core[minor],community[minor]: Upgrade all @root_validator() to @pre_init (#23841)

This PR introduces a @pre_init decorator that's a @root_validator(pre=True) but with all the defaults populated!

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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -106,7 +106,7 @@ class AzureChatOpenAI(ChatOpenAI):
         """Get the namespace of the langchain object."""
         return ["langchain", "chat_models", "azure_openai"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         if values["n"] < 1:

libs/community/langchain_community/chat_models/edenai.py

@@ -50,11 +50,10 @@ from langchain_core.pydantic_v1 import (
     Extra,
     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 import convert_to_secret_str, get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
 
 from langchain_community.utilities.requests import Requests
@@ -300,7 +299,7 @@ class ChatEdenAI(BaseChatModel):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         values["edenai_api_key"] = convert_to_secret_str(

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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -261,7 +261,7 @@ class ChatGooglePalm(BaseChatModel, BaseModel):
         """Get the namespace of the langchain object."""
         return ["langchain", "chat_models", "google_palm"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key, python package exists, temperature, top_p, and top_k."""
         google_api_key = convert_to_secret_str(

libs/community/langchain_community/chat_models/hunyuan.py

@@ -29,6 +29,7 @@ from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 
 logger = logging.getLogger(__name__)
@@ -190,7 +191,7 @@ class ChatHunyuan(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         values["hunyuan_api_base"] = get_from_dict_or_env(
             values,

libs/community/langchain_community/chat_models/jinachat.py

@@ -45,6 +45,7 @@ from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 from tenacity import (
     before_sleep_log,
@@ -218,7 +219,7 @@ class JinaChat(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["jinachat_api_key"] = convert_to_secret_str(

libs/community/langchain_community/chat_models/kinetica.py

@@ -11,6 +11,8 @@ from importlib.metadata import version
 from pathlib import Path
 from typing import TYPE_CHECKING, Any, Dict, List, Optional, cast
 
+from langchain_core.utils import pre_init
+
 if TYPE_CHECKING:
     import gpudb
 
@@ -24,7 +26,7 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field
 
 LOG = logging.getLogger(__name__)
 
@@ -341,7 +343,7 @@ class ChatKinetica(BaseChatModel):
     kdbc: Any = Field(exclude=True)
     """ Kinetica DB connection. """
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Pydantic object validator."""
 

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, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.adapters.openai import (
     convert_message_to_dict,
@@ -85,7 +85,7 @@ class ChatKonko(ChatOpenAI):
     max_tokens: int = 20
     """Maximum number of tokens to generate."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["konko_api_key"] = convert_to_secret_str(

libs/community/langchain_community/chat_models/litellm.py

@@ -48,10 +48,10 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
+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
+from langchain_core.utils import get_from_dict_or_env, pre_init
 from langchain_core.utils.function_calling import convert_to_openai_tool
 
 logger = logging.getLogger(__name__)
@@ -249,7 +249,7 @@ class ChatLiteLLM(BaseChatModel):
 
         return _completion_with_retry(**kwargs)
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key, python package exists, temperature, top_p, and top_k."""
         try:

libs/community/langchain_community/chat_models/moonshot.py

@@ -2,10 +2,10 @@
 
 from typing import Dict
 
-from langchain_core.pydantic_v1 import root_validator
 from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
+    pre_init,
 )
 
 from langchain_community.chat_models import ChatOpenAI
@@ -29,7 +29,7 @@ class MoonshotChat(MoonshotCommon, ChatOpenAI):  # type: ignore[misc]
             moonshot = MoonshotChat(model="moonshot-v1-8k")
     """
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the environment is set up correctly."""
         values["moonshot_api_key"] = convert_to_secret_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, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -48,7 +48,7 @@ class ChatOctoAI(ChatOpenAI):
     def is_lc_serializable(cls) -> bool:
         return False
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["octoai_api_base"] = get_from_dict_or_env(

libs/community/langchain_community/chat_models/openai.py

@@ -49,6 +49,7 @@ from langchain_core.runnables import Runnable
 from langchain_core.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 
 from langchain_community.adapters.openai import (
@@ -274,7 +275,7 @@ class ChatOpenAI(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         if values["n"] < 1:

libs/community/langchain_community/chat_models/premai.py

@@ -40,9 +40,8 @@ from langchain_core.pydantic_v1 import (
     Extra,
     Field,
     SecretStr,
-    root_validator,
 )
-from langchain_core.utils import get_from_dict_or_env
+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 (
@@ -249,7 +248,7 @@ class ChatPremAI(BaseChatModel, BaseModel):
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
 
-    @root_validator()
+    @pre_init
     def validate_environments(cls, values: Dict) -> Dict:
         """Validate that the package is installed and that the API token is valid"""
         try:

libs/community/langchain_community/chat_models/snowflake.py

@@ -16,6 +16,7 @@ from langchain_core.utils import (
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 from langchain_core.utils.utils import build_extra_kwargs
 
@@ -135,7 +136,7 @@ class ChatSnowflakeCortex(BaseChatModel):
         )
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         try:
             from snowflake.snowpark import Session

