core[minor],community[minor]: Upgrade all @root_validator() to @pre_i…

…nit (#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 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.utils import get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, Field
+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 @@ def get_lc_namespace(cls) -> List[str]:
         """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 @@
     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 Config:
 
         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 @@
     ChatGeneration,
     ChatResult,
 )
-from langchain_core.pydantic_v1 import BaseModel, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, SecretStr
+from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env, pre_init
 from tenacity import (
     before_sleep_log,
     retry,
@@ -261,7 +261,7 @@ def get_lc_namespace(cls) -> List[str]:
         """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 @@
     convert_to_secret_str,
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 
 logger = logging.getLogger(__name__)
@@ -190,7 +191,7 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         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 @@
     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 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         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 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.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.messages import AIMessageChunk, BaseMessage
 from langchain_core.outputs import 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 langchain_core.pydantic_v1 import Field, SecretStr
+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 @@ def is_lc_serializable(cls) -> bool:
     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 @@
     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 @@ def _completion_with_retry(**kwargs: Any) -> Any:
 
         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.utils import convert_to_secret_str, get_from_dict_or_env
+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 langchain_community.chat_models.openai import ChatOpenAI
 from langchain_community.utils.openai import is_openai_v1
@@ -48,7 +48,7 @@ def lc_secrets(self) -> Dict[str, str]:
     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.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 
 from langchain_community.adapters.openai import (
@@ -274,7 +275,7 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         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 @@
     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 Config:
         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 @@
     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 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         )
         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.utils import get_from_dict_or_env
+from langchain_core.pydantic_v1 import Field
+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 Config:
         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 @@
     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 @@ def _llm_type(self) -> str:
         """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 @@
     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 @@ def get_lc_namespace(cls) -> List[str]:
         """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.utils import (
     get_from_dict_or_env,
     get_pydantic_field_names,
+    pre_init,
 )
 from tenacity import (
     before_sleep_log,
@@ -166,7 +167,7 @@ def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
         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 typing import Dict
 
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
-from langchain_core.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.pydantic_v1 import Field, SecretStr
+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 @@ def lc_secrets(self) -> Dict[str, str]:
             "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 @@
 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.utils import convert_to_secret_str, get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, Field
+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 @@
 
 import requests
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Extra, root_validator
-from langchain_core.utils import get_from_dict_or_env
+from langchain_core.pydantic_v1 import BaseModel, Extra
+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 Config:
 
         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(