mirror of
https://github.com/hwchase17/langchain.git
synced 2026-07-14 13:47:41 +00:00
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>
124 lines
4.1 KiB
Python
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)
|