update

libs/community/langchain_community/adapters/openai.py

@@ -25,7 +25,7 @@ from langchain_core.messages import (
     SystemMessage,
     ToolMessage,
 )
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 from typing_extensions import Literal
 
 

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

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, List, Literal, Optional
 
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, root_validator
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.ainetwork.app import AINAppOps
@@ -53,13 +53,7 @@ class AINetworkToolkit(BaseToolkit):
             values["interface"] = authenticate(network=values.get("network", "testnet"))
         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
+    model_config = ConfigDict(validate_default=True, arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -3,8 +3,8 @@ from __future__ import annotations
 from typing import TYPE_CHECKING, List, Optional
 
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.amadeus.closest_airport import AmadeusClosestAirport
@@ -25,12 +25,7 @@ class AmadeusToolkit(BaseToolkit):
 
     client: Client = Field(default_factory=authenticate)
     llm: Optional[BaseLanguageModel] = Field(default=None)
-
-    class Config:
-        """Pydantic config."""
-
-        # Allow extra fields. This is needed for the `client` field.
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -2,7 +2,7 @@
 
 from typing import List
 
-from langchain_core.pydantic_v1 import Field
+from pydantic import ConfigDict, Field
 
 from langchain_community.agent_toolkits.base import BaseToolkit
 from langchain_community.tools import BaseTool
@@ -23,12 +23,7 @@ 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
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -1,7 +1,7 @@
 from typing import List
 
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.tools import BaseTool, BaseToolkit
+from pydantic import root_validator
 
 from langchain_community.tools.connery import ConneryService
 

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

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 from typing import Dict, List, Optional, Type
 
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.tools import BaseToolkit
+from pydantic import root_validator
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.file_management.copy import CopyFileTool

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

@@ -2,8 +2,8 @@
 
 from typing import Dict, List
 
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.tools import BaseToolkit
+from pydantic import BaseModel, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.github.prompt import (

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

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, List
 
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.gmail.create_draft import GmailCreateDraft
@@ -44,11 +44,7 @@ class GmailToolkit(BaseToolkit):
     """
 
     api_resource: Resource = Field(default_factory=build_resource_service)
-
-    class Config:
-        """Pydantic config."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -5,6 +5,7 @@ from __future__ import annotations
 from typing import List
 
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.multion.close_session import MultionCloseSession
@@ -25,10 +26,7 @@ class MultionToolkit(BaseToolkit):
         See https://python.langchain.com/docs/security for more information.
     """
 
-    class Config:
-        """Pydantic config."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -3,8 +3,8 @@ from __future__ import annotations
 from typing import Any, List, Optional, Sequence
 
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseTool, BaseToolkit
+from pydantic import Field
 
 from langchain_community.agent_toolkits.nla.tool import NLATool
 from langchain_community.tools.openapi.utils.openapi_utils import OpenAPISpec

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

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, List
 
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.office365.create_draft_message import (
@@ -39,11 +39,7 @@ class O365Toolkit(BaseToolkit):
     """
 
     account: Account = Field(default_factory=authenticate)
-
-    class Config:
-        """Pydantic config."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

libs/community/langchain_community/agent_toolkits/openapi/planner.py

@@ -9,8 +9,8 @@ import yaml
 from langchain_core.callbacks import BaseCallbackManager
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate, PromptTemplate
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseTool, Tool
+from pydantic import Field
 
 from langchain_community.agent_toolkits.openapi.planner_prompt import (
     API_CONTROLLER_PROMPT,
@@ -69,6 +69,7 @@ class RequestsGetToolWithParsing(BaseRequestsTool, BaseTool):
 
     name: str = "requests_get"
     """Tool name."""
+    # TODO[pydantic]: add type annotation
     description = REQUESTS_GET_TOOL_DESCRIPTION
     """Tool description."""
     response_length: int = MAX_RESPONSE_LENGTH
@@ -103,6 +104,7 @@ class RequestsPostToolWithParsing(BaseRequestsTool, BaseTool):
 
     name: str = "requests_post"
     """Tool name."""
+    # TODO[pydantic]: add type annotation
     description = REQUESTS_POST_TOOL_DESCRIPTION
     """Tool description."""
     response_length: int = MAX_RESPONSE_LENGTH
@@ -134,6 +136,7 @@ class RequestsPatchToolWithParsing(BaseRequestsTool, BaseTool):
 
     name: str = "requests_patch"
     """Tool name."""
+    # TODO[pydantic]: add type annotation
     description = REQUESTS_PATCH_TOOL_DESCRIPTION
     """Tool description."""
     response_length: int = MAX_RESPONSE_LENGTH
@@ -167,6 +170,7 @@ class RequestsPutToolWithParsing(BaseRequestsTool, BaseTool):
 
     name: str = "requests_put"
     """Tool name."""
+    # TODO[pydantic]: add type annotation
     description = REQUESTS_PUT_TOOL_DESCRIPTION
     """Tool description."""
     response_length: int = MAX_RESPONSE_LENGTH
@@ -198,6 +202,7 @@ class RequestsDeleteToolWithParsing(BaseRequestsTool, BaseTool):
 
     name: str = "requests_delete"
     """The name of the tool."""
+    # TODO[pydantic]: add type annotation
     description = REQUESTS_DELETE_TOOL_DESCRIPTION
     """The description of the tool."""
 

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

@@ -4,8 +4,8 @@ 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.tools import BaseTool, BaseToolkit
+from pydantic import ConfigDict, root_validator
 
 from langchain_community.tools.playwright.base import (
     BaseBrowserTool,
@@ -67,12 +67,7 @@ class PlayWrightBrowserToolkit(BaseToolkit):
 
     sync_browser: Optional["SyncBrowser"] = None
     async_browser: Optional["AsyncBrowser"] = None
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @root_validator(pre=True)
     def validate_imports_and_browser_provided(cls, values: dict) -> dict:

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

@@ -13,8 +13,8 @@ from langchain_core.prompts.chat import (
     HumanMessagePromptTemplate,
     SystemMessagePromptTemplate,
 )
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.powerbi.prompt import (
@@ -62,11 +62,7 @@ class PowerBIToolkit(BaseToolkit):
     callback_manager: Optional[BaseCallbackManager] = None
     output_token_limit: Optional[int] = None
     tiktoken_model_name: Optional[str] = None
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -2,8 +2,8 @@ from __future__ import annotations
 
 from typing import TYPE_CHECKING, List
 
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.slack.get_channel import SlackGetChannel
@@ -24,11 +24,7 @@ class SlackToolkit(BaseToolkit):
     """
 
     client: WebClient = Field(default_factory=login)
-
-    class Config:
-        """Pydantic config."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -3,8 +3,8 @@
 from typing import List
 
