core,integrations[minor]: Dont error on fields in model_kwargs (#27110)

Given the current erroring behavior, every time we've moved a kwarg from
model_kwargs and made it its own field that was a breaking change.
Updating this behavior to support the old instantiations /
serializations.

Assuming build_extra_kwargs was not something that itself is being used
externally and needs to be kept backwards compatible

libs/community/langchain_community/chat_models/snowflake.py

@@ -17,7 +17,7 @@ from langchain_core.utils import (
     get_pydantic_field_names,
     pre_init,
 )
-from langchain_core.utils.utils import build_extra_kwargs
+from langchain_core.utils.utils import _build_model_kwargs
 from pydantic import Field, SecretStr, model_validator
 
 SUPPORTED_ROLES: List[str] = [
@@ -131,10 +131,7 @@ class ChatSnowflakeCortex(BaseChatModel):
     def build_extra(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
-        extra = values.get("model_kwargs", {})
-        values["model_kwargs"] = build_extra_kwargs(
-            extra, values, all_required_field_names
-        )
+        values = _build_model_kwargs(values, all_required_field_names)
         return values
 
     @pre_init

libs/community/langchain_community/llms/anthropic.py

@@ -26,7 +26,7 @@ from langchain_core.utils import (
     get_pydantic_field_names,
     pre_init,
 )
-from langchain_core.utils.utils import build_extra_kwargs, convert_to_secret_str
+from langchain_core.utils.utils import _build_model_kwargs, convert_to_secret_str
 from pydantic import ConfigDict, Field, SecretStr, model_validator
 
 
@@ -69,11 +69,8 @@ class _AnthropicCommon(BaseLanguageModel):
     @model_validator(mode="before")
     @classmethod
     def build_extra(cls, values: Dict) -> Any:
-        extra = values.get("model_kwargs", {})
         all_required_field_names = get_pydantic_field_names(cls)
-        values["model_kwargs"] = build_extra_kwargs(
-            extra, values, all_required_field_names
-        )
+        values = _build_model_kwargs(values, all_required_field_names)
         return values
 
     @pre_init

libs/community/langchain_community/llms/llamacpp.py

@@ -8,7 +8,7 @@ from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.utils import get_pydantic_field_names, pre_init
-from langchain_core.utils.utils import build_extra_kwargs
+from langchain_core.utils.utils import _build_model_kwargs
 from pydantic import Field, model_validator
 
 logger = logging.getLogger(__name__)
@@ -199,10 +199,7 @@ class LlamaCpp(LLM):
     def build_model_kwargs(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
-        extra = values.get("model_kwargs", {})
-        values["model_kwargs"] = build_extra_kwargs(
-            extra, values, all_required_field_names
-        )
+        values = _build_model_kwargs(values, all_required_field_names)
         return values
 
     @property

libs/community/langchain_community/llms/openai.py

@@ -34,7 +34,7 @@ from langchain_core.utils import (
     pre_init,
 )
 from langchain_core.utils.pydantic import get_fields
-from langchain_core.utils.utils import build_extra_kwargs
+from langchain_core.utils.utils import _build_model_kwargs
 from pydantic import ConfigDict, Field, model_validator
 
 from langchain_community.utils.openai import is_openai_v1
@@ -268,10 +268,7 @@ class BaseOpenAI(BaseLLM):
     def build_extra(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
-        extra = values.get("model_kwargs", {})
-        values["model_kwargs"] = build_extra_kwargs(
-            extra, values, all_required_field_names
-        )
+        values = _build_model_kwargs(values, all_required_field_names)
         return values
 
     @pre_init

libs/community/tests/unit_tests/chat_models/test_anthropic.py

@@ -33,9 +33,12 @@ def test_anthropic_model_kwargs() -> None:
 
 
 @pytest.mark.requires("anthropic")
-def test_anthropic_invalid_model_kwargs() -> None:
-    with pytest.raises(ValueError):
-        ChatAnthropic(model_kwargs={"max_tokens_to_sample": 5})
+def test_anthropic_fields_in_model_kwargs() -> None:
+    """Test that for backwards compatibility fields can be passed in as model_kwargs."""
+    llm = ChatAnthropic(model_kwargs={"max_tokens_to_sample": 5})
+    assert llm.max_tokens_to_sample == 5
+    llm = ChatAnthropic(model_kwargs={"max_tokens": 5})
+    assert llm.max_tokens_to_sample == 5
 
 
 @pytest.mark.requires("anthropic")

libs/community/tests/unit_tests/llms/test_openai.py

@@ -26,13 +26,12 @@ def test_openai_model_kwargs() -> None:
 
 
 @pytest.mark.requires("openai")
-def test_openai_invalid_model_kwargs() -> None:
-    with pytest.raises(ValueError):
-        OpenAI(model_kwargs={"model_name": "foo"})
-
-    # Test that "model" cannot be specified in kwargs
-    with pytest.raises(ValueError):
-        OpenAI(model_kwargs={"model": "gpt-3.5-turbo-instruct"})
+def test_openai_fields_model_kwargs() -> None:
+    """Test that for backwards compatibility fields can be passed in as model_kwargs."""
+    llm = OpenAI(model_kwargs={"model_name": "foo"}, api_key="foo")
+    assert llm.model_name == "foo"
+    llm = OpenAI(model_kwargs={"model": "foo"}, api_key="foo")
+    assert llm.model_name == "foo"
 
 
 @pytest.mark.requires("openai")