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, root_validator
+from langchain_core.pydantic_v1 import Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.chat_models import ChatOpenAI
 from langchain_community.llms.solar import SOLAR_SERVICE_URL_BASE, SolarCommon
@@ -37,7 +37,7 @@ class SolarChat(SolarCommon, ChatOpenAI):
         arbitrary_types_allowed = True
         extra = "ignore"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the environment is set up correctly."""
         values["solar_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/chat_models/tongyi.py

@@ -49,10 +49,10 @@ from langchain_core.outputs import (
     ChatGenerationChunk,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
 from langchain_core.runnables import Runnable
 from langchain_core.tools import BaseTool
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+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 requests.exceptions import HTTPError
 from tenacity import (
@@ -431,7 +431,7 @@ class ChatTongyi(BaseChatModel):
         """Return type of llm."""
         return "tongyi"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["dashscope_api_key"] = convert_to_secret_str(

libs/community/langchain_community/chat_models/vertexai.py

@@ -27,7 +27,7 @@ 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 pre_init
 
 from langchain_community.llms.vertexai import (
     _VertexAICommon,
@@ -225,7 +225,7 @@ class ChatVertexAI(_VertexAICommon, BaseChatModel):
         """Get the namespace of the langchain object."""
         return ["langchain", "chat_models", "vertexai"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the python package exists in environment."""
         is_gemini = is_gemini_model(values["model_name"])

libs/community/langchain_community/chat_models/yuan2.py

@@ -44,6 +44,7 @@ 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 tenacity import (
     before_sleep_log,
@@ -166,7 +167,7 @@ class ChatYuan2(BaseChatModel):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["yuan2_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/embeddings/anyscale.py

@@ -4,8 +4,8 @@ from __future__ import annotations
 
 from typing import Dict
 
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.embeddings.openai import OpenAIEmbeddings
 from langchain_community.utils.openai import is_openai_v1
@@ -34,7 +34,7 @@ class AnyscaleEmbeddings(OpenAIEmbeddings):
             "anyscale_api_key": "ANYSCALE_API_KEY",
         }
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: dict) -> dict:
         """Validate that api key and python package exists in environment."""
         values["anyscale_api_key"] = convert_to_secret_str(

libs/community/langchain_community/embeddings/baidu_qianfan_endpoint.py

@@ -4,8 +4,8 @@ import logging
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -48,7 +48,7 @@ class QianfanEmbeddingsEndpoint(BaseModel, Embeddings):
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
     """extra params for model invoke using with `do`."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """
         Validate whether qianfan_ak and qianfan_sk in the environment variables or

libs/community/langchain_community/embeddings/deepinfra.py

@@ -2,8 +2,8 @@ from typing import Any, Dict, List, Mapping, Optional
 
 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, Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 DEFAULT_MODEL_ID = "sentence-transformers/clip-ViT-B-32"
 MAX_BATCH_SIZE = 1024
@@ -59,7 +59,7 @@ class DeepInfraEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         deepinfra_api_token = get_from_dict_or_env(

libs/community/langchain_community/embeddings/edenai.py

@@ -6,9 +6,8 @@ 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 langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.utilities.requests import Requests
 
@@ -35,7 +34,7 @@ class EdenAiEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         values["edenai_api_key"] = convert_to_secret_str(

libs/community/langchain_community/embeddings/embaas.py

@@ -2,8 +2,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -61,7 +61,7 @@ class EmbaasEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         embaas_api_key = convert_to_secret_str(

libs/community/langchain_community/embeddings/ernie.py

@@ -6,9 +6,9 @@ from typing import Dict, List, Optional
 import requests
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
 from langchain_core.runnables.config import run_in_executor
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -31,7 +31,7 @@ class ErnieEmbeddings(BaseModel, Embeddings):
 
     _lock = threading.Lock()
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         values["ernie_api_base"] = get_from_dict_or_env(
             values, "ernie_api_base", "ERNIE_API_BASE", "https://aip.baidubce.com"

libs/community/langchain_community/embeddings/fastembed.py

@@ -2,7 +2,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.utils import pre_init
 
 
 class FastEmbedEmbeddings(BaseModel, Embeddings):
@@ -54,7 +55,7 @@ class FastEmbedEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that FastEmbed has been installed."""
         model_name = values.get("model_name")

libs/community/langchain_community/embeddings/gigachat.py

@@ -5,7 +5,8 @@ from functools import cached_property
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.utils import pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -77,7 +78,7 @@ class GigaChatEmbeddings(BaseModel, Embeddings):
             key_file_password=self.key_file_password,
         )
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate authenticate data in environment and python package is installed."""
         try:

libs/community/langchain_community/embeddings/google_palm.py

@@ -4,8 +4,8 @@ import logging
 from typing import Any, Callable, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -62,7 +62,7 @@ class GooglePalmEmbeddings(BaseModel, Embeddings):
     show_progress_bar: bool = False
     """Whether to show a tqdm progress bar. Must have `tqdm` installed."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key, python package exists."""
         google_api_key = get_from_dict_or_env(

libs/community/langchain_community/embeddings/laser.py

@@ -2,7 +2,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.utils import pre_init
 
 LASER_MULTILINGUAL_MODEL: str = "laser2"
 