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.spark_sql.tool import (
@@ -26,11 +26,7 @@ class SparkSQLToolkit(BaseToolkit):
 
     db: SparkSQL = Field(exclude=True)
     llm: BaseLanguageModel = Field(exclude=True)
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

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

@@ -26,11 +26,6 @@ from langchain_community.agent_toolkits.sql.prompt import (
     SQL_FUNCTIONS_SUFFIX,
     SQL_PREFIX,
 )
-from langchain_community.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
-from langchain_community.tools.sql_database.tool import (
-    InfoSQLDatabaseTool,
-    ListSQLDatabaseTool,
-)
 
 if TYPE_CHECKING:
     from langchain.agents.agent import AgentExecutor
@@ -39,6 +34,7 @@ if TYPE_CHECKING:
     from langchain_core.language_models import BaseLanguageModel
     from langchain_core.tools import BaseTool
 
+    from langchain_community.agent_toolkits.sql.toolkit import SQLDatabaseToolkit
     from langchain_community.utilities.sql_database import SQLDatabase
 
 
@@ -115,6 +111,7 @@ def create_sql_agent(
         agent_executor = create_sql_agent(llm, db=db, agent_type="tool-calling", verbose=True)
 
     """  # noqa: E501
+
     from langchain.agents import (
         create_openai_functions_agent,
         create_openai_tools_agent,
@@ -128,6 +125,11 @@ def create_sql_agent(
     )
     from langchain.agents.agent_types import AgentType
 
+    from langchain_community.tools.sql_database.tool import (
+        InfoSQLDatabaseTool,
+        ListSQLDatabaseTool,
+    )
+
     if toolkit is None and db is None:
         raise ValueError(
             "Must provide exactly one of 'toolkit' or 'db'. Received neither."

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

@@ -3,8 +3,8 @@
 from typing import List
 
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import Field
 from langchain_core.tools import BaseToolkit
+from pydantic import ConfigDict, Field
 
 from langchain_community.tools import BaseTool
 from langchain_community.tools.sql_database.tool import (
@@ -32,10 +32,7 @@ class SQLDatabaseToolkit(BaseToolkit):
         """Return string representation of SQL dialect to use."""
         return self.db.dialect
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def get_tools(self) -> List[BaseTool]:
         """Get the tools in the toolkit."""

libs/community/langchain_community/agents/openai_assistant/base.py

@@ -15,10 +15,10 @@ from langchain.agents.openai_assistant.base import OpenAIAssistantRunnable, Outp
 from langchain_core._api import beta
 from langchain_core.callbacks import CallbackManager
 from langchain_core.load import dumpd
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.runnables import RunnableConfig, ensure_config
 from langchain_core.tools import BaseTool
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, Field, root_validator
 
 if TYPE_CHECKING:
     import openai

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

@@ -22,8 +22,8 @@ from langchain_core.output_parsers import (
     BaseOutputParser,
 )
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables import Runnable
+from pydantic import BaseModel
 
 from langchain_community.output_parsers.ernie_functions import (
     JsonOutputFunctionsParser,

libs/community/langchain_community/chains/graph_qa/arangodb.py

@@ -10,7 +10,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     AQL_FIX_PROMPT,

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

@@ -9,7 +9,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks.manager import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     ENTITY_EXTRACTION_PROMPT,

libs/community/langchain_community/chains/graph_qa/cypher.py

@@ -22,8 +22,8 @@ from langchain_core.prompts import (
     HumanMessagePromptTemplate,
     MessagesPlaceholder,
 )
-from langchain_core.pydantic_v1 import Field
 from langchain_core.runnables import Runnable
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.cypher_utils import (
     CypherQueryCorrector,

libs/community/langchain_community/chains/graph_qa/falkordb.py

@@ -10,7 +10,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_GENERATION_PROMPT,

libs/community/langchain_community/chains/graph_qa/gremlin.py

@@ -10,7 +10,7 @@ from langchain_core.callbacks.manager import CallbackManager, CallbackManagerFor
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
 from langchain_core.prompts.prompt import PromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/hugegraph.py

@@ -9,7 +9,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/kuzu.py

@@ -10,7 +10,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/nebulagraph.py

@@ -9,7 +9,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/neptune_cypher.py

@@ -9,7 +9,7 @@ from langchain.chains.prompt_selector import ConditionalPromptSelector
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts.base import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     CYPHER_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/neptune_sparql.py

@@ -12,7 +12,7 @@ from langchain_core.callbacks.manager import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts.base import BasePromptTemplate
 from langchain_core.prompts.prompt import PromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import SPARQL_QA_PROMPT
 from langchain_community.graphs import NeptuneRdfGraph

libs/community/langchain_community/chains/graph_qa/ontotext_graphdb.py

@@ -12,7 +12,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks.manager import CallbackManager, CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts.base import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     GRAPHDB_QA_PROMPT,

libs/community/langchain_community/chains/graph_qa/sparql.py

@@ -11,7 +11,7 @@ from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.prompts.base import BasePromptTemplate
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.chains.graph_qa.prompts import (
     SPARQL_GENERATION_SELECT_PROMPT,

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 pydantic import ConfigDict, Field, root_validator
 
 from langchain_community.utilities.requests import TextRequestsWrapper
 
@@ -37,12 +37,7 @@ class LLMRequestsChain(Chain):
     requests_key: str = "requests_result"  #: :meta private:
     input_key: str = "url"  #: :meta private:
     output_key: str = "output"  #: :meta private:
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @property
     def input_keys(self) -> List[str]:

libs/community/langchain_community/chains/openapi/chain.py

@@ -11,7 +11,7 @@ from langchain.chains.base import Chain
 from langchain.chains.llm import LLMChain
 from langchain_core.callbacks import CallbackManagerForChainRun, Callbacks
 from langchain_core.language_models import BaseLanguageModel
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 from requests import Response
 
 from langchain_community.tools.openapi.utils.api_models import APIOperation
@@ -30,14 +30,14 @@ class OpenAPIEndpointChain(Chain, BaseModel):
     """Chain interacts with an OpenAPI endpoint using natural language."""
 
