x

libs/partners/openai/langchain_openai/chat_models/azure.py

@@ -31,12 +31,12 @@ from langchain_core.output_parsers.openai_tools import (
     PydanticToolsParser,
 )
 from langchain_core.outputs import ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough
 from langchain_core.tools import BaseTool
 from langchain_core.utils import from_env, secret_from_env
 from langchain_core.utils.function_calling import convert_to_openai_tool
 from langchain_core.utils.pydantic import is_basemodel_subclass
+from pydantic import BaseModel, Field, SecretStr, root_validator
 
 from langchain_openai.chat_models.base import BaseChatOpenAI
 

libs/partners/openai/langchain_openai/chat_models/base.py

@@ -73,7 +73,6 @@ from langchain_core.output_parsers.openai_tools import (
     parse_tool_call,
 )
 from langchain_core.outputs import ChatGeneration, ChatGenerationChunk, ChatResult
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.runnables import Runnable, RunnableMap, RunnablePassthrough, chain
 from langchain_core.runnables.config import run_in_executor
 from langchain_core.tools import BaseTool
@@ -92,6 +91,14 @@ from langchain_core.utils.pydantic import (
     is_basemodel_subclass,
 )
 from langchain_core.utils.utils import build_extra_kwargs
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    SecretStr,
+    model_validator,
+    root_validator,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -377,13 +384,11 @@ class BaseChatOpenAI(BaseChatModel):
     include_response_headers: bool = False
     """Whether to include response headers in the output message response_metadata."""
 
-    class Config:
-        """Configuration for this pydantic object."""
+    model_config = ConfigDict(populate_by_name=True)
 
-        allow_population_by_field_name = True
-
-    @root_validator(pre=True)
-    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+    @model_validator(mode="before")
+    @classmethod
+    def build_extra(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})

libs/partners/openai/langchain_openai/embeddings/azure.py

@@ -5,8 +5,8 @@ from __future__ import annotations
 from typing import Callable, Dict, Optional, Union
 
 import openai
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import from_env, secret_from_env
+from pydantic import Field, SecretStr, root_validator
 
 from langchain_openai.embeddings.base import OpenAIEmbeddings
 

libs/partners/openai/langchain_openai/embeddings/base.py

@@ -21,8 +21,15 @@ from typing import (
 import openai
 import tiktoken
 from langchain_core.embeddings import Embeddings
-from langchain_core.pydantic_v1 import BaseModel, Field, SecretStr, root_validator
 from langchain_core.utils import from_env, get_pydantic_field_names, secret_from_env
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    SecretStr,
+    model_validator,
+    root_validator,
+)
 
 logger = logging.getLogger(__name__)
 
@@ -261,14 +268,11 @@ class OpenAIEmbeddings(BaseModel, Embeddings):
     """Whether to check the token length of inputs and automatically split inputs 
         longer than embedding_ctx_length."""
 
-    class Config:
-        """Configuration for this pydantic object."""
+    model_config = ConfigDict(extra="forbid", populate_by_name=True)
 
-        extra = "forbid"
-        allow_population_by_field_name = True
-
-    @root_validator(pre=True)
-    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+    @model_validator(mode="before")
+    @classmethod
+    def build_extra(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})

libs/partners/openai/langchain_openai/llms/azure.py

@@ -4,8 +4,8 @@ import logging
 from typing import Any, Callable, Dict, List, Mapping, Optional, Union
 
 import openai
-from langchain_core.pydantic_v1 import Field, SecretStr, root_validator
 from langchain_core.utils import from_env, secret_from_env
+from pydantic import Field, SecretStr, root_validator
 
 from langchain_openai.llms.base import BaseOpenAI
 

libs/partners/openai/langchain_openai/llms/base.py

@@ -26,9 +26,9 @@ 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, SecretStr, root_validator
 from langchain_core.utils import get_pydantic_field_names
 from langchain_core.utils.utils import build_extra_kwargs, from_env, secret_from_env
+from pydantic import ConfigDict, Field, SecretStr, model_validator, root_validator
 
 logger = logging.getLogger(__name__)
 
@@ -152,13 +152,11 @@ class BaseOpenAI(BaseLLM):
     """Optional additional JSON properties to include in the request parameters when
     making requests to OpenAI compatible APIs, such as vLLM."""
 
