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langchain/libs/standard-tests
ccurme 181dfef118
core, standard tests, partner packages: add test for model params (#21677)
1. Adds `.get_ls_params` to BaseChatModel which returns
```python
class LangSmithParams(TypedDict, total=False):
    ls_provider: str
    ls_model_name: str
    ls_model_type: Literal["chat"]
    ls_temperature: Optional[float]
    ls_max_tokens: Optional[int]
    ls_stop: Optional[List[str]]
```
by default it will only return
```python
{ls_model_type="chat", ls_stop=stop}
```

2. Add these params to inheritable metadata in
`CallbackManager.configure`

3. Implement `.get_ls_params` and populate all params for Anthropic +
all subclasses of BaseChatOpenAI

Sample trace:
https://smith.langchain.com/public/d2962673-4c83-47c7-b51e-61d07aaffb1b/r

**OpenAI**:
<img width="984" alt="Screenshot 2024-05-17 at 10 03 35 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/2ef41f74-a9df-4e0e-905d-da74fa82a910">

**Anthropic**:
<img width="978" alt="Screenshot 2024-05-17 at 10 06 07 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/39701c9f-7da5-4f1a-ab14-84e9169d63e7">

**Mistral** (and all others for which params are not yet populated):
<img width="977" alt="Screenshot 2024-05-17 at 10 08 43 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/37d7d894-fec2-4300-986f-49a5f0191b03">
3 days ago
..
langchain_standard_tests core, standard tests, partner packages: add test for model params (#21677) 3 days ago
scripts standard-tests: a standard unit and integration test set (#20182) 1 month ago
tests standard-tests: a standard unit and integration test set (#20182) 1 month ago
Makefile standard-tests: a standard unit and integration test set (#20182) 1 month ago
README.md standard-tests: a standard unit and integration test set (#20182) 1 month ago
poetry.lock multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646) 7 days ago
pyproject.toml multiple: core 0.2 nonbreaking dep, check_diff community->langchain dep (#21646) 7 days ago

README.md

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')