     api_request_chain: LLMChain
-    api_response_chain: Optional[LLMChain]
+    api_response_chain: Optional[LLMChain] = None
     api_operation: APIOperation
     requests: Requests = Field(exclude=True, default_factory=Requests)
     param_mapping: _ParamMapping = Field(alias="param_mapping")
     return_intermediate_steps: bool = False
     instructions_key: str = "instructions"  #: :meta private:
     output_key: str = "output"  #: :meta private:
-    max_text_length: Optional[int] = Field(ge=0)  #: :meta private:
+    max_text_length: Optional[int] = Field(None, ge=0)  #: :meta private:
 
     @property
     def input_keys(self) -> List[str]:

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

@@ -19,8 +19,8 @@ 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.vectorstores import VectorStoreRetriever
+from pydantic import ConfigDict, Field, validator
 
 from langchain_community.chains.pebblo_retrieval.enforcement_filters import (
     SUPPORTED_VECTORSTORES,
@@ -185,12 +185,9 @@ class PebbloRetrievalQA(Chain):
         else:
             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
+    model_config = ConfigDict(
+        extra="forbid", arbitrary_types_allowed=True, populate_by_name=True
+    )
 
     @property
     def input_keys(self) -> List[str]:

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

@@ -2,7 +2,7 @@
 
 from typing import Any, List, Optional, Union
 
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 
 class AuthContext(BaseModel):
@@ -89,17 +89,17 @@ class Framework(BaseModel):
 
 
 class Model(BaseModel):
-    vendor: Optional[str]
-    name: Optional[str]
+    vendor: Optional[str] = None
+    name: Optional[str] = None
 
 
 class PkgInfo(BaseModel):
-    project_home_page: Optional[str]
-    documentation_url: Optional[str]
-    pypi_url: Optional[str]
-    liscence_type: Optional[str]
-    installed_via: Optional[str]
-    location: Optional[str]
+    project_home_page: Optional[str] = None
+    documentation_url: Optional[str] = None
+    pypi_url: Optional[str] = None
+    liscence_type: Optional[str] = None
+    installed_via: Optional[str] = None
+    location: Optional[str] = None
 
 
 class VectorDB(BaseModel):
@@ -111,14 +111,14 @@ class VectorDB(BaseModel):
 
 class Chains(BaseModel):
     name: str
-    model: Optional[Model]
-    vector_dbs: Optional[List[VectorDB]]
+    model: Optional[Model] = None
+    vector_dbs: Optional[List[VectorDB]] = None
 
 
 class App(BaseModel):
     name: str
     owner: str
-    description: Optional[str]
+    description: Optional[str] = None
     runtime: Runtime
     framework: Framework
     chains: List[Chains]
@@ -126,8 +126,8 @@ class App(BaseModel):
 
 
 class Context(BaseModel):
-    retrieved_from: Optional[str]
-    doc: Optional[str]
+    retrieved_from: Optional[str] = None
+    doc: Optional[str] = None
     vector_db: str
 
 
@@ -138,9 +138,9 @@ class Prompt(BaseModel):
 class Qa(BaseModel):
     name: str
     context: Union[List[Optional[Context]], Optional[Context]]
-    prompt: Optional[Prompt]
-    response: Optional[Prompt]
+    prompt: Optional[Prompt] = None
+    response: Optional[Prompt] = None
     prompt_time: str
     user: str
-    user_identities: Optional[List[str]]
+    user_identities: Optional[List[str]] = None
     classifier_location: str

libs/community/langchain_community/chat_models/anthropic.py

@@ -20,6 +20,7 @@ from langchain_core.messages import (
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
 from langchain_core.prompt_values import PromptValue
+from pydantic import ConfigDict
 
 from langchain_community.llms.anthropic import _AnthropicCommon
 
@@ -91,11 +92,7 @@ class ChatAnthropic(BaseChatModel, _AnthropicCommon):
             model = ChatAnthropic(model="<model_name>", anthropic_api_key="my-api-key")
     """
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(populate_by_name=True, arbitrary_types_allowed=True)
 
     @property
     def lc_secrets(self) -> Dict[str, str]:

libs/community/langchain_community/chat_models/anyscale.py

@@ -9,8 +9,8 @@ from typing import TYPE_CHECKING, Dict, Optional, Set
 
 import requests
 from langchain_core.messages import BaseMessage
-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 pydantic import Field, SecretStr, root_validator
 
 from langchain_community.adapters.openai import convert_message_to_dict
 from langchain_community.chat_models.openai import (

libs/community/langchain_community/chat_models/azure_openai.py

@@ -9,8 +9,8 @@ from typing import Any, Callable, Dict, List, Union
 
 from langchain_core._api.deprecation import deprecated
 from langchain_core.outputs import ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.utils import get_from_dict_or_env, pre_init
+from pydantic import BaseModel, Field
 
 from langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.utils.openai import is_openai_v1

libs/community/langchain_community/chat_models/baichuan.py

@@ -26,12 +26,12 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
 )
+from pydantic import ConfigDict, Field, SecretStr, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -147,11 +147,7 @@ class ChatBaichuan(BaseChatModel):
     Whether to use search enhance, default is False."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Holds any model parameters valid for API call not explicitly specified."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/baidu_qianfan_endpoint.py

@@ -39,11 +39,11 @@ from langchain_core.output_parsers.openai_tools import (
     PydanticToolsParser,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, ConfigDict, Field, SecretStr, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -351,11 +351,7 @@ class QianfanChatEndpoint(BaseChatModel):
 
     endpoint: Optional[str] = None
     """Endpoint of the Qianfan LLM, required if custom model used."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/bedrock.py

@@ -16,7 +16,7 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Extra
+from pydantic import ConfigDict
 
 from langchain_community.chat_models.anthropic import (
     convert_messages_to_prompt_anthropic,
@@ -232,10 +232,7 @@ class BedrockChat(BaseChatModel, BedrockBase):
 
         return attributes
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
+    model_config = ConfigDict(extra="forbid")
 
     def _stream(
         self,

libs/community/langchain_community/chat_models/cohere.py

@@ -19,6 +19,7 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
+from pydantic import ConfigDict
 
 from langchain_community.llms.cohere import BaseCohere
 
@@ -117,11 +118,7 @@ class ChatCohere(BaseChatModel, BaseCohere):
             chat.invoke(messages)
     """
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(populate_by_name=True, arbitrary_types_allowed=True)
 