@@ -41,7 +42,7 @@ class LaserEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that laser_encoders has been installed."""
         try:

libs/community/langchain_community/embeddings/llm_rails.py

@@ -4,8 +4,8 @@ from typing import Dict, List, Optional
 
 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, Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
 class LLMRailsEmbeddings(BaseModel, Embeddings):
@@ -37,7 +37,7 @@ class LLMRailsEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         api_key = convert_to_secret_str(

libs/community/langchain_community/embeddings/localai.py

@@ -17,7 +17,11 @@ from typing import (
 
 from langchain_core.embeddings import Embeddings
 from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.utils import (
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+    pre_init,
+)
 from tenacity import (
     AsyncRetrying,
     before_sleep_log,
@@ -193,7 +197,7 @@ class LocalAIEmbeddings(BaseModel, Embeddings):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["openai_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/embeddings/minimax.py

@@ -5,8 +5,8 @@ from typing import Any, Callable, Dict, List, Optional
 
 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, Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -84,7 +84,7 @@ class MiniMaxEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that group id and api key exists in environment."""
         minimax_group_id = get_from_dict_or_env(

libs/community/langchain_community/embeddings/nemo.py

@@ -8,7 +8,8 @@ import aiohttp
 import requests
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
+from langchain_core.utils import pre_init
 
 
 def is_endpoint_live(url: str, headers: Optional[dict], payload: Any) -> bool:
@@ -58,7 +59,7 @@ class NeMoEmbeddings(BaseModel, Embeddings):
     model: str = "NV-Embed-QA-003"
     api_endpoint_url: str = "http://localhost:8088/v1/embeddings"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the end point is alive using the values that are provided."""
 

libs/community/langchain_community/embeddings/nlpcloud.py

@@ -1,8 +1,8 @@
 from typing import Any, Dict, List
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 
 class NLPCloudEmbeddings(BaseModel, Embeddings):
@@ -30,7 +30,7 @@ class NLPCloudEmbeddings(BaseModel, Embeddings):
     ) -> None:
         super().__init__(model_name=model_name, gpu=gpu, **kwargs)
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         nlpcloud_api_key = get_from_dict_or_env(

libs/community/langchain_community/embeddings/oci_generative_ai.py

@@ -2,7 +2,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.utils import pre_init
 
 CUSTOM_ENDPOINT_PREFIX = "ocid1.generativeaiendpoint"
 
@@ -89,7 +90,7 @@ class OCIGenAIEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:  # pylint: disable=no-self-argument
         """Validate that OCI config and python package exists in environment."""
 

libs/community/langchain_community/embeddings/octoai_embeddings.py

@@ -1,7 +1,7 @@
 from typing import Dict
 
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.embeddings.openai import OpenAIEmbeddings
 from langchain_community.utils.openai import is_openai_v1
@@ -38,7 +38,7 @@ class OctoAIEmbeddings(OpenAIEmbeddings):
     def lc_secrets(self) -> Dict[str, str]:
         return {"octoai_api_token": "OCTOAI_API_TOKEN"}
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: dict) -> dict:
         """Validate that api key and python package exists in environment."""
         values["endpoint_url"] = get_from_dict_or_env(

libs/community/langchain_community/embeddings/openai.py

@@ -22,7 +22,11 @@ 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.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.utils import (
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+    pre_init,
+)
 from tenacity import (
     AsyncRetrying,
     before_sleep_log,
@@ -282,7 +286,7 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["openai_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/embeddings/premai.py

@@ -5,8 +5,8 @@ from typing import Any, Callable, Dict, List, Optional, Union
 
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import create_base_retry_decorator
-from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -32,7 +32,7 @@ class PremAIEmbeddings(BaseModel, Embeddings):
 
     client: Any
 
-    @root_validator()
+    @pre_init
     def validate_environments(cls, values: Dict) -> Dict:
         """Validate that the package is installed and that the API token is valid"""
         try:

libs/community/langchain_community/embeddings/sagemaker_endpoint.py

@@ -1,7 +1,8 @@
 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, Extra
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.sagemaker_endpoint import ContentHandlerBase
 
@@ -115,7 +116,7 @@ class SagemakerEndpointEmbeddings(BaseModel, Embeddings):
         extra = Extra.forbid
         arbitrary_types_allowed = True
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Dont do anything if client provided externally"""
         if values.get("client") is not None:

libs/community/langchain_community/embeddings/sambanova.py

@@ -3,8 +3,8 @@ from typing import Dict, Generator, List, Optional
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 
 class SambaStudioEmbeddings(BaseModel, Embeddings):
@@ -64,7 +64,7 @@ class SambaStudioEmbeddings(BaseModel, Embeddings):
     batch_size: int = 32
     """Batch size for the embedding models"""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["sambastudio_embeddings_base_url"] = get_from_dict_or_env(

libs/community/langchain_community/embeddings/solar.py

@@ -6,8 +6,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -80,7 +80,7 @@ class SolarEmbeddings(BaseModel, Embeddings):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key exists in environment."""
         solar_api_key = convert_to_secret_str(

