self) -> Type[BaseChatModel]:
@@ -71,7 +48,7 @@ def chat_model_class(self) -> Type[BaseChatModel]:
     @property
     def chat_model_params(self) -> dict:
         return {
-            "model_name": "gemini-1.5-pro-001",
+            "model_name": "gemini-1.5-pro-002",
             "rate_limiter": rate_limiter,
             "temperature": 0,
             "api_transport": None,

libs/vertexai/tests/integration_tests/test_standard.py

@@ -1,32 +1,4 @@
 # serializer version: 1
-# name: TestGeminiAIStandard.test_serdes[serialized]
-  dict({
-    'id': list([
-      'langchain',
-      'chat_models',
-      'vertexai',
-      'ChatVertexAI',
-    ]),
-    'kwargs': dict({
-      'default_metadata': list([
-      ]),
-      'location': 'us-central1',
-      'max_output_tokens': 100,
-      'max_retries': 2,
-      'model_family': '1',
-      'model_name': 'gemini-1.0-pro-001',
-      'n': 1,
-      'project': 'test-project',
-      'request_parallelism': 5,
-      'stop': list([
-      ]),
-      'temperature': 0.0,
-    }),
-    'lc': 1,
-    'name': 'ChatVertexAI',
-    'type': 'constructor',
-  })
-# ---
 # name: TestGemini_15_AIStandard.test_serdes[serialized]
   dict({
     'id': list([

libs/vertexai/tests/unit_tests/__snapshots__/test_standard.ambr

@@ -29,7 +29,9 @@
     PydanticToolsParser,
 )
 from pydantic import BaseModel
-from vertexai.generative_models import SafetySetting as VertexSafetySetting
+from vertexai.generative_models import (  # type: ignore
+    SafetySetting as VertexSafetySetting,
+)
 from vertexai.language_models import (  # type: ignore
     ChatMessage,
     InputOutputTextPair,

libs/vertexai/tests/unit_tests/test_chat_models.py

@@ -6,16 +6,6 @@
 from langchain_google_vertexai import ChatVertexAI
 
 
-class TestGeminiAIStandard(ChatModelUnitTests):
-    @property
-    def chat_model_class(self) -> Type[BaseChatModel]:
-        return ChatVertexAI
-
-    @property
-    def chat_model_params(self) -> dict:
-        return {"model_name": "gemini-1.0-pro-001"}
-
-
 class TestGemini_15_AIStandard(ChatModelUnitTests):
     @property
     def chat_model_class(self) -> Type[BaseChatModel]: