Merge pull request #72 from langchain-ai/cc/standard_tests

add standard tests

libs/aws/pyproject.toml

@@ -25,6 +25,7 @@ pytest-cov = "^4.1.0"
 syrupy = "^4.0.2"
 pytest-asyncio = "^0.23.2"
 langchain-core = { git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/core" }
+langchain-standard-tests = {git = "https://github.com/langchain-ai/langchain.git", subdirectory = "libs/standard-tests"}
 
 [tool.poetry.group.codespell]
 optional = true

libs/aws/tests/integration_tests/chat_models/test_standard.py

@@ -0,0 +1,76 @@
+"""Standard LangChain interface tests"""
+
+from typing import Type
+
+import pytest
+from langchain_core.language_models import BaseChatModel
+from langchain_standard_tests.integration_tests import ChatModelIntegrationTests
+
+from langchain_aws.chat_models.bedrock import ChatBedrock
+
+
+class TestBedrockStandard(ChatModelIntegrationTests):
+    @pytest.fixture
+    def chat_model_class(self) -> Type[BaseChatModel]:
+        return ChatBedrock
+
+    @pytest.fixture
+    def chat_model_params(self) -> dict:
+        return {
+            "model_id": "anthropic.claude-3-sonnet-20240229-v1:0",
+        }
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_usage_metadata(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_usage_metadata(
+            chat_model_class,
+            chat_model_params,
+        )
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_stop_sequence(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_stop_sequence(
+            chat_model_class,
+            chat_model_params,
+        )
+
+    @pytest.mark.xfail(reason="Not yet implemented.")
+    def test_tool_message_histories_string_content(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+        chat_model_has_tool_calling: bool,
+    ) -> None:
+        super().test_tool_message_histories_string_content(
+            chat_model_class, chat_model_params, chat_model_has_tool_calling
+        )
+
+    @pytest.mark.xfail(reason="Not yet implemented.")
+    def test_tool_message_histories_list_content(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+        chat_model_has_tool_calling: bool,
+    ) -> None:
+        super().test_tool_message_histories_list_content(
+            chat_model_class, chat_model_params, chat_model_has_tool_calling
+        )
+
+    @pytest.mark.xfail(reason="Not yet implemented.")
+    def test_structured_few_shot_examples(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+        chat_model_has_tool_calling: bool,
+    ) -> None:
+        super().test_structured_few_shot_examples(
+            chat_model_class, chat_model_params, chat_model_has_tool_calling
+        )

libs/aws/tests/unit_tests/test_standard.py

@@ -0,0 +1,44 @@
+"""Standard LangChain interface tests"""
+
+from typing import Type
+
+import pytest
+from langchain_core.language_models import BaseChatModel
+from langchain_standard_tests.unit_tests import ChatModelUnitTests
+
+from langchain_aws.chat_models.bedrock import ChatBedrock
+
+
+class TestBedrockStandard(ChatModelUnitTests):
+    @pytest.fixture
+    def chat_model_class(self) -> Type[BaseChatModel]:
+        return ChatBedrock
+
+    @pytest.fixture
+    def chat_model_params(self) -> dict:
+        return {
+            "model_id": "anthropic.claude-3-sonnet-20240229-v1:0",
+            "region_name": "us-east-1",
+        }
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_chat_model_init_api_key(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_chat_model_init_api_key(
+            chat_model_class,
+            chat_model_params,
+        )
+
+    @pytest.mark.xfail(reason="Not implemented.")
+    def test_standard_params(
+        self,
+        chat_model_class: Type[BaseChatModel],
+        chat_model_params: dict,
+    ) -> None:
+        super().test_standard_params(
+            chat_model_class,
+            chat_model_params,
+        )