🦜️🔗 langchain-tests

Looking for the JS/TS version? Check out LangChain.js.

Quick Install

pip install langchain-tests

🤔 What is this?

This is a testing library for LangChain integrations. It contains the base classes for a standard set of tests.

📖 Documentation

For full documentation, see the API reference.

📕 Releases & Versioning

See our Releases and Versioning policies.

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.

💁 Contributing

As an open-source project in a rapidly developing field, we are extremely open to contributions, whether it be in the form of a new feature, improved infrastructure, or better documentation.

For detailed information on how to contribute, see the Contributing Guide.

Usage

To add standard tests to an integration package (e.g., for a chat model), 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 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')

Release files for langchain-tests 1.1.9

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for langchain-tests 1.1.9
File	Size	Uploaded
langchain_tests-1.1.9.tar.gz	184.4 kB	May 21, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for langchain-tests 1.1.9
File	Interpreter	ABI	Platform	Reset
langchain_tests-1.1.9-py3-none-any.whl 66.3 kB May 21, 2026	Python 3	none	any	Details

Total release size: 250.8 kB

Release files / langchain_tests-1.1.9.tar.gz

Download URL	langchain_tests-1.1.9.tar.gz
Size	184.4 kB
Tags	Source
SHA-256 checksum How to use checksums	`a977a0c8f9a42ba2021a5ae59d468e4023f98a83818a3cb30e12c1dfab830203`
BLAKE2b-256 checksum How to use checksums	`940e6eef4ddcc3503d40de4486abc923a48d5853a310d2b2752123e7a3c713b1`
Upload date	May 21, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.13`

Release files / langchain_tests-1.1.9-py3-none-any.whl

Download URL	langchain_tests-1.1.9-py3-none-any.whl
Size	66.3 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`f33e36e2015da437df2001ec6949b443de09dd37d021dea6160cf85912ccf05f`
BLAKE2b-256 checksum How to use checksums	`cabbef5ccff7c22938e28716ecf3c4cc468082843df7f3b2214a931cfcaae98a`
Upload date	May 21, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	Yes
Uploaded via	`twine/6.1.0 CPython/3.13.13`