Standard tests ensure your integration works as expected. When creating either a custom class for yourself or to publish in a LangChain integration, it is important to add standard tests to ensure it works as expected. This guide will show you how to add standard tests to each integration type.

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Setup

First, install the required dependencies:

langchain-core

Defines the interfaces we want to import to define our custom components

langchain-tests

Provides the standard tests and pytest plugins necessary to run them
Because added tests in new versions of langchain-tests can break your CI/CD pipelines, we recommend pinning to the latest version of langchain-tests to avoid unexpected changes.
pip install -U langchain-core
pip install -U langchain-tests
There are 2 namespaces in the langchain-tests package:
Both types of tests are implemented as pytest class-based test suites.

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Implementing standard tests

Depending on your integration type, you will need to implement either or both unit and integration tests. By subclassing the standard test suite for your integration type, you get the full collection of standard tests for that type. For a test run to be successful, the a given test should pass only if the model supports the capability being tested. Otherwise, the test should be skipped. Because different integrations offer unique sets of features, most standard tests provided by LangChain are opt-in by default to prevent false positives. Consequently, you will need to override properties to indicate which features your integration supports - see the below example for an illustration.
tests/integration_tests/test_standard.py
# Indicate that a chat model supports image inputs

class TestChatParrotLinkStandard(ChatModelIntegrationTests):
    # ... other required properties

    @property
    def supports_image_inputs(self) -> bool:
        return True  # (The default is False)
You should typically organize tests in these subdirectories relative to the root of your package:
  • tests/unit_tests for unit tests
  • tests/integration_tests for integration tests
To see the complete list of configurable capabilities and their defaults, visit the API reference for your integration type. Reference pages include code examples for implementing standard tests.

Unit tests

Integration tests

Here are some example implementations of standard tests from popular integrations:

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Running tests

If bootstrapping an integration from a template, a Makefile is provided that includes targets for running unit and integration tests: 
make test
make integration_test
Otherwise, if you follow the recommended directory structure, you can run tests with: 
# Run all tests
uv run --group test pytest tests/unit_tests/
uv run --group test --group test_integration pytest -n auto tests/integration_tests/

# For certain unit tests, you may need to set certain flags and environment variables:
TIKTOKEN_CACHE_DIR=tiktoken_cache uv run --group test pytest --disable-socket --allow-unix-socket tests/unit_tests/

# Run a specific test file
uv run --group test pytest tests/integration_tests/test_chat_models.py

# Run a specific test function in a file
uv run --group test pytest tests/integration_tests/test_chat_models.py::test_chat_completions

# Run a specific test function within a class
uv run --group test pytest tests/integration_tests/test_chat_models.py::TestChatParrotLinkIntegration::test_chat_completions

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Troubleshooting

For a full list of the standard test suites that are available, as well as information on which tests are included and how to troubleshoot common issues, see the Standard Tests API Reference. You can find troubleshooting guides under the individual test suites listed in that API Reference. For example, here is the guide for ChatModelIntegrationTests.test_usage_metadata.