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https://github.com/hwchase17/langchain.git
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236e957abb
After this PR chat models will correctly handle pydantic 2 with
bind_tools and with_structured_output.
```python
import pydantic
print(pydantic.__version__)
```
2.8.2
```python
from langchain_openai import ChatOpenAI
from pydantic import BaseModel, Field
class Add(BaseModel):
x: int
y: int
model = ChatOpenAI().bind_tools([Add])
print(model.invoke('2 + 5').tool_calls)
model = ChatOpenAI().with_structured_output(Add)
print(type(model.invoke('2 + 5')))
```
```
[{'name': 'Add', 'args': {'x': 2, 'y': 5}, 'id': 'call_PNUFa4pdfNOYXxIMHc6ps2Do', 'type': 'tool_call'}]
<class '__main__.Add'>
```
```python
from langchain_openai import ChatOpenAI
from pydantic.v1 import BaseModel, Field
class Add(BaseModel):
x: int
y: int
model = ChatOpenAI().bind_tools([Add])
print(model.invoke('2 + 5').tool_calls)
model = ChatOpenAI().with_structured_output(Add)
print(type(model.invoke('2 + 5')))
```
```python
[{'name': 'Add', 'args': {'x': 2, 'y': 5}, 'id': 'call_hhiHYP441cp14TtrHKx3Upg0', 'type': 'tool_call'}]
<class '__main__.Add'>
```
Addresses issues: https://github.com/langchain-ai/langchain/issues/22782
---------
Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>
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
- 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_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 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')