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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> |
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.. | ||
__init__.py | ||
chat_models.py | ||
experimental.py | ||
llms.py | ||
output_parsers.py | ||
py.typed |