     @property
     def _llm_type(self) -> str:

libs/community/langchain_community/chat_models/coze.py

@@ -19,11 +19,11 @@ from langchain_core.messages import (
     HumanMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-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 pydantic import ConfigDict, Field, SecretStr, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -110,11 +110,7 @@ class ChatCoze(BaseChatModel):
     true: set to true, partial message deltas will be sent .
     "Streaming response" will provide real-time response of the model to the client, and
     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
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/dappier.py

@@ -13,8 +13,8 @@ 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.utils import convert_to_secret_str, get_from_dict_or_env
+from pydantic import ConfigDict, Field, SecretStr, root_validator
 
 from langchain_community.utilities.requests import Requests
 
@@ -69,11 +69,7 @@ class ChatDappierAI(BaseChatModel):
     dappier_model: str = "dm_01hpsxyfm2fwdt2zet9cg6fdxt"
 
     dappier_api_key: Optional[SecretStr] = Field(None, description="Dappier API Token")
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
+    model_config = ConfigDict(extra="forbid")
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/deepinfra.py

@@ -54,11 +54,11 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 from langchain_core.utils import get_from_dict_or_env
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, Field, root_validator
 
 from langchain_community.utilities.requests import Requests
 

libs/community/langchain_community/chat_models/edenai.py

@@ -47,16 +47,16 @@ 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,
-    Field,
-    SecretStr,
-)
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    SecretStr,
+)
 
 from langchain_community.utilities.requests import Requests
 
@@ -295,11 +295,7 @@ class ChatEdenAI(BaseChatModel):
     edenai_api_url: str = "https://api.edenai.run/v2"
 
     edenai_api_key: Optional[SecretStr] = Field(None, description="EdenAI API Token")
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
+    model_config = ConfigDict(extra="forbid")
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/ernie.py

@@ -13,8 +13,8 @@ from langchain_core.messages import (
     HumanMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_from_dict_or_env
+from pydantic import root_validator
 
 logger = logging.getLogger(__name__)
 

libs/community/langchain_community/chat_models/everlyai.py

@@ -7,8 +7,8 @@ import sys
 from typing import TYPE_CHECKING, Dict, Optional, Set
 
 from langchain_core.messages import BaseMessage
-from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
+from pydantic import Field, root_validator
 
 from langchain_community.adapters.openai import convert_message_to_dict
 from langchain_community.chat_models.openai import (

libs/community/langchain_community/chat_models/fireworks.py

@@ -32,9 +32,9 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str
 from langchain_core.utils.env import get_from_dict_or_env
+from pydantic import Field, SecretStr, root_validator
 
 from langchain_community.adapters.openai import convert_message_to_dict
 

libs/community/langchain_community/chat_models/google_palm.py

@@ -21,8 +21,8 @@ from langchain_core.outputs import (
     ChatGeneration,
     ChatResult,
 )
-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 pydantic import BaseModel, SecretStr
 from tenacity import (
     before_sleep_log,
     retry,
@@ -231,7 +231,7 @@ class ChatGooglePalm(BaseChatModel, BaseModel):
 
     """
 
-    client: Any  #: :meta private:
+    client: Any = None  #: :meta private:
     model_name: str = "models/chat-bison-001"
     """Model name to use."""
     google_api_key: Optional[SecretStr] = None

libs/community/langchain_community/chat_models/gpt_router.py

@@ -30,8 +30,8 @@ from langchain_core.language_models.chat_models import (
 from langchain_core.language_models.llms import create_base_retry_decorator
 from langchain_core.messages import AIMessageChunk, BaseMessage, BaseMessageChunk
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from pydantic import BaseModel, Field, SecretStr, root_validator
 
 from langchain_community.adapters.openai import (
     convert_dict_to_message,
@@ -150,7 +150,7 @@ class GPTRouter(BaseChatModel):
     """
 
     client: Any = Field(default=None, exclude=True)  #: :meta private:
-    models_priority_list: List[GPTRouterModel] = Field(min_items=1)
+    models_priority_list: List[GPTRouterModel] = Field(min_length=1)
     gpt_router_api_base: str = Field(default=None)
     """WriteSonic GPTRouter custom endpoint"""
     gpt_router_api_key: Optional[SecretStr] = None
@@ -167,7 +167,6 @@ class GPTRouter(BaseChatModel):
     """Number of chat completions to generate for each prompt."""
     max_tokens: int = 256
 
-    @root_validator(allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:
         values["gpt_router_api_base"] = get_from_dict_or_env(
             values,

libs/community/langchain_community/chat_models/huggingface.py

@@ -25,7 +25,7 @@ from langchain_core.outputs import (
     ChatResult,
     LLMResult,
 )
-from langchain_core.pydantic_v1 import root_validator
+from pydantic import root_validator
 
 from langchain_community.llms.huggingface_endpoint import HuggingFaceEndpoint
 from langchain_community.llms.huggingface_hub import HuggingFaceHub

libs/community/langchain_community/chat_models/human.py

@@ -15,7 +15,7 @@ from langchain_core.messages import (
     messages_to_dict,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.llms.utils import enforce_stop_tokens
 

libs/community/langchain_community/chat_models/hunyuan.py

@@ -24,13 +24,13 @@ from langchain_core.messages import (
     HumanMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
     pre_init,
 )
+from pydantic import ConfigDict, Field, SecretStr, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -159,11 +159,7 @@ class ChatHunyuan(BaseChatModel):
 
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Holds any model parameters valid for API call not explicitly specified."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/javelin_ai_gateway.py

@@ -18,7 +18,7 @@ from langchain_core.outputs import (
     ChatGeneration,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, SecretStr
+from pydantic import BaseModel, ConfigDict, Extra, Field, SecretStr
 
 logger = logging.getLogger(__name__)
 
@@ -67,11 +67,7 @@ class ChatJavelinAIGateway(BaseChatModel):
 
     javelin_api_key: Optional[SecretStr] = Field(None, alias="api_key")
     """The API key for the Javelin AI Gateway."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     def __init__(self, **kwargs: Any):
         try:

libs/community/langchain_community/chat_models/jinachat.py

@@ -40,13 +40,13 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
     pre_init,
 )
+from pydantic import ConfigDict, Field, SecretStr, root_validator
 from tenacity import (
     before_sleep_log,
     retry,
@@ -187,11 +187,7 @@ class JinaChat(BaseChatModel):
     """Whether to stream the results or not."""
     max_tokens: Optional[int] = None
     """Maximum number of tokens to generate."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/kinetica.py

