langchain/libs/standard-tests
Bagatur d96f67b06f
standard-tests[patch]: Update chat model standard tests (#22378)
- Refactor standard test classes to make them easier to configure
- Update openai to support stop_sequences init param
- Update groq to support stop_sequences init param
- Update fireworks to support max_retries init param
- Update ChatModel.bind_tools to type tool_choice
- Update groq to handle tool_choice="any". **this may be controversial**

---------

Co-authored-by: Chester Curme <chester.curme@gmail.com>
2024-06-17 13:37:41 -07:00
..
langchain_standard_tests standard-tests[patch]: Update chat model standard tests (#22378) 2024-06-17 13:37:41 -07:00
scripts standard-tests: a standard unit and integration test set (#20182) 2024-04-09 12:43:00 -07:00
tests standard-tests: a standard unit and integration test set (#20182) 2024-04-09 12:43:00 -07:00
Makefile standard-tests: a standard unit and integration test set (#20182) 2024-04-09 12:43:00 -07:00
poetry.lock multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646) 2024-05-13 19:50:36 -07:00
pyproject.toml standard-tests[patch]: Release 0.1.1 (#22984) 2024-06-17 15:31:34 +00:00
README.md standard-tests: a standard unit and integration test set (#20182) 2024-04-09 12:43:00 -07:00

langchain-standard-tests

This is an INTERNAL library for the LangChain project. It contains the base classes for a standard set of tests.

Installation

This package will NOT be regularly published to pypi. It is intended to be installed directly from github at test time.

Pip:

```bash
pip install git+https://github.com/langchain-ai/langchain.git#subdirectory=libs/standard-tests
```

Poetry:

```bash
poetry add git+https://github.com/langchain-ai/langchain.git#subdirectory=libs/standard-tests
```

Usage

To add standard tests to an integration package's e.g. ChatModel, you need to create

  1. A unit test class that inherits from ChatModelUnitTests
  2. An integration test class that inherits from ChatModelIntegrationTests

tests/unit_tests/test_standard.py:

"""Standard LangChain interface tests"""

from typing import Type

import pytest
from langchain_core.language_models import BaseChatModel
from langchain_standard_tests.unit_tests import ChatModelUnitTests

from langchain_parrot_chain import ChatParrotChain


class TestParrotChainStandard(ChatModelUnitTests):
    @pytest.fixture
    def chat_model_class(self) -> Type[BaseChatModel]:
        return ChatParrotChain

tests/integration_tests/test_standard.py:

"""Standard LangChain interface tests"""

from typing import Type

import pytest
from langchain_core.language_models import BaseChatModel
from langchain_standard_tests.integration_tests import ChatModelIntegrationTests

from langchain_parrot_chain import ChatParrotChain


class TestParrotChainStandard(ChatModelIntegrationTests):
    @pytest.fixture
    def chat_model_class(self) -> Type[BaseChatModel]:
        return ChatParrotChain

Reference

The following fixtures are configurable in the test classes. Anything not marked as required is optional.

  • chat_model_class (required): The class of the chat model to be tested
  • chat_model_params: The keyword arguments to pass to the chat model constructor
  • chat_model_has_tool_calling: Whether the chat model can call tools. By default, this is set to hasattr(chat_model_class, 'bind_tools)
  • chat_model_has_structured_output: Whether the chat model can structured output. By default, this is set to hasattr(chat_model_class, 'with_structured_output')