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 @@
  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 @@
  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.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 @@ def validate_environment(cls, values: Dict) -> Dict:
  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 @@
  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 @@ def __new__(cls, **data: Any) -> Union[OpenAIChat, BaseOpenAI]: # type: ignore
  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")

libs/core/langchain_core/utils/__init__.py

@@ -32,6 +32,7 @@
 )
 
 __all__ = [
+ "build_extra_kwargs",
  "StrictFormatter",
  "check_package_version",
  "convert_to_secret_str",
@@ -46,7 +47,6 @@
  "raise_for_status_with_text",
  "xor_args",
  "try_load_from_hub",
- "build_extra_kwargs",
  "image",
  "get_from_env",
  "get_from_dict_or_env",

libs/core/langchain_core/utils/utils.py

@@ -210,6 +210,51 @@ def get_pydantic_field_names(pydantic_cls: Any) -> set[str]:
  return all_required_field_names
 
 
+def _build_model_kwargs(
+ values: dict[str, Any],
+ all_required_field_names: set[str],
+) -> dict[str, Any]:
+ """Build "model_kwargs" param from Pydanitc constructor values.
+
+ Args:
+ values: All init args passed in by user.
+ all_required_field_names: All required field names for the pydantic class.
+
+ Returns:
+ Dict[str, Any]: Extra kwargs.
+
+ Raises:
+ ValueError: If a field is specified in both values and extra_kwargs.
+ ValueError: If a field is specified in model_kwargs.
+ """
+ extra_kwargs = values.get("model_kwargs", {})
+ for field_name in list(values):
+ if field_name in extra_kwargs:
+ raise ValueError(f"Found {field_name} supplied twice.")
+ if field_name not in all_required_field_names:
+ warnings.warn(
+ f"""WARNING! {field_name} is not default parameter.
+ {field_name} was transferred to model_kwargs.
+ Please confirm that {field_name} is what you intended.""",
+ stacklevel=7,
+ )
+ extra_kwargs[field_name] = values.pop(field_name)
+
+ invalid_model_kwargs = all_required_field_names.intersection(extra_kwargs.keys())
+ if invalid_model_kwargs:
+ warnings.warn(
+ f"Parameters {invalid_model_kwargs} should be specified explicitly. "
+ f"Instead they were passed in as part of `model_kwargs` parameter.",
+ stacklevel=7,
+ )
+ for k in invalid_model_kwargs:
+ values[k] = extra_kwargs.pop(k)
+
+ values["model_kwargs"] = extra_kwargs
+ return values
+
+
+# DON'T USE! Kept for backwards-compatibility but should never have been public.
 def build_extra_kwargs(
  extra_kwargs: dict[str, Any],
  values: dict[str, Any],

libs/core/tests/unit_tests/utils/test_imports.py

@@ -17,8 +17,8 @@
  "raise_for_status_with_text",
  "xor_args",
  "try_load_from_hub",
- "build_extra_kwargs",
  "image",
+ "build_extra_kwargs",
  "get_from_dict_or_env",
  "get_from_env",
  "stringify_dict",

libs/partners/anthropic/langchain_anthropic/chat_models.py

@@ -56,13 +56,13 @@
 )
 from langchain_core.tools import BaseTool
 from langchain_core.utils import (
- build_extra_kwargs,
  from_env,
  get_pydantic_field_names,
  secret_from_env,
 )
 from langchain_core.utils.function_calling import convert_to_openai_tool
 from langchain_core.utils.pydantic import is_basemodel_subclass
+from langchain_core.utils.utils import _build_model_kwargs
 from pydantic import (
  BaseModel,
  ConfigDict,
@@ -646,11 +646,8 @@ def _get_ls_params(
  @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
 
  @model_validator(mode="after")

libs/partners/anthropic/langchain_anthropic/llms.py

@@ -25,7 +25,7 @@
  get_pydantic_field_names,
 )
 from langchain_core.utils.utils import (
- build_extra_kwargs,
+ _build_model_kwargs,
  from_env,
  secret_from_env,
 )
@@ -88,11 +88,8 @@ 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
 
  @model_validator(mode="after")

libs/partners/anthropic/tests/unit_tests/test_chat_models.py

@@ -61,9 +61,12 @@ def test_anthropic_model_kwargs() -> None:
 
 
 @pytest.mark.requires("anthropic")
-def test_anthropic_invalid_model_kwargs() -> None:
- with pytest.raises(ValueError):
- ChatAnthropic(model="foo", model_kwargs={"max_tokens_to_sample": 5}) # type: ignore[call-arg]
+def test_anthropic_fields_in_model_kwargs() -> None:
+ """Test that for backwards compatibility fields can be passed in as model_kwargs."""
+ llm = ChatAnthropic(model="foo", model_kwargs={"max_tokens_to_sample": 5}) # type: ignore[call-arg]
+ assert llm.max_tokens == 5
+ llm = ChatAnthropic(model="foo", model_kwargs={"max_tokens": 5}) # type: ignore[call-arg]
+ assert llm.max_tokens == 5
 
 
 @pytest.mark.requires("anthropic")

libs/partners/fireworks/langchain_fireworks/chat_models.py

@@ -79,7 +79,7 @@
  convert_to_openai_tool,
 )
 from langchain_core.utils.pydantic import is_basemodel_subclass
-from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
+from langchain_core.utils.utils import _build_model_kwargs, from_env, secret_from_env
 from pydantic import (
  BaseModel,
  ConfigDict,
@@ -366,10 +366,7 @@ def is_lc_serializable(cls) -> bool:
  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
 
  @model_validator(mode="after")

libs/partners/fireworks/langchain_fireworks/llms.py

@@ -11,7 +11,7 @@
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.utils import get_pydantic_field_names
-from langchain_core.utils.utils import build_extra_kwargs, secret_from_env
+from langchain_core.utils.utils import _build_model_kwargs, secret_from_env
 from pydantic import ConfigDict, Field, SecretStr, model_validator
 
 from langchain_fireworks.version import __version__
@@ -93,10 +93,7 @@ class Fireworks(LLM):
  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
 
  @property

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -90,7 +90,7 @@
  TypeBaseModel,
  is_basemodel_subclass,
 )
-from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
+from langchain_core.utils.utils import _build_model_kwargs, from_env, secret_from_env
 from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
@@ -477,10 +477,7 @@ class BaseChatOpenAI(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
 
  @model_validator(mode="after")

libs/partners/openai/langchain_openai/llms/base.py

@@ -27,7 +27,7 @@
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
 from langchain_core.utils import get_pydantic_field_names
-from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
+from langchain_core.utils.utils import _build_model_kwargs, from_env, secret_from_env
 from pydantic import ConfigDict, Field, SecretStr, model_validator
 from typing_extensions import Self
 
@@ -160,10 +160,7 @@ 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
 
  @model_validator(mode="after")

libs/partners/openai/tests/unit_tests/llms/test_base.py

@@ -30,9 +30,12 @@ def test_openai_model_kwargs() -> None:
  assert llm.model_kwargs == {"foo": "bar"}
 
 
-def test_openai_invalid_model_kwargs() -> None:
- with pytest.raises(ValueError):
- OpenAI(model_kwargs={"model_name": "foo"})
+def test_openai_fields_in_model_kwargs() -> None:
+ """Test that for backwards compatibility fields can be passed in as model_kwargs."""
+ llm = OpenAI(model_kwargs={"model_name": "foo"})
+ assert llm.model_name == "foo"
+ llm = OpenAI(model_kwargs={"model": "foo"})
+ assert llm.model_name == "foo"
 
 
 def test_openai_incorrect_field() -> None: