community[patch]: Upgrade pydantic extra (#25185)

Upgrade to using a literal for specifying the extra which is the
recommended approach in pydantic 2.

This works correctly also in pydantic v1.

```python
from pydantic.v1 import BaseModel

class Foo(BaseModel, extra="forbid"):
    x: int

Foo(x=5, y=1)
```

And 


```python
from pydantic.v1 import BaseModel

class Foo(BaseModel):
    x: int

    class Config:
      extra = "forbid"

Foo(x=5, y=1)
```


## Enum -> literal using grit pattern:

```
engine marzano(0.1)
language python
or {
    `extra=Extra.allow` => `extra="allow"`,
    `extra=Extra.forbid` => `extra="forbid"`,
    `extra=Extra.ignore` => `extra="ignore"`
}
```

Resorted attributes in config and removed doc-string in case we will
need to deal with going back and forth between pydantic v1 and v2 during
the 0.3 release. (This will reduce merge conflicts.)


## Sort attributes in Config:

```
engine marzano(0.1)
language python


function sort($values) js {
    return $values.text.split(',').sort().join("\n");
}


class_definition($name, $body) as $C where {
    $name <: `Config`,
    $body <: block($statements),
    $values = [],
    $statements <: some bubble($values) assignment() as $A where {
        $values += $A
    },
    $body => sort($values),
}

```

libs/community/langchain_community/agent_toolkits/ainetwork/toolkit.py

@@ -54,12 +54,8 @@ class AINetworkToolkit(BaseToolkit):
         return values
 
     class Config:
-        """Pydantic config."""
-
-        # Allow extra fields. This is needed for the `interface` field.
-        validate_all = True
-        # Allow arbitrary types. This is needed for the `interface` field.
         arbitrary_types_allowed = True
+        validate_all = True
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

libs/community/langchain_community/agent_toolkits/amadeus/toolkit.py

@@ -27,9 +27,6 @@ class AmadeusToolkit(BaseToolkit):
     llm: Optional[BaseLanguageModel] = Field(default=None)
 
     class Config:
-        """Pydantic config."""
-
-        # Allow extra fields. This is needed for the `client` field.
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/cassandra_database/toolkit.py

@@ -25,9 +25,6 @@ class CassandraDatabaseToolkit(BaseToolkit):
     db: CassandraDatabase = Field(exclude=True)
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        # Allow arbitrary types. This is needed for the `db` field.
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/financial_datasets/toolkit.py

@@ -32,8 +32,6 @@ class FinancialDatasetsToolkit(BaseToolkit):
         self.api_wrapper = api_wrapper
 
     class Config:
-        """Pydantic config."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/gmail/toolkit.py

@@ -46,8 +46,6 @@ class GmailToolkit(BaseToolkit):
     api_resource: Resource = Field(default_factory=build_resource_service)
 
     class Config:
-        """Pydantic config."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/multion/toolkit.py

@@ -26,8 +26,6 @@ class MultionToolkit(BaseToolkit):
     """
 
     class Config:
-        """Pydantic config."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/office365/toolkit.py

@@ -41,8 +41,6 @@ class O365Toolkit(BaseToolkit):
     account: Account = Field(default_factory=authenticate)
 
     class Config:
-        """Pydantic config."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/playwright/toolkit.py

@@ -4,7 +4,7 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, List, Optional, Type, cast
 
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import root_validator
 from langchain_core.tools import BaseTool, BaseToolkit
 
 from langchain_community.tools.playwright.base import (
@@ -69,10 +69,8 @@ class PlayWrightBrowserToolkit(BaseToolkit):
     async_browser: Optional["AsyncBrowser"] = None
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_imports_and_browser_provided(cls, values: dict) -> dict:

libs/community/langchain_community/agent_toolkits/powerbi/toolkit.py

@@ -64,8 +64,6 @@ class PowerBIToolkit(BaseToolkit):
     tiktoken_model_name: Optional[str] = None
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/slack/toolkit.py

@@ -26,8 +26,6 @@ class SlackToolkit(BaseToolkit):
     client: WebClient = Field(default_factory=login)
 
     class Config:
-        """Pydantic config."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/spark_sql/toolkit.py

@@ -28,8 +28,6 @@ class SparkSQLToolkit(BaseToolkit):
     llm: BaseLanguageModel = Field(exclude=True)
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/agent_toolkits/sql/toolkit.py

