Files
langchain/libs/standard-tests/langchain_tests/unit_tests/tools.py
Mason Daugherty 5a016de53f chore: delete deprecated items (#33192)
Removed:
- `libs/core/langchain_core/chat_history.py`: `add_user_message` and
`add_ai_message` in favor of `add_messages` and `aadd_messages`
- `libs/core/langchain_core/language_models/base.py`: `predict`,
`predict_messages`, and async versions in favor of `invoke`. removed
`_all_required_field_names` since it was a wrapper on
`get_pydantic_field_names`
- `libs/core/langchain_core/language_models/chat_models.py`:
`callback_manager` param in favor of `callbacks`. `__call__` and
`call_as_llm` method in favor of `invoke`
- `libs/core/langchain_core/language_models/llms.py`: `callback_manager`
param in favor of `callbacks`. `__call__`, `predict`, `apredict`, and
`apredict_messages` methods in favor of `invoke`
- `libs/core/langchain_core/prompts/chat.py`: `from_role_strings` and
`from_strings` in favor of `from_messages`
- `libs/core/langchain_core/prompts/pipeline.py`: removed
`PipelinePromptTemplate`
- `libs/core/langchain_core/prompts/prompt.py`: `input_variables` param
on `from_file` as it wasn't used
- `libs/core/langchain_core/tools/base.py`: `callback_manager` param in
favor of `callbacks`
- `libs/core/langchain_core/tracers/context.py`: `tracing_enabled` in
favor of `tracing_enabled_v2`
- `libs/core/langchain_core/tracers/langchain_v1.py`: entire module
- `libs/core/langchain_core/utils/loading.py`: entire module,
`try_load_from_hub`
- `libs/core/langchain_core/vectorstores/in_memory.py`: `upsert` in
favor of `add_documents`
- `libs/standard-tests/langchain_tests/integration_tests/chat_models.py`
and `libs/standard-tests/langchain_tests/unit_tests/chat_models.py`:
`tool_choice_value` as models should accept `tool_choice="any"`
- `langchain` will consequently no longer expose these items if it was
previously

---------

Co-authored-by: Mohammad Mohtashim <45242107+keenborder786@users.noreply.github.com>
Co-authored-by: Caspar Broekhuizen <caspar@langchain.dev>
Co-authored-by: ccurme <chester.curme@gmail.com>
Co-authored-by: Christophe Bornet <cbornet@hotmail.com>
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
Co-authored-by: Sadra Barikbin <sadraqazvin1@yahoo.com>
Co-authored-by: Vadym Barda <vadim.barda@gmail.com>
2025-10-03 03:33:24 +00:00

124 lines
4.1 KiB
Python

"""Tools unit tests."""
from __future__ import annotations
import os
from abc import abstractmethod
from unittest import mock
import pytest
from langchain_core.tools import BaseTool
from pydantic import SecretStr
from langchain_tests.base import BaseStandardTests
class ToolsTests(BaseStandardTests):
"""Base class for testing tools.
This won't show in the documentation, but the docstrings will be inherited by
subclasses.
"""
@property
@abstractmethod
def tool_constructor(self) -> type[BaseTool] | BaseTool:
"""Returns a class or instance of a tool to be tested."""
...
@property
def tool_constructor_params(self) -> dict:
"""Returns a dictionary of parameters to pass to the tool constructor."""
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 - it should not
have {"name", "id", "args"} keys.
"""
return {}
@pytest.fixture
def tool(self) -> BaseTool:
"""Tool fixture."""
if isinstance(self.tool_constructor, BaseTool):
if self.tool_constructor_params != {}:
msg = (
"If tool_constructor is an instance of BaseTool, "
"tool_constructor_params must be empty"
)
raise ValueError(msg)
return self.tool_constructor
return self.tool_constructor(**self.tool_constructor_params)
class ToolsUnitTests(ToolsTests):
"""Base class for tools unit tests."""
@property
def init_from_env_params(self) -> tuple[dict, dict, dict]:
"""Init from env params.
Return env vars, init args, and expected instance attrs for initializing
from env vars.
"""
return {}, {}, {}
def test_init(self) -> None:
"""Test init.
Test that the tool can be initialized with :attr:`tool_constructor` and
:attr:`tool_constructor_params`. If this fails, check that the
keyword args defined in :attr:`tool_constructor_params` are valid.
"""
if isinstance(self.tool_constructor, BaseTool):
tool = self.tool_constructor
else:
tool = self.tool_constructor(**self.tool_constructor_params)
assert tool is not None
def test_init_from_env(self) -> None:
"""Test that the tool can be initialized from environment variables."""
env_params, tools_params, expected_attrs = self.init_from_env_params
if env_params:
with mock.patch.dict(os.environ, env_params):
tool = self.tool_constructor(**tools_params) # type: ignore[operator]
assert tool is not None
for k, expected in expected_attrs.items():
actual = getattr(tool, k)
if isinstance(actual, SecretStr):
actual = actual.get_secret_value()
assert actual == expected
def test_has_name(self, tool: BaseTool) -> None:
"""Tests that the tool has a name attribute to pass to chat models.
If this fails, add a `name` parameter to your tool.
"""
assert tool.name
def test_has_input_schema(self, tool: BaseTool) -> None:
"""Tests that the tool has an input schema.
If this fails, add an `args_schema` to your tool.
See
`this guide <https://python.langchain.com/docs/how_to/custom_tools/#subclass-basetool>`_
and see how `CalculatorInput` is configured in the
`CustomCalculatorTool.args_schema` attribute
"""
assert tool.get_input_schema()
def test_input_schema_matches_invoke_params(self, tool: BaseTool) -> None:
"""Tests that the provided example params match the declared input schema.
If this fails, update the `tool_invoke_params_example` attribute to match
the input schema (`args_schema`) of the tool.
"""
# this will be a pydantic object
input_schema = tool.get_input_schema()
assert input_schema(**self.tool_invoke_params_example)