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{ | ||
"cells": [ | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"# How to add standard tests to a tool\n", | ||
"\n", | ||
"When creating either a custom tool or a new tool to publish in a LangChain integration, it is important to add standard tests to ensure the tool works as expected. This guide will show you how to add standard tests to a tool.\n", | ||
"\n", | ||
"## Setup\n", | ||
"\n", | ||
"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==0.3.0` will provide the standard tests we want to use.\n", | ||
"\n", | ||
":::note\n", | ||
"\n", | ||
"The `langchain-tests` package contains the module `langchain_standard_tests`. This name\n", | ||
"mistmatch is due to this package historically being called `langchain_standard_tests` and\n", | ||
"the name not being available on PyPi. This will either be reconciled by our \n", | ||
"[PEP 541 request](https://github.com/pypi/support/issues/5062) (we welcome upvotes!), \n", | ||
"or in a new release of `langchain-tests`.\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==0.3.0` to avoid unexpected changes.\n", | ||
"\n", | ||
":::" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"%pip install -U langchain-core langchain-tests==0.3.0 pytest pytest-socket" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"Let's say we're publishing a package, `langchain_parrot_link`, that exposes a\n", | ||
"tool called `ParrotMultiplyTool`:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# title=\"langchain_parrot_link/tools.py\"\n", | ||
"from langchain_core.tools import BaseTool\n", | ||
"\n", | ||
"\n", | ||
"class ParrotMultiplyTool(BaseTool):\n", | ||
" name: str = \"ParrotMultiplyTool\"\n", | ||
" description: str = (\n", | ||
" \"Multiply two numbers like a parrot. Parrots always add \"\n", | ||
" \"eighty for their matey.\"\n", | ||
" )\n", | ||
"\n", | ||
" def _run(self, a: int, b: int) -> int:\n", | ||
" return a * b + 80" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"And we'll assume you've structured your package the same way as the main LangChain\n", | ||
"packages:\n", | ||
"\n", | ||
"```\n", | ||
"/\n", | ||
"├── langchain_parrot_link/\n", | ||
"│ └── tools.py\n", | ||
"└── tests/\n", | ||
" ├── unit_tests/\n", | ||
" │ └── test_tools.py\n", | ||
" └── integration_tests/\n", | ||
" └── test_tools.py\n", | ||
"```\n", | ||
"\n", | ||
"## Add and configure standard tests\n", | ||
"\n", | ||
"There are 2 namespaces in the `langchain-tests` package: \n", | ||
"\n", | ||
"- unit tests (`langchain_standard_tests.unit_tests`): designed to be used to test the tool in isolation and without access to external services\n", | ||
"- integration tests (`langchain_standard_tests.integration_tests`): designed to be used to test the tool with access to external services (in particular, the external service that the tool is designed to interact with).\n", | ||
"\n", | ||
":::note\n", | ||
"\n", | ||
"Integration tests can also be run without access to external services, **if** they are properly mocked.\n", | ||
"\n", | ||
":::\n", | ||
"\n", | ||
"Both types of tests are implemented as [`pytest` class-based test suites](https://docs.pytest.org/en/7.1.x/getting-started.html#group-multiple-tests-in-a-class).\n", | ||
"\n", | ||
"By subclassing the base classes for each type of standard test (see below), you get all of the standard tests for that type, and you\n", | ||
"can override the properties that the test suite uses to configure the tests.\n", | ||
"\n", | ||
"### Standard tools tests\n", | ||
"\n", | ||