@@ -84,8 +84,6 @@ class SQLDatabaseToolkit(BaseToolkit):
         return self.db.dialect
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def get_tools(self) -> List[BaseTool]:

libs/community/langchain_community/chains/llm_requests.py

@@ -7,7 +7,7 @@ from typing import Any, Dict, List, Optional
 from langchain.chains import LLMChain
 from langchain.chains.base import Chain
 from langchain_core.callbacks import CallbackManagerForChainRun
-from langchain_core.pydantic_v1 import Extra, Field, root_validator
+from langchain_core.pydantic_v1 import Field, root_validator
 
 from langchain_community.utilities.requests import TextRequestsWrapper
 
@@ -39,10 +39,8 @@ class LLMRequestsChain(Chain):
     output_key: str = "output"  #: :meta private:
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @property
     def input_keys(self) -> List[str]:

libs/community/langchain_community/chains/pebblo_retrieval/base.py

@@ -19,7 +19,7 @@ from langchain_core.callbacks import (
 )
 from langchain_core.documents import Document
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import Extra, Field, validator
+from langchain_core.pydantic_v1 import Field, validator
 from langchain_core.vectorstores import VectorStoreRetriever
 
 from langchain_community.chains.pebblo_retrieval.enforcement_filters import (
@@ -205,11 +205,9 @@ class PebbloRetrievalQA(Chain):
             return {self.output_key: answer}
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
         allow_population_by_field_name = True
+        arbitrary_types_allowed = True
+        extra = "forbid"
 
     @property
     def input_keys(self) -> List[str]:

libs/community/langchain_community/chat_models/anthropic.py

@@ -92,8 +92,6 @@ class ChatAnthropic(BaseChatModel, _AnthropicCommon):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
 

libs/community/langchain_community/chat_models/baichuan.py

@@ -376,8 +376,6 @@ class ChatBaichuan(BaseChatModel):
     """Holds any model parameters valid for API call not explicitly specified."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py

@@ -380,8 +380,6 @@ class QianfanChatEndpoint(BaseChatModel):
     """Endpoint of the Qianfan LLM, required if custom model used."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/bedrock.py

@@ -16,7 +16,6 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Extra
 
 from langchain_community.chat_models.anthropic import (
     convert_messages_to_prompt_anthropic,
@@ -233,9 +232,7 @@ class BedrockChat(BaseChatModel, BedrockBase):
         return attributes
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def _stream(
         self,

libs/community/langchain_community/chat_models/cohere.py

@@ -118,8 +118,6 @@ class ChatCohere(BaseChatModel, BaseCohere):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
 

libs/community/langchain_community/chat_models/coze.py

@@ -112,8 +112,6 @@ class ChatCoze(BaseChatModel):
     the client needs to assemble the final reply based on the type of message. """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/dappier.py

@@ -13,7 +13,7 @@ from langchain_core.messages import (
     BaseMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 from langchain_community.utilities.requests import Requests
@@ -71,9 +71,7 @@ class ChatDappierAI(BaseChatModel):
     dappier_api_key: Optional[SecretStr] = Field(None, description="Dappier API Token")
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/edenai.py

@@ -49,7 +49,6 @@ from langchain_core.output_parsers.openai_tools import (
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.pydantic_v1 import (
     BaseModel,
-    Extra,
     Field,
     SecretStr,
 )
@@ -298,9 +297,7 @@ class ChatEdenAI(BaseChatModel):
     edenai_api_key: Optional[SecretStr] = Field(None, description="EdenAI API Token")
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/hunyuan.py

@@ -133,8 +133,6 @@ class ChatHunyuan(BaseChatModel):
     """Holds any model parameters valid for API call not explicitly specified."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/javelin_ai_gateway.py

@@ -18,14 +18,14 @@ from langchain_core.outputs import (
     ChatGeneration,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 
 logger = logging.getLogger(__name__)
 
 
 # Ignoring type because below is valid pydantic code
 # Unexpected keyword argument "extra" for "__init_subclass__" of "object"  [call-arg]
-class ChatParams(BaseModel, extra=Extra.allow):
+class ChatParams(BaseModel, extra="allow"):
     """Parameters for the `Javelin AI Gateway` LLM."""
 
     temperature: float = 0.0
@@ -69,8 +69,6 @@ class ChatJavelinAIGateway(BaseChatModel):
     """The API key for the Javelin AI Gateway."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     def __init__(self, **kwargs: Any):

libs/community/langchain_community/chat_models/jinachat.py

@@ -189,8 +189,6 @@ class JinaChat(BaseChatModel):
     """Maximum number of tokens to generate."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/kinetica.py