@@ -12,6 +12,7 @@ from pathlib import Path
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
 
 from langchain_core.utils import pre_init
+from pydantic import ConfigDict
 
 if TYPE_CHECKING:
     import gpudb
@@ -26,7 +27,7 @@ from langchain_core.messages import (
 )
 from langchain_core.output_parsers.transform import BaseOutputParser
 from langchain_core.outputs import ChatGeneration, ChatResult, Generation
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, Field
 
 LOG = logging.getLogger(__name__)
 
@@ -78,7 +79,7 @@ class _KdtSuggestContext(BaseModel):
 class _KdtSuggestPayload(BaseModel):
     """pydantic API request type"""
 
-    question: Optional[str]
+    question: Optional[str] = None
     context: List[_KdtSuggestContext]
 
     def get_system_str(self) -> str:
@@ -542,11 +543,7 @@ class KineticaSqlResponse(BaseModel):
     # dataframe: "pd.DataFrame" = Field(default=None)
     dataframe: Any = Field(default=None)
     """The Pandas dataframe containing the fetched data."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
 
 class KineticaSqlOutputParser(BaseOutputParser[KineticaSqlResponse]):
@@ -583,11 +580,7 @@ class KineticaSqlOutputParser(BaseOutputParser[KineticaSqlResponse]):
 
     kdbc: Any = Field(exclude=True)
     """ Kinetica DB connection. """
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def parse(self, text: str) -> KineticaSqlResponse:
         df = self.kdbc.to_df(text)

libs/community/langchain_community/chat_models/konko.py

@@ -23,8 +23,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.messages import AIMessageChunk, BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
+from pydantic import Field, SecretStr
 
 from langchain_community.adapters.openai import (
     convert_message_to_dict,

libs/community/langchain_community/chat_models/litellm.py

@@ -48,11 +48,11 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
 from langchain_core.utils import get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, Field
 
 logger = logging.getLogger(__name__)
 

libs/community/langchain_community/chat_models/llama_edge.py

@@ -21,8 +21,8 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_pydantic_field_names
+from pydantic import ConfigDict, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -83,11 +83,7 @@ class LlamaEdgeChatService(BaseChatModel):
     """model name, default is `NA`."""
     streaming: bool = False
     """Whether to stream the results or not."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/llamacpp.py

@@ -46,10 +46,10 @@ from langchain_core.output_parsers.openai_tools import (
     parse_tool_call,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, Field, root_validator
 
 
 class ChatLlamaCpp(BaseChatModel):

libs/community/langchain_community/chat_models/maritalk.py

@@ -16,7 +16,7 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 from requests import Response
 from requests.exceptions import HTTPError
 

libs/community/langchain_community/chat_models/minimax.py

@@ -25,8 +25,8 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from pydantic import BaseModel, ConfigDict, Field, SecretStr, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -285,11 +285,7 @@ class MiniMaxChat(BaseChatModel):
     """Minimax API Key"""
     streaming: bool = False
     """Whether to stream the results or not."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True, allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/mlflow.py

@@ -19,11 +19,11 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import (
+from langchain_core.runnables import RunnableConfig
+from pydantic import (
     Field,
     PrivateAttr,
 )
-from langchain_core.runnables import RunnableConfig
 
 logger = logging.getLogger(__name__)
 

libs/community/langchain_community/chat_models/mlflow_ai_gateway.py

@@ -18,7 +18,7 @@ from langchain_core.outputs import (
     ChatGeneration,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Extra
+from pydantic import BaseModel, Extra
 
 logger = logging.getLogger(__name__)
 

libs/community/langchain_community/chat_models/oci_generative_ai.py

@@ -16,7 +16,7 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Extra
+from pydantic import ConfigDict
 
 from langchain_community.llms.oci_generative_ai import OCIGenAIBase
 from langchain_community.llms.utils import enforce_stop_tokens
@@ -220,10 +220,7 @@ class ChatOCIGenAI(BaseChatModel, OCIGenAIBase):
 
     """  # noqa: E501
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
+    model_config = ConfigDict(extra="forbid")
 
     @property
     def _llm_type(self) -> str:

libs/community/langchain_community/chat_models/octoai.py

@@ -2,8 +2,8 @@
 
 from typing import Dict
 
-from langchain_core.pydantic_v1 import Field, SecretStr
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
+from pydantic import Field, SecretStr
 
 from langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.utils.openai import is_openai_v1

libs/community/langchain_community/chat_models/openai.py

@@ -44,13 +44,13 @@ from langchain_core.messages import (
     ToolMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.runnables import Runnable
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
     pre_init,
 )
+from pydantic import BaseModel, ConfigDict, Field, root_validator
 
 from langchain_community.adapters.openai import (
     convert_dict_to_message,
@@ -243,11 +243,7 @@ class ChatOpenAI(BaseChatModel):
     # [httpx documentation](https://www.python-httpx.org/api/#client) for more details.
     http_client: Union[Any, None] = None
     """Optional httpx.Client."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/pai_eas_endpoint.py

@@ -17,8 +17,8 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import get_from_dict_or_env
+from pydantic import root_validator
 
 from langchain_community.llms.utils import enforce_stop_tokens
 

libs/community/langchain_community/chat_models/perplexity.py

@@ -35,8 +35,8 @@ from langchain_core.messages import (
     ToolMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from pydantic import ConfigDict, Field, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -80,11 +80,7 @@ class ChatPerplexity(BaseChatModel):
     """Whether to stream the results or not."""
     max_tokens: Optional[int] = None
     """Maximum number of tokens to generate."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @property
     def lc_secrets(self) -> Dict[str, str]:
@@ -116,7 +112,6 @@ class ChatPerplexity(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator(allow_reuse=True)
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["pplx_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/chat_models/premai.py

@@ -35,13 +35,13 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import (
+from langchain_core.utils import get_from_dict_or_env, pre_init
+from pydantic import (
     BaseModel,
-    Extra,
+    ConfigDict,
     Field,
     SecretStr,
 )
-from langchain_core.utils import get_from_dict_or_env, pre_init
 
 if TYPE_CHECKING:
     from premai.api.chat_completions.v1_chat_completions_create import (
@@ -239,14 +239,10 @@ class ChatPremAI(BaseChatModel, BaseModel):
     streaming: Optional[bool] = False
     """Whether to stream the responses or not."""
 