libs/community/langchain_community/embeddings/vertexai.py

@@ -8,7 +8,7 @@ from typing import Any, Dict, List, Literal, Optional, Tuple
 from langchain_core._api.deprecation import deprecated
 from langchain_core.embeddings import Embeddings
 from langchain_core.language_models.llms import create_base_retry_decorator
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.vertexai import _VertexAICommon
 from langchain_community.utilities.vertexai import raise_vertex_import_error
@@ -33,7 +33,7 @@ class VertexAIEmbeddings(_VertexAICommon, Embeddings):
     show_progress_bar: bool = False
     """Whether to show a tqdm progress bar. Must have `tqdm` installed."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validates that the python package exists in environment."""
         cls._try_init_vertexai(values)

libs/community/langchain_community/embeddings/volcengine.py

@@ -4,8 +4,8 @@ import logging
 from typing import Any, Dict, List, Optional
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, root_validator
+from langchain_core.pydantic_v1 import BaseModel
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -43,7 +43,7 @@ class VolcanoEmbeddings(BaseModel, Embeddings):
     client: Any
     """volcano client"""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """
         Validate whether volcano_ak and volcano_sk in the environment variables or

libs/community/langchain_community/embeddings/yandex.py

@@ -7,8 +7,8 @@ import time
 from typing import Any, Callable, Dict, List, Sequence
 
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -76,7 +76,7 @@ class YandexGPTEmbeddings(BaseModel, Embeddings):
 
         allow_population_by_field_name = True
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that iam token exists in environment."""
 

libs/community/langchain_community/llms/ai21.py

@@ -3,8 +3,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
 class AI21PenaltyData(BaseModel):
@@ -73,7 +73,7 @@ class AI21(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         ai21_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/aleph_alpha.py

@@ -2,8 +2,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -129,7 +129,7 @@ class AlephAlpha(LLM):
     """Stop sequences to use."""
 
     # Client params
-    aleph_alpha_api_key: Optional[str] = None
+    aleph_alpha_api_key: Optional[SecretStr] = None
     """API key for Aleph Alpha API."""
     host: str = "https://api.aleph-alpha.com"
     """The hostname of the API host. 
@@ -167,7 +167,7 @@ class AlephAlpha(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["aleph_alpha_api_key"] = convert_to_secret_str(

libs/community/langchain_community/llms/anthropic.py

@@ -25,6 +25,7 @@ from langchain_core.utils import (
     check_package_version,
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 from langchain_core.utils.utils import build_extra_kwargs, convert_to_secret_str
 
@@ -74,7 +75,7 @@ class _AnthropicCommon(BaseLanguageModel):
         )
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["anthropic_api_key"] = convert_to_secret_str(
@@ -185,7 +186,7 @@ class Anthropic(LLM, _AnthropicCommon):
         allow_population_by_field_name = True
         arbitrary_types_allowed = True
 
-    @root_validator()
+    @pre_init
     def raise_warning(cls, values: Dict) -> Dict:
         """Raise warning that this class is deprecated."""
         warnings.warn(

libs/community/langchain_community/llms/anyscale.py

@@ -14,8 +14,8 @@ from langchain_core.callbacks import (
     CallbackManagerForLLMRun,
 )
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.openai import (
     BaseOpenAI,
@@ -93,7 +93,7 @@ class Anyscale(BaseOpenAI):
     def is_lc_serializable(cls) -> bool:
         return False
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["anyscale_api_base"] = get_from_dict_or_env(

libs/community/langchain_community/llms/aphrodite.py

@@ -3,7 +3,8 @@ from typing import Any, Dict, List, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import BaseLLM
 from langchain_core.outputs import Generation, LLMResult
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
+from langchain_core.utils import pre_init
 
 
 class Aphrodite(BaseLLM):
@@ -157,7 +158,7 @@ class Aphrodite(BaseLLM):
 
     client: Any  #: :meta private:
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that python package exists in environment."""
 

libs/community/langchain_community/llms/baichuan.py

@@ -7,8 +7,8 @@ from typing import Any, Dict, List, Optional
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -31,7 +31,7 @@ class BaichuanLLM(LLM):
     baichuan_api_host: Optional[str] = None
     baichuan_api_key: Optional[SecretStr] = None
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         values["baichuan_api_key"] = convert_to_secret_str(
             get_from_dict_or_env(values, "baichuan_api_key", "BAICHUAN_API_KEY")

libs/community/langchain_community/llms/baidu_qianfan_endpoint.py

@@ -16,8 +16,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -76,7 +76,7 @@ class QianfanLLMEndpoint(LLM):
     In the case of other model, passing these params will not affect the result.
     """
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         values["qianfan_ak"] = convert_to_secret_str(
             get_from_dict_or_env(

libs/community/langchain_community/llms/bananadev.py

@@ -4,7 +4,7 @@ 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.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -63,7 +63,7 @@ class Banana(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         banana_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/beam.py

@@ -10,7 +10,7 @@ import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -95,7 +95,7 @@ class Beam(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         beam_client_id = get_from_dict_or_env(

libs/community/langchain_community/llms/bedrock.py

@@ -21,8 +21,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import BaseModel, Extra, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra, Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 from langchain_community.utilities.anthropic import (
@@ -389,7 +389,7 @@ class BedrockBase(BaseModel, ABC):
                 ...Logic to handle guardrail intervention...
     """  # noqa: E501
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that AWS credentials to and python package exists in environment."""
 