@@ -544,8 +544,6 @@ class KineticaSqlResponse(BaseModel):
     """The Pandas dataframe containing the fetched data."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
 
@@ -585,8 +583,6 @@ class KineticaSqlOutputParser(BaseOutputParser[KineticaSqlResponse]):
     """ Kinetica DB connection. """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def parse(self, text: str) -> KineticaSqlResponse:

libs/community/langchain_community/chat_models/llama_edge.py

@@ -85,8 +85,6 @@ class LlamaEdgeChatService(BaseChatModel):
     """Whether to stream the results or not."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/minimax.py

@@ -384,8 +384,6 @@ class MiniMaxChat(BaseChatModel):
     """Whether to stream the results or not."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True, allow_reuse=True)

libs/community/langchain_community/chat_models/mlflow_ai_gateway.py

@@ -18,14 +18,14 @@ from langchain_core.outputs import (
     ChatGeneration,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 logger = logging.getLogger(__name__)
 
 
 # Ignoring type because below is valid pydantic code
 # Unexpected keyword argument "extra" for "__init_subclass__" of "object"  [call-arg]
-class ChatParams(BaseModel, extra=Extra.allow):
+class ChatParams(BaseModel, extra="allow"):
     """Parameters for the `MLflow AI Gateway` LLM."""
 
     temperature: float = 0.0

libs/community/langchain_community/chat_models/oci_generative_ai.py

@@ -38,7 +38,7 @@ from langchain_core.output_parsers.openai_tools import (
     PydanticToolsParser,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 from langchain_core.utils.function_calling import convert_to_openai_function
@@ -500,9 +500,7 @@ class ChatOCIGenAI(BaseChatModel, OCIGenAIBase):
     """  # noqa: E501
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @property
     def _llm_type(self) -> str:

libs/community/langchain_community/chat_models/openai.py

@@ -245,8 +245,6 @@ class ChatOpenAI(BaseChatModel):
     """Optional httpx.Client."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/perplexity.py

@@ -82,8 +82,6 @@ class ChatPerplexity(BaseChatModel):
     """Maximum number of tokens to generate."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @property

libs/community/langchain_community/chat_models/premai.py

@@ -40,7 +40,6 @@ from langchain_core.messages import (
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.pydantic_v1 import (
     BaseModel,
-    Extra,
     Field,
     SecretStr,
 )
@@ -299,11 +298,9 @@ class ChatPremAI(BaseChatModel, BaseModel):
     client: Any
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @pre_init
     def validate_environments(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/solar.py

@@ -31,8 +31,6 @@ class SolarChat(SolarCommon, ChatOpenAI):
 
     # this is needed to match ChatOpenAI superclass
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
         extra = "ignore"

libs/community/langchain_community/chat_models/sparkllm.py

@@ -246,8 +246,6 @@ class ChatSparkLLM(BaseChatModel):
     """Holds any model parameters valid for API call not explicitly specified."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/chat_models/tongyi.py

@@ -458,8 +458,6 @@ class ChatTongyi(BaseChatModel):
     """Maximum number of retries to make when generating."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @property

libs/community/langchain_community/chat_models/yuan2.py

@@ -121,8 +121,6 @@ class ChatYuan2(BaseChatModel):
     """The penalty to apply to repeated tokens."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @property

libs/community/langchain_community/chat_models/zhipuai.py

@@ -373,8 +373,6 @@ class ChatZhipuAI(BaseChatModel):
     """Maximum number of tokens to generate."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(pre=True)

libs/community/langchain_community/cross_encoders/huggingface.py

@@ -1,6 +1,6 @@
 from typing import Any, Dict, List, Tuple
 
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field
+from langchain_core.pydantic_v1 import BaseModel, Field
 
 from langchain_community.cross_encoders.base import BaseCrossEncoder
 
@@ -46,9 +46,7 @@ class HuggingFaceCrossEncoder(BaseModel, BaseCrossEncoder):
         )
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def score(self, text_pairs: List[Tuple[str, str]]) -> List[float]:
         """Compute similarity scores using a HuggingFace transformer model.

libs/community/langchain_community/cross_encoders/sagemaker_endpoint.py

@@ -1,7 +1,7 @@
 import json
 from typing import Any, Dict, List, Optional, Tuple
 