"Here's how you would configure the standard unit tests for the custom tool, e.g. in `tests/test_tools.py`:" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": { | ||
"title": "tests/test_custom_tool.py" | ||
}, | ||
"outputs": [], | ||
"source": [ | ||
"# title=\"tests/unit_tests/test_custom_tool.py\"\n", | ||
"from typing import Type\n", | ||
"\n", | ||
"from langchain_parrot_link.tools import ParrotMultiplyTool\n", | ||
"from langchain_standard_tests.unit_tests import ToolsUnitTests\n", | ||
"\n", | ||
"\n", | ||
"class MultiplyToolUnitTests(ToolsUnitTests):\n", | ||
" @property\n", | ||
" def tool_constructor(self) -> Type[ParrotMultiplyTool]:\n", | ||
" return ParrotMultiplyTool\n", | ||
"\n", | ||
" def tool_constructor_params(self) -> dict:\n", | ||
" # if your tool constructor instead required initialization arguments like\n", | ||
" # `def __init__(self, some_arg: int):`, you would return those here\n", | ||
" # as a dictionary, e.g.: `return {'some_arg': 42}`\n", | ||
" return {}\n", | ||
"\n", | ||
" def tool_invoke_params_example(self) -> dict:\n", | ||
" \"\"\"\n", | ||
" Returns a dictionary representing the \"args\" of an example tool call.\n", | ||
"\n", | ||
" This should NOT be a ToolCall dict - i.e. it should not\n", | ||
" have {\"name\", \"id\", \"args\"} keys.\n", | ||
" \"\"\"\n", | ||
" return {\"a\": 2, \"b\": 3}" | ||
] | ||
}, | ||
{ | ||
"cell_type": "code", | ||
"execution_count": null, | ||
"metadata": {}, | ||
"outputs": [], | ||
"source": [ | ||
"# title=\"tests/integration_tests/test_custom_tool.py\"\n", | ||
"from typing import Type\n", | ||
"\n", | ||
"from langchain_parrot_link.tools import ParrotMultiplyTool\n", | ||
"from langchain_standard_tests.integration_tests import ToolsIntegrationTests\n", | ||
"\n", | ||
"\n", | ||
"class MultiplyToolIntegrationTests(ToolsIntegrationTests):\n", | ||
" @property\n", | ||
" def tool_constructor(self) -> Type[ParrotMultiplyTool]:\n", | ||
" return ParrotMultiplyTool\n", | ||
"\n", | ||
" def tool_constructor_params(self) -> dict:\n", | ||
" # if your tool constructor instead required initialization arguments like\n", | ||
" # `def __init__(self, some_arg: int):`, you would return those here\n", | ||
" # as a dictionary, e.g.: `return {'some_arg': 42}`\n", | ||
" return {}\n", | ||
"\n", | ||
" def tool_invoke_params_example(self) -> dict:\n", | ||
" \"\"\"\n", | ||
" Returns a dictionary representing the \"args\" of an example tool call.\n", | ||
"\n", | ||
" This should NOT be a ToolCall dict - i.e. it should not\n", | ||
" have {\"name\", \"id\", \"args\"} keys.\n", | ||
" \"\"\"\n", | ||
" return {\"a\": 2, \"b\": 3}" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [ | ||
"and you would run these with the following commands from your project root\n", | ||
"\n", | ||
"```bash\n", | ||
"# run unit tests without network access\n", | ||
"pytest --disable-socket --enable-unix-socket tests/unit_tests\n", | ||
"\n", | ||
"# run integration tests\n", | ||
"pytest tests/integration_tests\n", | ||
"```" | ||
] | ||
}, | ||
{ | ||
"cell_type": "markdown", | ||
"metadata": {}, | ||
"source": [] | ||
} | ||
], | ||
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"kernelspec": { | ||
"display_name": ".venv", | ||
"language": "python", | ||
"name": "python3" | ||
}, | ||
"language_info": { | ||
"codemirror_mode": { | ||
"name": "ipython", | ||
"version": 3 | ||
}, | ||
"file_extension": ".py", | ||
"mimetype": "text/x-python", | ||
"name": "python", | ||
"nbconvert_exporter": "python", | ||
"pygments_lexer": "ipython3", | ||
"version": "3.11.4" | ||
} | ||
}, | ||
"nbformat": 4, | ||
"nbformat_minor": 2 | ||
} |
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