@@ -743,7 +743,7 @@ class Bedrock(LLM, BedrockBase):
 
     """
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         model_id = values["model_id"]
         if model_id.startswith("anthropic.claude-3"):

libs/community/langchain_community/llms/cerebriumai.py

@@ -5,7 +5,7 @@ import requests
 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.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -62,7 +62,7 @@ class CerebriumAI(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         cerebriumai_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/clarifai.py

@@ -4,7 +4,8 @@ from typing import Any, Dict, List, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import Generation, LLMResult
-from langchain_core.pydantic_v1 import Extra, Field, root_validator
+from langchain_core.pydantic_v1 import Extra, Field
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -53,7 +54,7 @@ class Clarifai(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that we have all required info to access Clarifai
         platform and python package exists in environment."""

libs/community/langchain_community/llms/cohere.py

@@ -10,8 +10,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.load.serializable import Serializable
-from langchain_core.pydantic_v1 import Extra, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Extra, Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -95,7 +95,7 @@ class BaseCohere(Serializable):
     user_agent: str = "langchain"
     """Identifier for the application making the request."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         try:

libs/community/langchain_community/llms/ctransformers.py

@@ -6,7 +6,7 @@ from langchain_core.callbacks import (
     CallbackManagerForLLMRun,
 )
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import pre_init
 
 
 class CTransformers(LLM):
@@ -57,7 +57,7 @@ class CTransformers(LLM):
         """Return type of llm."""
         return "ctransformers"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that ``ctransformers`` package is installed."""
         try:

libs/community/langchain_community/llms/ctranslate2.py

@@ -3,7 +3,8 @@ from typing import Any, Dict, List, Optional, Union
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, LLMResult
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
+from langchain_core.utils import pre_init
 
 
 class CTranslate2(BaseLLM):
@@ -50,7 +51,7 @@ class CTranslate2(BaseLLM):
     explicitly specified.
     """
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that python package exists in environment."""
 

libs/community/langchain_community/llms/deepinfra.py

@@ -8,8 +8,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.utilities.requests import Requests
 
@@ -43,7 +43,7 @@ class DeepInfra(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         deepinfra_api_token = get_from_dict_or_env(

libs/community/langchain_community/llms/deepsparse.py

@@ -1,12 +1,18 @@
 # flake8: noqa
+from langchain_core.utils import pre_init
 from typing import Any, AsyncIterator, Dict, Iterator, List, Optional, Union
+from langchain_core.utils import pre_init
 from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import pre_init
 from langchain_core.callbacks import (
     AsyncCallbackManagerForLLMRun,
     CallbackManagerForLLMRun,
 )
+from langchain_core.utils import pre_init
 from langchain_core.language_models.llms import LLM
+from langchain_core.utils import pre_init
 from langchain_community.llms.utils import enforce_stop_tokens
+from langchain_core.utils import pre_init
 from langchain_core.outputs import GenerationChunk
 
 
@@ -55,7 +61,7 @@ class DeepSparse(LLM):
         """Return type of llm."""
         return "deepsparse"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that ``deepsparse`` package is installed."""
         try:

libs/community/langchain_community/llms/edenai.py

@@ -10,7 +10,7 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 from langchain_community.utilities.requests import Requests
@@ -73,7 +73,7 @@ class EdenAI(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         values["edenai_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/llms/exllamav2.py

@@ -3,7 +3,8 @@ from typing import Any, Dict, Iterator, List, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
+from langchain_core.utils import pre_init
 
 
 class ExLlamaV2(LLM):
@@ -58,7 +59,7 @@ class ExLlamaV2(LLM):
     disallowed_tokens: List[int] = Field(None)
     """List of tokens to disallow during generation."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         try:
             import torch

libs/community/langchain_community/llms/fireworks.py

@@ -9,8 +9,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import BaseLLM, create_base_retry_decorator
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str
+from langchain_core.utils import convert_to_secret_str, pre_init
 from langchain_core.utils.env import get_from_dict_or_env
 
 
@@ -61,7 +61,7 @@ class Fireworks(BaseLLM):
         """Get the namespace of the langchain object."""
         return ["langchain", "llms", "fireworks"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key in environment."""
         try:

libs/community/langchain_community/llms/friendli.py

@@ -10,7 +10,8 @@ from langchain_core.callbacks.manager import (
 from langchain_core.language_models.llms import LLM
 from langchain_core.load.serializable import Serializable
 from langchain_core.outputs import GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
+from langchain_core.utils import pre_init
 from langchain_core.utils.env import get_from_dict_or_env
 from langchain_core.utils.utils import convert_to_secret_str
 