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 
 from langchain_community.cross_encoders.base import BaseCrossEncoder
 
@@ -90,10 +90,8 @@ class SagemakerEndpointCrossEncoder(BaseModel, BaseCrossEncoder):
    """
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/dashscope_rerank.py

@@ -5,7 +5,7 @@ from typing import Any, Dict, List, Optional, Sequence, Union
 
 from langchain_core.callbacks.base import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
-from langchain_core.pydantic_v1 import Extra, Field, root_validator
+from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 
@@ -26,11 +26,9 @@ class DashScopeRerank(BaseDocumentCompressor):
         DASHSCOPE_API_KEY."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
         allow_population_by_field_name = True
+        arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/flashrank_rerank.py

@@ -4,7 +4,7 @@ from typing import TYPE_CHECKING, Dict, Optional, Sequence
 
 from langchain_core.callbacks.manager import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import root_validator
 
 if TYPE_CHECKING:
     from flashrank import Ranker, RerankRequest
@@ -34,10 +34,8 @@ class FlashrankRerank(BaseDocumentCompressor):
     """Prefix for flashrank_rerank metadata keys"""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/jina_rerank.py

@@ -6,7 +6,7 @@ from typing import Any, Dict, List, Optional, Sequence, Union
 import requests
 from langchain_core.callbacks import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 JINA_API_URL: str = "https://api.jina.ai/v1/rerank"
@@ -28,10 +28,8 @@ class JinaRerank(BaseDocumentCompressor):
     """Identifier for the application making the request."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/llmlingua_filter.py

@@ -72,10 +72,8 @@ class LLMLinguaCompressor(BaseDocumentCompressor):
         return values
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = "forbid"
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @staticmethod
     def _format_context(docs: Sequence[Document]) -> List[str]:

libs/community/langchain_community/document_compressors/rankllm_rerank.py

@@ -7,7 +7,7 @@ from typing import TYPE_CHECKING, Any, Dict, Optional, Sequence
 from langchain.retrievers.document_compressors.base import BaseDocumentCompressor
 from langchain_core.callbacks.manager import Callbacks
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import Extra, Field, PrivateAttr, root_validator
+from langchain_core.pydantic_v1 import Field, PrivateAttr, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 if TYPE_CHECKING:
@@ -37,10 +37,8 @@ class RankLLMRerank(BaseDocumentCompressor):
     _retriever: Any = PrivateAttr()
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/volcengine_rerank.py

@@ -5,7 +5,7 @@ from typing import Any, Dict, List, Optional, Sequence, Union
 
 from langchain_core.callbacks.base import Callbacks
 from langchain_core.documents import BaseDocumentCompressor, Document
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 
@@ -33,11 +33,9 @@ class VolcengineRerank(BaseDocumentCompressor):
     """Number of documents to return."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
         allow_population_by_field_name = True
+        arbitrary_types_allowed = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_loaders/base_o365.py

@@ -38,9 +38,9 @@ class _O365Settings(BaseSettings):
     client_secret: SecretStr = Field(..., env="O365_CLIENT_SECRET")
 
     class Config:
-        env_prefix = ""
         case_sentive = False
         env_file = ".env"
+        env_prefix = ""
 
 
 class _O365TokenStorage(BaseSettings):

libs/community/langchain_community/document_loaders/onedrive_file.py

@@ -23,8 +23,6 @@ class OneDriveFileLoader(BaseLoader, BaseModel):
 
     class Config:
         arbitrary_types_allowed = True
-        """Allow arbitrary types. This is needed for the File type. Default is True.
-         See https://pydantic-docs.helpmanual.io/usage/types/#arbitrary-types-allowed"""
 
     def load(self) -> List[Document]:
         """Load Documents"""

libs/community/langchain_community/document_loaders/onenote.py

@@ -21,11 +21,9 @@ class _OneNoteGraphSettings(BaseSettings):
     client_secret: SecretStr = Field(..., env="MS_GRAPH_CLIENT_SECRET")
 
     class Config:
-        """Config for OneNoteGraphSettings."""
-
-        env_prefix = ""
         case_sentive = False
         env_file = ".env"
+        env_prefix = ""
 
 
 class OneNoteLoader(BaseLoader, BaseModel):

libs/community/langchain_community/document_transformers/embeddings_redundant_filter.py