-    client: Any
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        allow_population_by_field_name = True
-        arbitrary_types_allowed = True
+    client: Any = None
+    model_config = ConfigDict(
+        extra="forbid", populate_by_name=True, arbitrary_types_allowed=True
+    )
 
     @pre_init
     def validate_environments(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/snowflake.py

@@ -11,7 +11,6 @@ from langchain_core.messages import (
     SystemMessage,
 )
 from langchain_core.outputs import ChatGeneration, ChatResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
@@ -19,6 +18,7 @@ from langchain_core.utils import (
     pre_init,
 )
 from langchain_core.utils.utils import build_extra_kwargs
+from pydantic import Field, SecretStr, root_validator
 
 SUPPORTED_ROLES: List[str] = [
     "system",

libs/community/langchain_community/chat_models/solar.py

@@ -3,8 +3,8 @@
 from typing import Dict
 
 from langchain_core._api import deprecated
-from langchain_core.pydantic_v1 import Field
 from langchain_core.utils import get_from_dict_or_env, pre_init
+from pydantic import ConfigDict, Field
 
 from langchain_community.chat_models import ChatOpenAI
 from langchain_community.llms.solar import SOLAR_SERVICE_URL_BASE, SolarCommon
@@ -28,14 +28,9 @@ class SolarChat(SolarCommon, ChatOpenAI):
     """
 
     max_tokens: int = Field(default=1024)
-
-    # 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"
+    model_config = ConfigDict(
+        populate_by_name=True, arbitrary_types_allowed=True, extra="ignore"
+    )
 
     @pre_init
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/chat_models/sparkllm.py

@@ -35,11 +35,11 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import Field, root_validator
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
 )
+from pydantic import ConfigDict, Field, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -162,11 +162,7 @@ class ChatSparkLLM(BaseChatModel):
     """What search sampling control to use."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """Holds any model parameters valid for API call not explicitly specified."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/chat_models/tongyi.py

@@ -53,11 +53,11 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
+from pydantic import BaseModel, ConfigDict, Field, SecretStr
 from requests.exceptions import HTTPError
 from tenacity import (
     before_sleep_log,
@@ -451,11 +451,7 @@ class ChatTongyi(BaseChatModel):
 
     max_retries: int = 10
     """Maximum number of retries to make when generating."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @property
     def _llm_type(self) -> str:

libs/community/langchain_community/chat_models/yuan2.py

@@ -40,12 +40,12 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
     pre_init,
 )
+from pydantic import BaseModel, ConfigDict, Field, root_validator
 from tenacity import (
     before_sleep_log,
     retry,
@@ -119,11 +119,7 @@ class ChatYuan2(BaseChatModel):
 
     repeat_penalty: Optional[float] = 1.18
     """The penalty to apply to repeated tokens."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @property
     def lc_secrets(self) -> Dict[str, str]:

libs/community/langchain_community/chat_models/zhipuai.py

@@ -31,8 +31,8 @@ from langchain_core.messages import (
     SystemMessageChunk,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
 from langchain_core.utils import get_from_dict_or_env
+from pydantic import BaseModel, ConfigDict, Field, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -371,11 +371,7 @@ class ChatZhipuAI(BaseChatModel):
     """Whether to stream the results or not."""
     max_tokens: Optional[int] = None
     """Maximum number of tokens to generate."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        allow_population_by_field_name = True
+    model_config = ConfigDict(populate_by_name=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict[str, Any]) -> Dict[str, Any]:

libs/community/langchain_community/cross_encoders/fake.py

@@ -1,7 +1,7 @@
 from difflib import SequenceMatcher
 from typing import List, Tuple
 
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 from langchain_community.cross_encoders.base import BaseCrossEncoder
 

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 pydantic import BaseModel, ConfigDict, Field
 
 from langchain_community.cross_encoders.base import BaseCrossEncoder
 
@@ -23,7 +23,7 @@ class HuggingFaceCrossEncoder(BaseModel, BaseCrossEncoder):
             )
     """
 
-    client: Any  #: :meta private:
+    client: Any = None  #: :meta private:
     model_name: str = DEFAULT_MODEL_NAME
     """Model name to use."""
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
@@ -45,10 +45,7 @@ class HuggingFaceCrossEncoder(BaseModel, BaseCrossEncoder):
             self.model_name, **self.model_kwargs
         )
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
+    model_config = ConfigDict(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 pydantic import BaseModel, ConfigDict, root_validator
 
 from langchain_community.cross_encoders.base import BaseCrossEncoder
 
@@ -61,7 +61,7 @@ class SagemakerEndpointCrossEncoder(BaseModel, BaseCrossEncoder):
                credentials_profile_name=credentials_profile_name
            )
    """
-    client: Any  #: :meta private:
+    client: Any = None  #: :meta private:
 
     endpoint_name: str = ""
     """The name of the endpoint from the deployed Sagemaker model.
@@ -88,12 +88,7 @@ class SagemakerEndpointCrossEncoder(BaseModel, BaseCrossEncoder):
    function. See `boto3`_. docs for more info.
    .. _boto3: <https://boto3.amazonaws.com/v1/documentation/api/latest/index.html>
    """
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/dashscope_rerank.py

@@ -5,8 +5,8 @@ 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.utils import get_from_dict_or_env
+from pydantic import ConfigDict, Field, root_validator
 
 
 class DashScopeRerank(BaseDocumentCompressor):
@@ -24,13 +24,9 @@ class DashScopeRerank(BaseDocumentCompressor):
     dashscope_api_key: Optional[str] = Field(None, alias="api_key")
     """DashScope API key. Must be specified directly or via environment variable 
         DASHSCOPE_API_KEY."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
-        allow_population_by_field_name = True
+    model_config = ConfigDict(
+        extra="forbid", arbitrary_types_allowed=True, populate_by_name=True
+    )
 
     @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 pydantic import ConfigDict, root_validator
 
 if TYPE_CHECKING:
     from flashrank import Ranker, RerankRequest
@@ -28,12 +28,7 @@ class FlashrankRerank(BaseDocumentCompressor):
     """Number of documents to return."""
     model: Optional[str] = None
     """Model to use for reranking."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/jina_rerank.py

@@ -6,8 +6,8 @@ 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.utils import get_from_dict_or_env
+from pydantic import ConfigDict, root_validator
 