@@ -66,7 +67,7 @@ class BaseFriendli(Serializable):
     # is used by default.
     top_p: Optional[float] = None
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate if personal access token is provided in environment."""
         try:

libs/community/langchain_community/llms/gigachat.py

@@ -11,7 +11,7 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.load.serializable import Serializable
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import pre_init
 
 if TYPE_CHECKING:
     import gigachat
@@ -113,7 +113,7 @@ class _BaseGigaChat(Serializable):
             verbose=self.verbose,
         )
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate authenticate data in environment and python package is installed."""
         try:

libs/community/langchain_community/llms/google_palm.py

@@ -6,8 +6,8 @@ from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LanguageModelInput
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms import BaseLLM
 from langchain_community.utilities.vertexai import create_retry_decorator
@@ -107,7 +107,7 @@ class GooglePalm(BaseLLM, BaseModel):
         """Get the namespace of the langchain object."""
         return ["langchain", "llms", "google_palm"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate api key, python package exists."""
         google_api_key = get_from_dict_or_env(

libs/community/langchain_community/llms/gooseai.py

@@ -4,7 +4,7 @@ from typing import Any, Dict, List, Mapping, Optional
 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.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -86,7 +86,7 @@ class GooseAI(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         gooseai_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/gpt4all.py

@@ -3,7 +3,8 @@ from typing import Any, Dict, List, Mapping, Optional, Set
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Extra, Field, root_validator
+from langchain_core.pydantic_v1 import Extra, Field
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -127,7 +128,7 @@ class GPT4All(LLM):
             "streaming": self.streaming,
         }
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the python package exists in the environment."""
         try:

libs/community/langchain_community/llms/huggingface_endpoint.py

@@ -10,7 +10,11 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.utils import (
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+    pre_init,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -162,7 +166,7 @@ class HuggingFaceEndpoint(LLM):
         values["model"] = values.get("endpoint_url") or values.get("repo_id")
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that package is installed and that the API token is valid."""
         try:

libs/community/langchain_community/llms/huggingface_hub.py

@@ -4,8 +4,8 @@ from typing import Any, Dict, List, Mapping, Optional
 from langchain_core._api.deprecation import deprecated
 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 Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -61,7 +61,7 @@ class HuggingFaceHub(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         huggingfacehub_api_token = get_from_dict_or_env(

libs/community/langchain_community/llms/huggingface_text_gen_inference.py

@@ -9,7 +9,7 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
-from langchain_core.utils import get_pydantic_field_names
+from langchain_core.utils import get_pydantic_field_names, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -134,7 +134,7 @@ class HuggingFaceTextGenInference(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that python package exists in environment."""
 

libs/community/langchain_community/llms/llamacpp.py

@@ -8,7 +8,7 @@ from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_pydantic_field_names
+from langchain_core.utils import get_pydantic_field_names, pre_init
 from langchain_core.utils.utils import build_extra_kwargs
 
 logger = logging.getLogger(__name__)
@@ -133,7 +133,7 @@ class LlamaCpp(LLM):
     verbose: bool = True
     """Print verbose output to stderr."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that llama-cpp-python library is installed."""
         try:

libs/community/langchain_community/llms/manifest.py

@@ -2,7 +2,8 @@ from typing import Any, Dict, List, Mapping, Optional
 
 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 Extra
+from langchain_core.utils import pre_init
 
 
 class ManifestWrapper(LLM):
@@ -16,7 +17,7 @@ class ManifestWrapper(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that python package exists in environment."""
         try:

libs/community/langchain_community/llms/minimax.py

@@ -16,7 +16,7 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import LLM
 from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -72,7 +72,7 @@ class MinimaxCommon(BaseModel):
     minimax_group_id: Optional[str] = None
     minimax_api_key: Optional[SecretStr] = None
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["minimax_api_key"] = convert_to_secret_str(

libs/community/langchain_community/llms/moonshot.py

@@ -4,7 +4,7 @@ import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LLM
 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 langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -79,7 +79,7 @@ class MoonshotCommon(BaseModel):
         """
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["moonshot_api_key"] = convert_to_secret_str(

libs/community/langchain_community/llms/mosaicml.py

@@ -3,8 +3,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -64,7 +64,7 @@ class MosaicML(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         mosaicml_api_token = get_from_dict_or_env(

libs/community/langchain_community/llms/nlpcloud.py

@@ -2,8 +2,8 @@ from typing import Any, Dict, List, Mapping, Optional
 
 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 Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
 class NLPCloud(LLM):
@@ -56,7 +56,7 @@ class NLPCloud(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["nlpcloud_api_key"] = convert_to_secret_str(

libs/community/langchain_community/llms/oci_data_science_model_deployment_endpoint.py

@@ -4,8 +4,8 @@ from typing import Any, Dict, List, Optional
 import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -47,7 +47,7 @@ class OCIModelDeploymentLLM(LLM):
     """Stop words to use when generating. Model output is cut off
     at the first occurrence of any of these substrings."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(  # pylint: disable=no-self-argument
         cls, values: Dict
     ) -> Dict:

libs/community/langchain_community/llms/oci_generative_ai.py

@@ -8,7 +8,8 @@ from typing import Any, Dict, Iterator, List, Mapping, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -99,7 +100,7 @@ class OCIGenAIBase(BaseModel, ABC):
     is_stream: bool = False
     """Whether to stream back partial progress"""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that OCI config and python package exists in environment."""
 