@@ -154,8 +154,6 @@ class EmbeddingsRedundantFilter(BaseDocumentTransformer, BaseModel):
     to be considered redundant."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def transform_documents(
@@ -204,8 +202,6 @@ class EmbeddingsClusteringFilter(BaseDocumentTransformer, BaseModel):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def transform_documents(

libs/community/langchain_community/document_transformers/long_context_reorder.py

@@ -30,8 +30,6 @@ class LongContextReorder(BaseDocumentTransformer, BaseModel):
     See: https://arxiv.org/abs//2307.03172"""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         arbitrary_types_allowed = True
 
     def transform_documents(

libs/community/langchain_community/embeddings/baichuan.py

@@ -59,8 +59,6 @@ class BaichuanTextEmbeddings(BaseModel, Embeddings):
     """Chunk size when multiple texts are input"""
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @root_validator(allow_reuse=True)

libs/community/langchain_community/embeddings/bedrock.py

@@ -6,7 +6,7 @@ from typing import Any, Dict, List, Optional
 import numpy as np
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.runnables.config import run_in_executor
 
 
@@ -75,9 +75,7 @@ class BedrockEmbeddings(BaseModel, Embeddings):
     """Whether the embeddings should be normalized to unit vectors"""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=False, skip_on_failure=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/clarifai.py

@@ -2,7 +2,7 @@ import logging
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -44,9 +44,7 @@ class ClarifaiEmbeddings(BaseModel, Embeddings):
     api_base: str = "https://api.clarifai.com"
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/cloudflare_workersai.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 DEFAULT_MODEL_NAME = "@cf/baai/bge-base-en-v1.5"
 
@@ -44,9 +44,7 @@ class CloudflareWorkersAIEmbeddings(BaseModel, Embeddings):
         self.headers = {"Authorization": f"Bearer {self.api_token}"}
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using Cloudflare Workers AI.

libs/community/langchain_community/embeddings/clova.py

@@ -4,7 +4,7 @@ from typing import Dict, List, Optional, cast
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 
@@ -54,7 +54,7 @@ class ClovaEmbeddings(BaseModel, Embeddings):
     """Application ID for identifying your application."""
 
     class Config:
-        extra = Extra.forbid
+        extra = "forbid"
 
     @root_validator(pre=True, allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/cohere.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Optional
 
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 from langchain_community.llms.cohere import _create_retry_decorator
@@ -50,9 +50,7 @@ class CohereEmbeddings(BaseModel, Embeddings):
     """Identifier for the application making the request."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/dashscope.py

@@ -10,7 +10,7 @@ from typing import (
 )
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 from requests.exceptions import HTTPError
 from tenacity import (
@@ -109,9 +109,7 @@ class DashScopeEmbeddings(BaseModel, Embeddings):
     """Maximum number of retries to make when generating."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/deepinfra.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Mapping, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import get_from_dict_or_env, pre_init
 
 DEFAULT_MODEL_ID = "sentence-transformers/clip-ViT-B-32"
@@ -55,9 +55,7 @@ class DeepInfraEmbeddings(BaseModel, Embeddings):
     """Batch size for embedding requests."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/edenai.py

@@ -3,7 +3,6 @@ from typing import Any, Dict, List, Optional
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import (
     BaseModel,
-    Extra,
     Field,
     SecretStr,
 )
@@ -30,9 +29,7 @@ class EdenAiEmbeddings(BaseModel, Embeddings):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/embaas.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Mapping, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from requests.adapters import HTTPAdapter, Retry
 from typing_extensions import NotRequired, TypedDict
@@ -57,9 +57,7 @@ class EmbaasEmbeddings(BaseModel, Embeddings):
     timeout: Optional[int] = 30
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/fastembed.py

@@ -4,7 +4,7 @@ from typing import Any, Dict, List, Literal, Optional
 
 import numpy as np
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import pre_init
 
 MIN_VERSION = "0.2.0"
@@ -67,9 +67,7 @@ class FastEmbedEmbeddings(BaseModel, Embeddings):
     _model: Any  # : :meta private:
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "allow"
-
-        extra = Extra.allow
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/gradient_ai.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 from packaging.version import parse
 
@@ -51,9 +51,7 @@ class GradientEmbeddings(BaseModel, Embeddings):
 