 JINA_API_URL: str = "https://api.jina.ai/v1/rerank"
 
@@ -26,12 +26,7 @@ class JinaRerank(BaseDocumentCompressor):
         JINA_API_KEY."""
     user_agent: str = "langchain"
     """Identifier for the application making the request."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/llmlingua_filter.py

@@ -8,7 +8,7 @@ from langchain_core.documents import Document
 from langchain_core.documents.compressor import (
     BaseDocumentCompressor,
 )
-from langchain_core.pydantic_v1 import root_validator
+from pydantic import ConfigDict, root_validator
 
 DEFAULT_LLM_LINGUA_INSTRUCTION = (
     "Given this documents, please answer the final question"
@@ -71,11 +71,7 @@ class LLMLinguaCompressor(BaseDocumentCompressor):
             )
         return values
 
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = "forbid"
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @staticmethod
     def _format_context(docs: Sequence[Document]) -> List[str]:

libs/community/langchain_community/document_compressors/openvino_rerank.py

@@ -5,7 +5,7 @@ import numpy as np
 from langchain_core.callbacks import Callbacks
 from langchain_core.documents import Document
 from langchain_core.documents.compressor import BaseDocumentCompressor
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 
 class RerankRequest:

libs/community/langchain_community/document_compressors/rankllm_rerank.py

@@ -7,8 +7,8 @@ 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.utils import get_from_dict_or_env
+from pydantic import ConfigDict, Field, PrivateAttr, root_validator
 
 if TYPE_CHECKING:
     from rank_llm.data import Candidate, Query, Request
@@ -35,12 +35,7 @@ class RankLLMRerank(BaseDocumentCompressor):
     gpt_model: str = Field(default="gpt-3.5-turbo")
     """OpenAI model name."""
     _retriever: Any = PrivateAttr()
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        extra = Extra.forbid
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(extra="forbid", arbitrary_types_allowed=True)
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_compressors/volcengine_rerank.py

@@ -5,8 +5,8 @@ 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.utils import get_from_dict_or_env
+from pydantic import ConfigDict, root_validator
 
 
 class VolcengineRerank(BaseDocumentCompressor):
@@ -31,13 +31,9 @@ class VolcengineRerank(BaseDocumentCompressor):
 
     top_n: Optional[int] = 3
     """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
+    model_config = ConfigDict(
+        extra="forbid", arbitrary_types_allowed=True, populate_by_name=True
+    )
 
     @root_validator(pre=True)
     def validate_environment(cls, values: Dict) -> Dict:

libs/community/langchain_community/document_loaders/apify_dataset.py

@@ -1,7 +1,7 @@
 from typing import Any, Callable, Dict, List
 
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from pydantic import BaseModel, root_validator
 
 from langchain_community.document_loaders.base import BaseLoader
 
@@ -26,7 +26,7 @@ class ApifyDatasetLoader(BaseLoader, BaseModel):
             documents = loader.load()
     """  # noqa: E501
 
-    apify_client: Any
+    apify_client: Any = None
     """An instance of the ApifyClient class from the apify-client Python package."""
     dataset_id: str
     """The ID of the dataset on the Apify platform."""

libs/community/langchain_community/document_loaders/base_o365.py

@@ -10,13 +10,8 @@ from enum import Enum
 from pathlib import Path, PurePath
 from typing import TYPE_CHECKING, Any, Dict, Iterable, List, Sequence, Union
 
-from langchain_core.pydantic_v1 import (
-    BaseModel,
-    BaseSettings,
-    Field,
-    FilePath,
-    SecretStr,
-)
+from pydantic import BaseModel, Field, FilePath, SecretStr
+from pydantic_settings import BaseSettings, SettingsConfigDict
 
 from langchain_community.document_loaders.base import BaseLoader
 from langchain_community.document_loaders.blob_loaders.file_system import (
@@ -34,13 +29,11 @@ CHUNK_SIZE = 1024 * 1024 * 5
 
 
 class _O365Settings(BaseSettings):
-    client_id: str = Field(..., env="O365_CLIENT_ID")
-    client_secret: SecretStr = Field(..., env="O365_CLIENT_SECRET")
-
-    class Config:
-        env_prefix = ""
-        case_sentive = False
-        env_file = ".env"
+    client_id: str = Field(..., validation_alias="O365_CLIENT_ID")
+    client_secret: SecretStr = Field(..., validation_alias="O365_CLIENT_SECRET")
+    model_config = SettingsConfigDict(
+        env_prefix="", case_sentive=False, env_file=".env"
+    )
 
 
 class _O365TokenStorage(BaseSettings):

libs/community/langchain_community/document_loaders/docugami.py

@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Mapping, Optional, Sequence, Union
 import requests
 from langchain_core._api.deprecation import deprecated
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from pydantic import BaseModel, root_validator
 
 from langchain_community.document_loaders.base import BaseLoader
 
@@ -44,13 +44,13 @@ class DocugamiLoader(BaseLoader, BaseModel):
     access_token: Optional[str] = os.environ.get("DOCUGAMI_API_KEY")
     """The Docugami API access token to use."""
 
-    max_text_length = 4096
+    max_text_length: int = 4096
     """Max length of chunk text returned."""
 
     min_text_length: int = 32
     """Threshold under which chunks are appended to next to avoid over-chunking."""
 
-    max_metadata_length = 512
+    max_metadata_length: int = 512
     """Max length of metadata text returned."""
 
     include_xml_tags: bool = False
@@ -69,13 +69,13 @@ class DocugamiLoader(BaseLoader, BaseModel):
     """Set to False if you want to full whitespace formatting in the original
     XML doc, including indentation."""
 
-    docset_id: Optional[str]
+    docset_id: Optional[str] = None
     """The Docugami API docset ID to use."""
 
-    document_ids: Optional[Sequence[str]]
+    document_ids: Optional[Sequence[str]] = None
     """The Docugami API document IDs to use."""
 
