standard-tests: tool tests (#28244)

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Erick Friis 2024-11-20 19:26:16 -08:00 committed by GitHub
parent 35e6052df5
commit 60e572f591
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3 changed files with 84 additions and 15 deletions

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@ -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",

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@ -10,50 +10,56 @@ class ToolsIntegrationTests(ToolsTests):
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:
"""

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@ -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}