core, standard tests, partner packages: add test for model params (#21677)

1. Adds `.get_ls_params` to BaseChatModel which returns
```python
class LangSmithParams(TypedDict, total=False):
    ls_provider: str
    ls_model_name: str
    ls_model_type: Literal["chat"]
    ls_temperature: Optional[float]
    ls_max_tokens: Optional[int]
    ls_stop: Optional[List[str]]
```
by default it will only return
```python
{ls_model_type="chat", ls_stop=stop}
```

2. Add these params to inheritable metadata in
`CallbackManager.configure`

3. Implement `.get_ls_params` and populate all params for Anthropic +
all subclasses of BaseChatOpenAI

Sample trace:
https://smith.langchain.com/public/d2962673-4c83-47c7-b51e-61d07aaffb1b/r

**OpenAI**:
<img width="984" alt="Screenshot 2024-05-17 at 10 03 35 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/2ef41f74-a9df-4e0e-905d-da74fa82a910">

**Anthropic**:
<img width="978" alt="Screenshot 2024-05-17 at 10 06 07 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/39701c9f-7da5-4f1a-ab14-84e9169d63e7">

**Mistral** (and all others for which params are not yet populated):
<img width="977" alt="Screenshot 2024-05-17 at 10 08 43 AM"
src="https://github.com/langchain-ai/langchain/assets/26529506/37d7d894-fec2-4300-986f-49a5f0191b03">

libs/standard-tests/langchain_standard_tests/unit_tests/chat_models.py

@@ -1,9 +1,9 @@
 from abc import ABC, abstractmethod
-from typing import Type
+from typing import List, Literal, Optional, Type
 
 import pytest
 from langchain_core.language_models import BaseChatModel
-from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_core.pydantic_v1 import BaseModel, Field, ValidationError
 from langchain_core.tools import tool
 
 
@@ -89,3 +89,29 @@ class ChatModelUnitTests(ABC):
         model = chat_model_class(**chat_model_params)
         assert model is not None
         assert model.with_structured_output(Person) is not None
+
+    def test_standard_params(
+        self, chat_model_class: Type[BaseChatModel], chat_model_params: dict
+    ) -> None:
+        class ExpectedParams(BaseModel):
+            ls_provider: str
+            ls_model_name: str
+            ls_model_type: Literal["chat"]
+            ls_temperature: Optional[float]
+            ls_max_tokens: Optional[int]
+            ls_stop: Optional[List[str]]
+
+        model = chat_model_class(**chat_model_params)
+        ls_params = model._get_ls_params()
+        try:
+            ExpectedParams(**ls_params)
+        except ValidationError as e:
+            pytest.fail(f"Validation error: {e}")
+
+        # Test optional params
+        model = chat_model_class(max_tokens=10, stop=["test"], **chat_model_params)
+        ls_params = model._get_ls_params()
+        try:
+            ExpectedParams(**ls_params)
+        except ValidationError as e:
+            pytest.fail(f"Validation error: {e}")