     # LLM call kwargs
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/huggingface.py

@@ -4,7 +4,7 @@ from typing import Any, Dict, List, Optional
 import requests
 from langchain_core._api import deprecated, warn_deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 
 DEFAULT_MODEL_NAME = "sentence-transformers/all-mpnet-base-v2"
 DEFAULT_INSTRUCT_MODEL = "hkunlp/instructor-large"
@@ -81,9 +81,7 @@ class HuggingFaceEmbeddings(BaseModel, Embeddings):
         )
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace transformer model.
@@ -185,9 +183,7 @@ class HuggingFaceInstructEmbeddings(BaseModel, Embeddings):
             self.show_progress = self.encode_kwargs.pop("show_progress_bar")
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace instruct model.
@@ -314,9 +310,7 @@ class HuggingFaceBgeEmbeddings(BaseModel, Embeddings):
             self.show_progress = self.encode_kwargs.pop("show_progress_bar")
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace transformer model.

libs/community/langchain_community/embeddings/huggingface_hub.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Optional
 
 from langchain_core._api import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 DEFAULT_MODEL = "sentence-transformers/all-mpnet-base-v2"
@@ -48,9 +48,7 @@ class HuggingFaceHubEmbeddings(BaseModel, Embeddings):
     huggingfacehub_api_token: Optional[str] = None
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/infinity.py

@@ -8,7 +8,7 @@ import aiohttp
 import numpy as np
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 __all__ = ["InfinityEmbeddings"]
@@ -45,9 +45,7 @@ class InfinityEmbeddings(BaseModel, Embeddings):
 
     # LLM call kwargs
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/infinity_local.py

@@ -5,7 +5,7 @@ from logging import getLogger
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 
 __all__ = ["InfinityEmbeddingsLocal"]
 
@@ -58,9 +58,7 @@ class InfinityEmbeddingsLocal(BaseModel, Embeddings):
 
     # LLM call kwargs
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/ipex_llm.py

@@ -4,7 +4,7 @@
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field
+from langchain_core.pydantic_v1 import BaseModel, Field
 
 DEFAULT_BGE_MODEL = "BAAI/bge-small-en-v1.5"
 DEFAULT_QUERY_BGE_INSTRUCTION_EN = (
@@ -107,9 +107,7 @@ class IpexLLMBgeEmbeddings(BaseModel, Embeddings):
             self.query_instruction = DEFAULT_QUERY_BGE_INSTRUCTION_ZH
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace transformer model.

libs/community/langchain_community/embeddings/itrex.py

@@ -3,7 +3,7 @@ import os
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 
 class QuantizedBgeEmbeddings(BaseModel, Embeddings):
@@ -119,9 +119,7 @@ class QuantizedBgeEmbeddings(BaseModel, Embeddings):
         )
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "allow"
-
-        extra = Extra.allow
 
     def _embed(self, inputs: Any) -> Any:
         import torch

libs/community/langchain_community/embeddings/johnsnowlabs.py

@@ -3,7 +3,7 @@ import sys
 from typing import Any, List
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 
 class JohnSnowLabsEmbeddings(BaseModel, Embeddings):
@@ -59,9 +59,7 @@ class JohnSnowLabsEmbeddings(BaseModel, Embeddings):
             raise Exception("Failure loading model") from exc
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a JohnSnowLabs transformer model.

libs/community/langchain_community/embeddings/laser.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Optional
 
 import numpy as np
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import pre_init
 
 LASER_MULTILINGUAL_MODEL: str = "laser2"
@@ -38,9 +38,7 @@ class LaserEmbeddings(BaseModel, Embeddings):
     _encoder_pipeline: Any  # : :meta private:
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/llamacpp.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 
 
 class LlamaCppEmbeddings(BaseModel, Embeddings):
@@ -58,9 +58,7 @@ class LlamaCppEmbeddings(BaseModel, Embeddings):
     """Print verbose output to stderr."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=False, skip_on_failure=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/llm_rails.py

@@ -4,7 +4,7 @@ from typing import Dict, List, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
@@ -33,9 +33,7 @@ class LLMRailsEmbeddings(BaseModel, Embeddings):
     """LLMRails API key."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/localai.py

@@ -16,7 +16,7 @@ from typing import (
 )
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
@@ -167,9 +167,7 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
     """Holds any model parameters valid for `create` call not explicitly specified."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/embeddings/minimax.py

@@ -5,7 +5,7 @@ from typing import Any, Callable, Dict, List, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
@@ -118,10 +118,8 @@ class MiniMaxEmbeddings(BaseModel, Embeddings):
     """API Key for MiniMax API."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         allow_population_by_field_name = True
+        extra = "forbid"
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/modelscope_hub.py

