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core,groq,openai,mistralai,robocorp,fireworks,anthropic[patch]: Update BaseModel subclass and instance checks to handle both v1 and proper namespaces (#24417)
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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@@ -53,11 +53,16 @@ from langchain_core.outputs import (
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ChatGenerationChunk,
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ChatResult,
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)
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from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
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from langchain_core.pydantic_v1 import (
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BaseModel,
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Field,
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SecretStr,
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)
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from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
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from langchain_core.tools import BaseTool
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from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
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from langchain_core.utils.function_calling import convert_to_openai_tool
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from langchain_core.utils.pydantic import is_basemodel_subclass
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from requests.exceptions import HTTPError
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from tenacity import (
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before_sleep_log,
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@@ -865,7 +870,7 @@ class ChatTongyi(BaseChatModel):
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"""
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if kwargs:
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raise ValueError(f"Received unsupported arguments {kwargs}")
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is_pydantic_schema = isinstance(schema, type) and issubclass(schema, BaseModel)
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is_pydantic_schema = isinstance(schema, type) and is_basemodel_subclass(schema)
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llm = self.bind_tools([schema])
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if is_pydantic_schema:
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output_parser: OutputParserLike = PydanticToolsParser(
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