community[patch]: Fix missing protected_namespaces (#27076)

Fixes #26861

---------

Co-authored-by: Eugene Yurtsev <eyurtsev@gmail.com>

libs/community/langchain_community/llms/azureml_endpoint.py

@@ -9,7 +9,7 @@ from langchain_core.callbacks.manager import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, LLMResult
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
-from pydantic import BaseModel, SecretStr, model_validator, validator
+from pydantic import BaseModel, ConfigDict, SecretStr, model_validator, validator
 
 DEFAULT_TIMEOUT = 50
 
@@ -382,6 +382,8 @@ class AzureMLBaseEndpoint(BaseModel):
     model_kwargs: Optional[dict] = None
     """Keyword arguments to pass to the model."""
 
+    model_config = ConfigDict(protected_namespaces=())
+
     @model_validator(mode="before")
     @classmethod
     def validate_environ(cls, values: Dict) -> Any:

libs/community/langchain_community/llms/bedrock.py

@@ -295,6 +295,8 @@ class LLMInputOutputAdapter:
 class BedrockBase(BaseModel, ABC):
     """Base class for Bedrock models."""
 
+    model_config = ConfigDict(protected_namespaces=())
+
     client: Any = Field(exclude=True)  #: :meta private:
 
     region_name: Optional[str] = None

libs/community/langchain_community/llms/minimax.py

@@ -16,7 +16,7 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
-from pydantic import BaseModel, Field, SecretStr, model_validator
+from pydantic import BaseModel, ConfigDict, Field, SecretStr, model_validator
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -58,6 +58,8 @@ class _MinimaxEndpointClient(BaseModel):
 class MinimaxCommon(BaseModel):
     """Common parameters for Minimax large language models."""
 
+    model_config = ConfigDict(protected_namespaces=())
+
     _client: _MinimaxEndpointClient
     model: str = "abab5.5-chat"
     """Model name to use."""

libs/community/langchain_community/llms/vertexai.py

@@ -11,7 +11,7 @@ from langchain_core.callbacks.manager import (
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
 from langchain_core.utils import pre_init
-from pydantic import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from langchain_community.utilities.vertexai import (
     create_retry_decorator,
@@ -100,6 +100,8 @@ async def acompletion_with_retry(
 
 
 class _VertexAIBase(BaseModel):
+    model_config = ConfigDict(protected_namespaces=())
+
     project: Optional[str] = None
     "The default GCP project to use when making Vertex API calls."
     location: str = "us-central1"

libs/community/langchain_community/llms/volcengine_maas.py

@@ -6,12 +6,14 @@ 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 convert_to_secret_str, get_from_dict_or_env, pre_init
-from pydantic import BaseModel, Field, SecretStr
+from pydantic import BaseModel, ConfigDict, Field, SecretStr
 
 
 class VolcEngineMaasBase(BaseModel):
     """Base class for VolcEngineMaas models."""
 
+    model_config = ConfigDict(protected_namespaces=())
+
     client: Any = None
 
     volc_engine_maas_ak: Optional[SecretStr] = None