standard-tests: tool tests (#28244)

docs/docs/contributing/how_to/integrations/standard_tests.ipynb

@@ -13,12 +13,12 @@
     "First, let's install 2 dependencies:\n",
     "\n",
     "- `langchain-core` will define the interfaces we want to import to define our custom tool.\n",
-    "- `langchain-tests==0.3.2` will provide the standard tests we want to use.\n",
+    "- `langchain-tests==0.3.3` will provide the standard tests we want to use.\n",
     "\n",
     ":::note\n",
     "\n",
     "Because added tests in new versions of `langchain-tests` will always break your CI/CD pipelines, we recommend pinning the \n",
-    "version of `langchain-tests==0.3.2` to avoid unexpected changes.\n",
+    "version of `langchain-tests` to avoid unexpected changes.\n",
     "\n",
     ":::"
    ]
@@ -178,7 +178,7 @@
     "\n",
     "```bash\n",
     "# run unit tests without network access\n",
-    "pytest --disable-socket --enable-unix-socket tests/unit_tests\n",
+    "pytest --disable-socket --allow-unix-socket tests/unit_tests\n",
     "\n",
     "# run integration tests\n",
     "pytest tests/integration_tests\n",

libs/standard-tests/langchain_tests/integration_tests/tools.py

@@ -10,50 +10,56 @@ def test_invoke_matches_output_schema(self, tool: BaseTool) -> None:
         If invoked with a ToolCall, the tool should return a valid ToolMessage content.
         """
         tool_call = ToolCall(
-            name=tool.name, args=self.tool_invoke_params_example, id=None
+            name=tool.name,
+            args=self.tool_invoke_params_example,
+            id="123",
+            type="tool_call",
         )
         result = tool.invoke(tool_call)
 
         if tool.response_format == "content":
-            content = result
+            tool_message = result
         elif tool.response_format == "content_and_artifact":
             # should be (content, artifact)
             assert isinstance(result, tuple)
             assert len(result) == 2
-            content, artifact = result
+            tool_message, artifact = result
 
             assert artifact  # artifact can be anything, but shouldn't be none
 
         # check content is a valid ToolMessage content
-        assert isinstance(content, (str, list))
-        if isinstance(content, list):
+        assert isinstance(tool_message.content, (str, list))
+        if isinstance(tool_message.content, list):
             # content blocks must be str or dict
-            assert all(isinstance(c, (str, dict)) for c in content)
+            assert all(isinstance(c, (str, dict)) for c in tool_message.content)
 
     async def test_async_invoke_matches_output_schema(self, tool: BaseTool) -> None:
         """
         If ainvoked with a ToolCall, the tool should return a valid ToolMessage content.
         """
         tool_call = ToolCall(
-            name=tool.name, args=self.tool_invoke_params_example, id=None
+            name=tool.name,
+            args=self.tool_invoke_params_example,
+            id="123",
+            type="tool_call",
         )
         result = await tool.ainvoke(tool_call)
 
         if tool.response_format == "content":
-            content = result
+            tool_message = result
         elif tool.response_format == "content_and_artifact":
             # should be (content, artifact)
             assert isinstance(result, tuple)
             assert len(result) == 2
-            content, artifact = result
+            tool_message, artifact = result
 
             assert artifact  # artifact can be anything, but shouldn't be none
 
         # check content is a valid ToolMessage content
-        assert isinstance(content, (str, list))
-        if isinstance(content, list):
+        assert isinstance(tool_message.content, (str, list))
+        if isinstance(tool_message.content, list):
             # content blocks must be str or dict
-            assert all(isinstance(c, (str, dict)) for c in content)
+            assert all(isinstance(c, (str, dict)) for c in tool_message.content)
 
     def test_invoke_no_tool_call(self, tool: BaseTool) -> None:
         """

libs/standard-tests/tests/unit_tests/test_basic_tool.py

@@ -0,0 +1,63 @@
+from typing import Type
+
+from langchain_core.tools import BaseTool
+
+from langchain_tests.integration_tests import ToolsIntegrationTests
+from langchain_tests.unit_tests import ToolsUnitTests
+
+
+class ParrotMultiplyTool(BaseTool):  # type: ignore
+    name: str = "ParrotMultiplyTool"
+    description: str = (
+        "Multiply two numbers like a parrot. Parrots always add "
+        "eighty for their matey."
+    )
+
+    def _run(self, a: int, b: int) -> int:
+        return a * b + 80
+
+
+class TestParrotMultiplyToolUnit(ToolsUnitTests):
+    @property
+    def tool_constructor(self) -> Type[ParrotMultiplyTool]:
+        return ParrotMultiplyTool
+
+    @property
+    def tool_constructor_params(self) -> dict:
+        # if your tool constructor instead required initialization arguments like
+        # `def __init__(self, some_arg: int):`, you would return those here
+        # as a dictionary, e.g.: `return {'some_arg': 42}`
+        return {}
+
+    @property
+    def tool_invoke_params_example(self) -> dict:
+        """
+        Returns a dictionary representing the "args" of an example tool call.
+
+        This should NOT be a ToolCall dict - i.e. it should not
+        have {"name", "id", "args"} keys.
+        """
+        return {"a": 2, "b": 3}
+
+
+class TestParrotMultiplyToolIntegration(ToolsIntegrationTests):
+    @property
+    def tool_constructor(self) -> Type[ParrotMultiplyTool]:
+        return ParrotMultiplyTool
+
+    @property
+    def tool_constructor_params(self) -> dict:
+        # if your tool constructor instead required initialization arguments like
+        # `def __init__(self, some_arg: int):`, you would return those here
+        # as a dictionary, e.g.: `return {'some_arg': 42}`
+        return {}
+
+    @property
+    def tool_invoke_params_example(self) -> dict:
+        """
+        Returns a dictionary representing the "args" of an example tool call.
+
+        This should NOT be a ToolCall dict - i.e. it should not
+        have {"name", "id", "args"} keys.
+        """
+        return {"a": 2, "b": 3}