-    file_paths: Optional[Sequence[Union[Path, str]]]
+    file_paths: Optional[Sequence[Union[Path, str]]] = None
     """The local file paths to use."""
 
     include_project_metadata_in_doc_metadata: bool = True

libs/community/langchain_community/document_loaders/dropbox.py

@@ -12,7 +12,7 @@ from pathlib import Path
 from typing import Any, Dict, List, Optional
 
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from pydantic import BaseModel, root_validator
 
 from langchain_community.document_loaders.base import BaseLoader
 

libs/community/langchain_community/document_loaders/github.py

@@ -5,8 +5,8 @@ from typing import Callable, Dict, Iterator, List, Literal, Optional, Union
 
 import requests
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, root_validator, validator
 from langchain_core.utils import get_from_dict_or_env
+from pydantic import BaseModel, root_validator, validator
 
 from langchain_community.document_loaders.base import BaseLoader
 
@@ -181,7 +181,7 @@ class GithubFileLoader(BaseGitHubLoader, ABC):
     file_extension: str = ".md"
     branch: str = "main"
 
-    file_filter: Optional[Callable[[str], bool]]
+    file_filter: Optional[Callable[[str], bool]] = None
 
     def get_file_paths(self) -> List[Dict]:
         base_url = (

libs/community/langchain_community/document_loaders/googledrive.py

@@ -13,7 +13,7 @@ from typing import Any, Dict, List, Optional, Sequence, Union
 
 from langchain_core._api.deprecation import deprecated
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, root_validator, validator
+from pydantic import BaseModel, root_validator, validator
 
 from langchain_community.document_loaders.base import BaseLoader
 

libs/community/langchain_community/document_loaders/onedrive.py

@@ -6,7 +6,7 @@ import logging
 from typing import TYPE_CHECKING, Iterator, List, Optional, Sequence, Union
 
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.document_loaders.base_o365 import (
     O365BaseLoader,

libs/community/langchain_community/document_loaders/onedrive_file.py

@@ -4,7 +4,7 @@ import tempfile
 from typing import TYPE_CHECKING, List
 
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from langchain_community.document_loaders.base import BaseLoader
 from langchain_community.document_loaders.unstructured import UnstructuredFileLoader
@@ -20,11 +20,7 @@ class OneDriveFileLoader(BaseLoader, BaseModel):
 
     file: File = Field(...)
     """The file to load."""
-
-    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"""
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def load(self) -> List[Document]:
         """Load Documents"""

libs/community/langchain_community/document_loaders/onenote.py

@@ -5,33 +5,24 @@ from typing import Dict, Iterator, List, Optional
 
 import requests
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import (
-    BaseModel,
-    BaseSettings,
-    Field,
-    FilePath,
-    SecretStr,
-)
+from pydantic import BaseModel, Field, FilePath, SecretStr
 
 from langchain_community.document_loaders.base import BaseLoader
 
+# from pydantic_settings import BaseSettings, SettingsConfigDict
 
-class _OneNoteGraphSettings(BaseSettings):
-    client_id: str = Field(..., env="MS_GRAPH_CLIENT_ID")
-    client_secret: SecretStr = Field(..., env="MS_GRAPH_CLIENT_SECRET")
-
-    class Config:
-        """Config for OneNoteGraphSettings."""
-
-        env_prefix = ""
-        case_sentive = False
-        env_file = ".env"
+#
+# class _OneNoteGraphSettings(BaseSettings):
+#     client_id: str = Field(..., validation_alias="MS_GRAPH_CLIENT_ID")
+#     client_secret: SecretStr = Field(..., validation_alias="MS_GRAPH_CLIENT_SECRET")
+#     model_config = SettingsConfigDict(env_prefix="", case_sentive=False, env_file=".env")
+#
 
 
 class OneNoteLoader(BaseLoader, BaseModel):
     """Load pages from OneNote notebooks."""
 
-    settings: _OneNoteGraphSettings = Field(default_factory=_OneNoteGraphSettings)  # type: ignore[arg-type]
+    # settings: _OneNoteGraphSettings = Field(default_factory=_OneNoteGraphSettings)  # type: ignore[arg-type]
     """Settings for the Microsoft Graph API client."""
     auth_with_token: bool = False
     """Whether to authenticate with a token or not. Defaults to False."""
@@ -39,7 +30,7 @@ class OneNoteLoader(BaseLoader, BaseModel):
     """Personal access token"""
     onenote_api_base_url: str = "https://graph.microsoft.com/v1.0/me/onenote"
     """URL of Microsoft Graph API for OneNote"""
-    authority_url = "https://login.microsoftonline.com/consumers/"
+    authority_url: str = "https://login.microsoftonline.com/consumers/"
     """A URL that identifies a token authority"""
     token_path: FilePath = Path.home() / ".credentials" / "onenote_graph_token.txt"
     """Path to the file where the access token is stored"""

libs/community/langchain_community/document_loaders/sharepoint.py

@@ -9,7 +9,7 @@ from typing import Any, Iterator, List, Optional, Sequence
 import requests  # type: ignore
 from langchain_core.document_loaders import BaseLoader
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import Field
+from pydantic import Field
 
 from langchain_community.document_loaders.base_o365 import (
     O365BaseLoader,

libs/community/langchain_community/document_loaders/youtube.py

@@ -9,8 +9,8 @@ from typing import Any, Dict, Generator, List, Optional, Sequence, Union
 from urllib.parse import parse_qs, urlparse
 
 from langchain_core.documents import Document
-from langchain_core.pydantic_v1 import root_validator
-from langchain_core.pydantic_v1.dataclasses import dataclass
+from pydantic import root_validator
+from pydantic.dataclasses import dataclass
 
 from langchain_community.document_loaders.base import BaseLoader
 

libs/community/langchain_community/document_transformers/embeddings_redundant_filter.py

@@ -5,7 +5,7 @@ from typing import Any, Callable, List, Sequence
 import numpy as np
 from langchain_core.documents import BaseDocumentTransformer, Document
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Field
+from pydantic import BaseModel, ConfigDict, Field
 
 from langchain_community.utils.math import cosine_similarity
 
@@ -152,11 +152,7 @@ class EmbeddingsRedundantFilter(BaseDocumentTransformer, BaseModel):
     similarity_threshold: float = 0.95
     """Threshold for determining when two documents are similar enough
     to be considered redundant."""
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def transform_documents(
         self, documents: Sequence[Document], **kwargs: Any
@@ -202,11 +198,7 @@ class EmbeddingsClusteringFilter(BaseDocumentTransformer, BaseModel):
     This could dramatically reduce results when there is a lot of overlap between 
     clusters.
     """
-
-    class Config:
-        """Configuration for this pydantic object."""
-
-        arbitrary_types_allowed = True
+    model_config = ConfigDict(arbitrary_types_allowed=True)
 
     def transform_documents(
         self, documents: Sequence[Document], **kwargs: Any