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>

libs/community/langchain_community/chains/ernie_functions/base.py

@@ -24,6 +24,7 @@ from langchain_core.output_parsers import (
 from langchain_core.prompts import BasePromptTemplate
 from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables import Runnable
+from langchain_core.utils.pydantic import is_basemodel_subclass
 
 from langchain_community.output_parsers.ernie_functions import (
     JsonOutputFunctionsParser,
@@ -94,7 +95,7 @@ def _get_python_function_arguments(function: Callable, arg_descriptions: dict) -
     for arg, arg_type in annotations.items():
         if arg == "return":
             continue
-        if isinstance(arg_type, type) and issubclass(arg_type, BaseModel):
+        if isinstance(arg_type, type) and is_basemodel_subclass(arg_type):
             # Mypy error:
             # "type" has no attribute "schema"
             properties[arg] = arg_type.schema()  # type: ignore[attr-defined]
@@ -156,7 +157,7 @@ def convert_to_ernie_function(
     """
     if isinstance(function, dict):
         return function
-    elif isinstance(function, type) and issubclass(function, BaseModel):
+    elif isinstance(function, type) and is_basemodel_subclass(function):
         return cast(Dict, convert_pydantic_to_ernie_function(function))
     elif callable(function):
         return convert_python_function_to_ernie_function(function)
@@ -185,7 +186,7 @@ def get_ernie_output_parser(
             only the function arguments and not the function name.
     """
     function_names = [convert_to_ernie_function(f)["name"] for f in functions]
-    if isinstance(functions[0], type) and issubclass(functions[0], BaseModel):
+    if isinstance(functions[0], type) and is_basemodel_subclass(functions[0]):
         if len(functions) > 1:
             pydantic_schema: Union[Dict, Type[BaseModel]] = {
                 name: fn for name, fn in zip(function_names, functions)