libs/community/langchain_community/llms/octoai_endpoint.py

@@ -1,7 +1,7 @@
 from typing import Any, Dict
 
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.openai import BaseOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -66,7 +66,7 @@ class OctoAIEndpoint(BaseOpenAI):
         """Return type of llm."""
         return "octoai_endpoint"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["octoai_api_base"] = get_from_dict_or_env(

libs/community/langchain_community/llms/opaqueprompts.py

@@ -5,8 +5,8 @@ from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import BaseLanguageModel
 from langchain_core.language_models.llms import LLM
 from langchain_core.messages import AIMessage
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -38,7 +38,7 @@ class OpaquePrompts(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validates that the OpaquePrompts API key and the Python package exist."""
         try:

libs/community/langchain_community/llms/openai.py

@@ -29,7 +29,11 @@ from langchain_core.callbacks import (
 from langchain_core.language_models.llms import BaseLLM, create_base_retry_decorator
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
 from langchain_core.pydantic_v1 import Field, root_validator
-from langchain_core.utils import get_from_dict_or_env, get_pydantic_field_names
+from langchain_core.utils import (
+    get_from_dict_or_env,
+    get_pydantic_field_names,
+    pre_init,
+)
 from langchain_core.utils.utils import build_extra_kwargs
 
 from langchain_community.utils.openai import is_openai_v1
@@ -269,7 +273,7 @@ class BaseOpenAI(BaseLLM):
         )
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         if values["n"] < 1:
@@ -818,7 +822,7 @@ class AzureOpenAI(BaseOpenAI):
         """Get the namespace of the langchain object."""
         return ["langchain", "llms", "openai"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         if values["n"] < 1:
@@ -1025,7 +1029,7 @@ class OpenAIChat(BaseLLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         openai_api_key = get_from_dict_or_env(

libs/community/langchain_community/llms/openlm.py

@@ -1,6 +1,6 @@
 from typing import Any, Dict
 
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.openai import BaseOpenAI
 
@@ -16,7 +16,7 @@ class OpenLM(BaseOpenAI):
     def _invocation_params(self) -> Dict[str, Any]:
         return {**{"model": self.model_name}, **super()._invocation_params}
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         try:
             import openlm

libs/community/langchain_community/llms/pai_eas_endpoint.py

@@ -6,8 +6,7 @@ import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import root_validator
+from langchain_core.utils import get_from_dict_or_env, pre_init
-from langchain_core.utils import get_from_dict_or_env
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -52,7 +51,7 @@ class PaiEasEndpoint(LLM):
 
     version: Optional[str] = "2.0"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["eas_service_url"] = get_from_dict_or_env(

libs/community/langchain_community/llms/petals.py

@@ -4,7 +4,7 @@ from typing import Any, Dict, List, Mapping, Optional
 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.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -86,7 +86,7 @@ class Petals(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         huggingface_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/pipelineai.py

@@ -10,7 +10,7 @@ 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_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -65,7 +65,7 @@ class PipelineAI(LLM, BaseModel):
         values["pipeline_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         pipeline_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/predictionguard.py

@@ -3,8 +3,8 @@ from typing import Any, Dict, List, Optional
 
 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 Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -53,7 +53,7 @@ class PredictionGuard(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the access token and python package exists in environment."""
         token = get_from_dict_or_env(values, "token", "PREDICTIONGUARD_TOKEN")

libs/community/langchain_community/llms/replicate.py

@@ -7,7 +7,7 @@ from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
 from langchain_core.pydantic_v1 import Extra, Field, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 if TYPE_CHECKING:
     from replicate.prediction import Prediction
@@ -97,7 +97,7 @@ class Replicate(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         replicate_api_token = get_from_dict_or_env(

libs/community/langchain_community/llms/rwkv.py

@@ -8,7 +8,8 @@ from typing import Any, Dict, List, Mapping, Optional, Set
 
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Extra
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -98,7 +99,7 @@ class RWKV(LLM, BaseModel):
             "verbose",
         }
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the python package exists in the environment."""
         try:

libs/community/langchain_community/llms/sagemaker_endpoint.py

@@ -7,7 +7,8 @@ from typing import Any, Dict, Generic, Iterator, List, Mapping, Optional, TypeVa
 
 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 Extra
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -249,7 +250,7 @@ class SagemakerEndpoint(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Dont do anything if client provided externally"""
         if values.get("client") is not None:

libs/community/langchain_community/llms/sambanova.py

@@ -5,8 +5,8 @@ import requests
 from langchain_core.callbacks.manager import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import Extra, root_validator
+from langchain_core.pydantic_v1 import Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 
 class SVEndpointHandler:
@@ -218,7 +218,7 @@ class Sambaverse(LLM):
     def is_lc_serializable(cls) -> bool:
         return True
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         values["sambaverse_url"] = get_from_dict_or_env(
@@ -731,7 +731,7 @@ class SambaStudio(LLM):
         """Return type of llm."""
         return "Sambastudio LLM"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["sambastudio_base_url"] = get_from_dict_or_env(

