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/chat_models/edenai.py

@@ -57,6 +57,7 @@ from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from langchain_core.utils.pydantic import is_basemodel_subclass
 
 from langchain_community.utilities.requests import Requests
 
@@ -443,7 +444,7 @@ class ChatEdenAI(BaseChatModel):
         if kwargs:
             raise ValueError(f"Received unsupported arguments {kwargs}")
         llm = self.bind_tools([schema], tool_choice="required")
-        if isinstance(schema, type) and issubclass(schema, BaseModel):
+        if isinstance(schema, type) and is_basemodel_subclass(schema):
             output_parser: OutputParserLike = PydanticToolsParser(
                 tools=[schema], first_tool_only=True
             )