@@ -1,7 +1,7 @@
 from typing import Any, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 
 class ModelScopeEmbeddings(BaseModel, Embeddings):
@@ -40,9 +40,7 @@ class ModelScopeEmbeddings(BaseModel, Embeddings):
         )
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a modelscope embedding model.

libs/community/langchain_community/embeddings/mosaicml.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Mapping, Optional, Tuple
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 
@@ -42,9 +42,7 @@ class MosaicMLInstructorEmbeddings(BaseModel, Embeddings):
     mosaicml_api_token: Optional[str] = None
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/oci_generative_ai.py

@@ -2,7 +2,7 @@ from enum import Enum
 from typing import Any, Dict, Iterator, List, Mapping, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import pre_init
 
 CUSTOM_ENDPOINT_PREFIX = "ocid1.generativeaiendpoint"
@@ -86,9 +86,7 @@ class OCIGenAIEmbeddings(BaseModel, Embeddings):
      per request"""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:  # pylint: disable=no-self-argument

libs/community/langchain_community/embeddings/ollama.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Mapping, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 logger = logging.getLogger(__name__)
 
@@ -142,9 +142,7 @@ class OllamaEmbeddings(BaseModel, Embeddings):
         return {**{"model": self.model}, **self._default_params}
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def _process_emb_response(self, input: str) -> List[float]:
         """Process a response from the API.

libs/community/langchain_community/embeddings/openai.py

@@ -21,7 +21,7 @@ from typing import (
 import numpy as np
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
@@ -255,10 +255,8 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     """Optional httpx.Client."""
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         allow_population_by_field_name = True
+        extra = "forbid"
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/embeddings/openvino.py

@@ -2,7 +2,7 @@ from pathlib import Path
 from typing import Any, Dict, List
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field
+from langchain_core.pydantic_v1 import BaseModel, Field
 
 DEFAULT_QUERY_INSTRUCTION = (
     "Represent the question for retrieving supporting documents: "
@@ -255,9 +255,7 @@ class OpenVINOEmbeddings(BaseModel, Embeddings):
         return all_embeddings
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace transformer model.

libs/community/langchain_community/embeddings/optimum_intel.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 
 class QuantizedBiEncoderEmbeddings(BaseModel, Embeddings):
@@ -101,9 +101,7 @@ For more information, please visit:
         self.transformer_model.eval()
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "allow"
-
-        extra = Extra.allow
 
     def _embed(self, inputs: Any) -> Any:
         try:

libs/community/langchain_community/embeddings/oracleai.py

@@ -14,7 +14,7 @@ import traceback
 from typing import TYPE_CHECKING, Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 if TYPE_CHECKING:
     from oracledb import Connection
@@ -38,9 +38,7 @@ class OracleEmbeddings(BaseModel, Embeddings):
         super().__init__(**kwargs)
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     """
     1 - user needs to have create procedure, 

libs/community/langchain_community/embeddings/ovhcloud.py

@@ -4,7 +4,7 @@ from typing import Any, List
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 logger = logging.getLogger(__name__)
 
@@ -24,9 +24,7 @@ class OVHCloudEmbeddings(BaseModel, Embeddings):
     region: str = "kepler"
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def __init__(self, **kwargs: Any):
         super().__init__(**kwargs)

libs/community/langchain_community/embeddings/sagemaker_endpoint.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.utils import pre_init
 
 from langchain_community.llms.sagemaker_endpoint import ContentHandlerBase
@@ -111,10 +111,8 @@ class SagemakerEndpointEmbeddings(BaseModel, Embeddings):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
         arbitrary_types_allowed = True
+        extra = "forbid"
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/self_hosted.py

@@ -1,7 +1,6 @@
 from typing import Any, Callable, List
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import Extra
 
 from langchain_community.llms.self_hosted import SelfHostedPipeline
 
@@ -67,9 +66,7 @@ class SelfHostedEmbeddings(SelfHostedPipeline, Embeddings):
     """Any kwargs to pass to the model's inference function."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a HuggingFace transformer model.

libs/community/langchain_community/embeddings/solar.py

@@ -6,7 +6,7 @@ from typing import Any, Callable, Dict, List, Optional
 import requests
 from langchain_core._api import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
@@ -76,9 +76,7 @@ class SolarEmbeddings(BaseModel, Embeddings):
     """API Key for Solar API."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/spacy_embeddings.py