-    class Config:
-        """Configuration for this pydantic object."""
+    model_config = ConfigDict(populate_by_name=True)
 
-        allow_population_by_field_name = True
-
-    @root_validator(pre=True)
-    def build_extra(cls, values: Dict[str, Any]) -> Dict[str, Any]:
+    @model_validator(mode="before")
+    @classmethod
+    def build_extra(cls, values: Dict[str, Any]) -> Any:
         """Build extra kwargs from additional params that were passed in."""
         all_required_field_names = get_pydantic_field_names(cls)
         extra = values.get("model_kwargs", {})

libs/partners/openai/tests/integration_tests/chat_models/test_base.py

@@ -19,13 +19,13 @@ from langchain_core.messages import (
 )
 from langchain_core.outputs import ChatGeneration, ChatResult, LLMResult
 from langchain_core.prompts import ChatPromptTemplate
-from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_standard_tests.integration_tests.chat_models import (
     _validate_tool_call_message,
 )
 from langchain_standard_tests.integration_tests.chat_models import (
     magic_function as invalid_magic_function,
 )
+from pydantic import BaseModel, Field
 
 from langchain_openai import ChatOpenAI
 from tests.unit_tests.fake.callbacks import FakeCallbackHandler

libs/partners/openai/tests/unit_tests/chat_models/test_azure.py

@@ -40,9 +40,7 @@ def test_initialize_more() -> None:
 
 
 def test_initialize_azure_openai_with_openai_api_base_set() -> None:
-    with mock.patch.dict(
-        os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}
-    ):
+    with mock.patch.dict(os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}):
         llm = AzureChatOpenAI(  # type: ignore[call-arg, call-arg]
             api_key="xyz",  # type: ignore[arg-type]
             azure_endpoint="my-base-url",

libs/partners/openai/tests/unit_tests/chat_models/test_base.py

@@ -14,7 +14,7 @@ from langchain_core.messages import (
     ToolCall,
     ToolMessage,
 )
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 from langchain_openai import ChatOpenAI
 from langchain_openai.chat_models.base import (

libs/partners/openai/tests/unit_tests/embeddings/test_azure_embeddings.py

@@ -16,9 +16,7 @@ def test_initialize_azure_openai() -> None:
 
 
 def test_intialize_azure_openai_with_base_set() -> None:
-    with mock.patch.dict(
-            os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}
-    ):
+    with mock.patch.dict(os.environ, {"OPENAI_API_BASE": "https://api.openai.com"}):
         embeddings = AzureOpenAIEmbeddings(  # type: ignore[call-arg, call-arg]
             model="text-embedding-large",
             api_key="xyz",  # type: ignore[arg-type]

libs/partners/openai/tests/unit_tests/fake/callbacks.py

@@ -6,7 +6,7 @@ from uuid import UUID
 
 from langchain_core.callbacks.base import AsyncCallbackHandler, BaseCallbackHandler
 from langchain_core.messages import BaseMessage
-from langchain_core.pydantic_v1 import BaseModel
+from pydantic import BaseModel
 
 
 class BaseFakeCallbackHandler(BaseModel):

libs/partners/openai/tests/unit_tests/test_secrets.py

@@ -2,7 +2,7 @@ from typing import Type, cast
 
 import pytest
 from langchain_core.load import dumpd
-from langchain_core.pydantic_v1 import SecretStr
+from pydantic import SecretStr
 from pytest import CaptureFixture, MonkeyPatch
 
 from langchain_openai import (