libs/community/langchain_community/llms/solar.py

@@ -4,7 +4,7 @@ import requests
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models import LLM
 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 langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -68,7 +68,7 @@ class SolarCommon(BaseModel):
     def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         api_key = get_from_dict_or_env(values, "solar_api_key", "SOLAR_API_KEY")
         if api_key is None or len(api_key) == 0:

libs/community/langchain_community/llms/sparkllm.py

@@ -17,8 +17,8 @@ from wsgiref.handlers import format_date_time
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -54,7 +54,7 @@ class SparkLLM(LLM):
     top_k: int = 4
     model_kwargs: Dict[str, Any] = Field(default_factory=dict)
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         values["spark_app_id"] = get_from_dict_or_env(
             values,

libs/community/langchain_community/llms/stochasticai.py

@@ -6,7 +6,7 @@ import requests
 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.utils import convert_to_secret_str, get_from_dict_or_env
+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
 
@@ -58,7 +58,7 @@ class StochasticAI(LLM):
         values["model_kwargs"] = extra
         return values
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key exists in environment."""
         stochasticai_api_key = convert_to_secret_str(

libs/community/langchain_community/llms/symblai_nebula.py

@@ -5,8 +5,8 @@ from typing import Any, Callable, 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, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from requests import ConnectTimeout, ReadTimeout, RequestException
 from tenacity import (
     before_sleep_log,
@@ -65,7 +65,7 @@ class Nebula(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         nebula_service_url = get_from_dict_or_env(

libs/community/langchain_community/llms/tongyi.py

@@ -24,8 +24,8 @@ from langchain_core.callbacks import (
 )
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 from requests.exceptions import HTTPError
 from tenacity import (
     before_sleep_log,
@@ -198,7 +198,7 @@ class Tongyi(BaseLLM):
         """Return type of llm."""
         return "tongyi"
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and python package exists in environment."""
         values["dashscope_api_key"] = get_from_dict_or_env(

libs/community/langchain_community/llms/vertexai.py

@@ -10,7 +10,8 @@ from langchain_core.callbacks.manager import (
 )
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import BaseModel, Field, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field
+from langchain_core.utils import pre_init
 
 from langchain_community.utilities.vertexai import (
     create_retry_decorator,
@@ -222,7 +223,7 @@ class VertexAI(_VertexAICommon, BaseLLM):
         """Get the namespace of the langchain object."""
         return ["langchain", "llms", "vertexai"]
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the python package exists in environment."""
         tuned_model_name = values.get("tuned_model_name")
@@ -409,7 +410,7 @@ class VertexAIModelGarden(_VertexAIBase, BaseLLM):
     "Set result_arg to None if output of the model is expected to be a string."
     "Otherwise, if it's a dict, provided an argument that contains the result."
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that the python package exists in environment."""
         try:

libs/community/langchain_community/llms/vllm.py

@@ -3,7 +3,8 @@ from typing import Any, Dict, List, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, LLMResult
-from langchain_core.pydantic_v1 import Field, root_validator
+from langchain_core.pydantic_v1 import Field
+from langchain_core.utils import pre_init
 
 from langchain_community.llms.openai import BaseOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -73,7 +74,7 @@ class VLLM(BaseLLM):
 
     client: Any  #: :meta private:
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that python package exists in environment."""
 

libs/community/langchain_community/llms/volcengine_maas.py

@@ -5,8 +5,8 @@ from typing import Any, Dict, Iterator, List, Optional
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import LLM
 from langchain_core.outputs import GenerationChunk
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
+from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 
 class VolcEngineMaasBase(BaseModel):
@@ -52,7 +52,7 @@ class VolcEngineMaasBase(BaseModel):
     """Timeout for read response from volc engine maas endpoint. 
     Default is 60 seconds."""
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         volc_engine_maas_ak = convert_to_secret_str(
             get_from_dict_or_env(values, "volc_engine_maas_ak", "VOLC_ACCESSKEY")

libs/community/langchain_community/llms/watsonxllm.py

@@ -6,8 +6,8 @@ from langchain_core._api.deprecation import deprecated
 from langchain_core.callbacks import CallbackManagerForLLMRun
 from langchain_core.language_models.llms import BaseLLM
 from langchain_core.outputs import Generation, GenerationChunk, LLMResult
-from langchain_core.pydantic_v1 import Extra, SecretStr, root_validator
+from langchain_core.pydantic_v1 import Extra, SecretStr
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 
 logger = logging.getLogger(__name__)
 
@@ -115,7 +115,7 @@ class WatsonxLLM(BaseLLM):
             "instance_id": "WATSONX_INSTANCE_ID",
         }
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that credentials and python package exists in environment."""
         values["url"] = convert_to_secret_str(

libs/community/langchain_community/llms/writer.py

@@ -3,8 +3,8 @@ 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, root_validator
+from langchain_core.pydantic_v1 import Extra
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.utils import get_from_dict_or_env, pre_init
 
 from langchain_community.llms.utils import enforce_stop_tokens
 
@@ -69,7 +69,7 @@ class Writer(LLM):
 
         extra = Extra.forbid
 
-    @root_validator()
+    @pre_init
     def validate_environment(cls, values: Dict) -> Dict:
         """Validate that api key and organization id exist in environment."""