@@ -2,7 +2,7 @@ import importlib.util
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 
 
 class SpacyEmbeddings(BaseModel, Embeddings):
@@ -23,9 +23,7 @@ class SpacyEmbeddings(BaseModel, Embeddings):
     nlp: Optional[Any] = None
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid  # Forbid extra attributes during model initialization
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/sparkllm.py

@@ -116,8 +116,6 @@ class SparkLLMTextEmbeddings(BaseModel, Embeddings):
     If "query", it belongs to query Embedding."""
 
     class Config:
-        """Configuration for this pydantic object"""
-
         allow_population_by_field_name = True
 
     @root_validator(allow_reuse=True)

libs/community/langchain_community/embeddings/tensorflow_hub.py

@@ -1,7 +1,7 @@
 from typing import Any, List
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.pydantic_v1 import BaseModel
 
 DEFAULT_MODEL_URL = "https://tfhub.dev/google/universal-sentence-encoder-multilingual/3"
 
@@ -44,9 +44,7 @@ class TensorflowHubEmbeddings(BaseModel, Embeddings):
         self.embed = tensorflow_hub.load(self.model_url)
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     def embed_documents(self, texts: List[str]) -> List[List[float]]:
         """Compute doc embeddings using a TensorflowHub embedding model.

libs/community/langchain_community/embeddings/textembed.py

@@ -17,7 +17,7 @@ import aiohttp
 import numpy as np
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 __all__ = ["TextEmbedEmbeddings"]
@@ -60,9 +60,7 @@ class TextEmbedEmbeddings(BaseModel, Embeddings):
     """TextEmbed client."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=False, skip_on_failure=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/voyageai.py

@@ -16,7 +16,7 @@ from typing import (
 import requests
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 from tenacity import (
     before_sleep_log,
@@ -100,9 +100,7 @@ class VoyageEmbeddings(BaseModel, Embeddings):
         raised if any given text exceeds the context length."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/embeddings/yandex.py

@@ -72,8 +72,6 @@ class YandexGPTEmbeddings(BaseModel, Embeddings):
     _grpc_metadata: Sequence
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
 
     @pre_init

libs/community/langchain_community/llms/ai21.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Optional, cast
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
@@ -69,9 +69,7 @@ class AI21(LLM):
     """Base url to use, if None decides based on model name."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/llms/aleph_alpha.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Optional, Sequence
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra, SecretStr
+from langchain_core.pydantic_v1 import SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
@@ -163,9 +163,7 @@ class AlephAlpha(LLM):
     by de-prioritizing your request below concurrent ones."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/llms/amazon_api_gateway.py

@@ -3,7 +3,6 @@ from typing import Any, Dict, List, Mapping, Optional
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -45,9 +44,7 @@ class AmazonAPIGateway(LLM):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @property
     def _identifying_params(self) -> Mapping[str, Any]:

libs/community/langchain_community/llms/anthropic.py

@@ -181,8 +181,6 @@ class Anthropic(LLM, _AnthropicCommon):
     """
 
     class Config:
-        """Configuration for this pydantic object."""
-
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
 

libs/community/langchain_community/llms/arcee.py

@@ -2,7 +2,7 @@ from typing import Any, Dict, List, Optional, Union, cast
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra, SecretStr, root_validator
+from langchain_core.pydantic_v1 import SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 
 from langchain_community.utilities.arcee import ArceeWrapper, DALMFilter
@@ -52,9 +52,7 @@ class Arcee(LLM):
     """Keyword arguments to pass to the model."""
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
         underscore_attrs_are_private = True
 
     @property

libs/community/langchain_community/llms/aviary.py

@@ -5,7 +5,7 @@ from typing import Any, Dict, List, Mapping, Optional, Union, cast
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_from_dict_or_env
 
 from langchain_community.llms.utils import enforce_stop_tokens
@@ -123,9 +123,7 @@ class Aviary(LLM):
     version: Optional[str] = None
 
     class Config:
-        """Configuration for this pydantic object."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/llms/bananadev.py

@@ -3,7 +3,7 @@ from typing import Any, Dict, List, Mapping, Optional, cast
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
@@ -41,9 +41,7 @@ class Banana(LLM):
     banana_api_key: Optional[SecretStr] = None
 
     class Config:
-        """Configuration for this pydantic config."""
+        extra = "forbid"
-
-        extra = Extra.forbid
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]: