mirror of
https://github.com/hwchase17/langchain.git
synced 2025-10-22 09:41:52 +00:00
52b0570bec
- Support thinking blocks in core's `convert_to_openai_messages` (pass through instead of error) - Ignore thinking blocks in ChatOpenAI (instead of error) - Support Anthropic-style image blocks in ChatOpenAI --- Standard integration tests include a `supports_anthropic_inputs` property which is currently enabled only for tests on `ChatAnthropic`. This test enforces compatibility with message histories of the form: ``` - system message - human message - AI message with tool calls specified only through `tool_use` content blocks - human message containing `tool_result` and an additional `text` block ``` It additionally checks support for Anthropic-style image inputs if `supports_image_inputs` is enabled. Here we change this test, such that if you enable `supports_anthropic_inputs`: - You support AI messages with text and `tool_use` content blocks - You support Anthropic-style image inputs (if `supports_image_inputs` is enabled) - You support thinking content blocks. That is, we add a test case for thinking content blocks, but we also remove the requirement of handling tool results within HumanMessages (motivated by existing agent abstractions, which should all return ToolMessage). We move that requirement to a ChatAnthropic-specific test.
langchain-tests
This is a testing library for LangChain integrations. It contains the base classes for a standard set of tests.
Installation
We encourage pinning your version to a specific version in order to avoid breaking your CI when we publish new tests. We recommend upgrading to the latest version periodically to make sure you have the latest tests.
Not pinning your version will ensure you always have the latest tests, but it may also break your CI if we introduce tests that your integration doesn't pass.
Pip:
```bash
pip install -U langchain-tests
```
Poetry:
```bash
poetry add langchain-tests
```
Usage
To add standard tests to an integration package's e.g. ChatModel, you need to create
- A unit test class that inherits from ChatModelUnitTests
- 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_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_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 testedchat_model_params: The keyword arguments to pass to the chat model constructorchat_model_has_tool_calling: Whether the chat model can call tools. By default, this is set tohasattr(chat_model_class, 'bind_tools)chat_model_has_structured_output: Whether the chat model can structured output. By default, this is set tohasattr(chat_model_class, 'with_structured_output')