Use a submodule for pydantic v1 compat (#9371)

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libs/experimental/langchain_experimental/llms/anthropic_functions.py

@@ -19,7 +19,8 @@ from langchain.schema.messages import (
     BaseMessage,
     SystemMessage,
 )
-from pydantic_v1 import root_validator
+
+from langchain_experimental.pydantic_v1 import root_validator
 
 prompt = """In addition to responding, you can use tools. \
 You have access to the following tools.

libs/experimental/langchain_experimental/llms/jsonformer_decoder.py

@@ -6,7 +6,8 @@ from typing import TYPE_CHECKING, Any, List, Optional, cast
 
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
-from pydantic_v1 import Field, root_validator
+
+from langchain_experimental.pydantic_v1 import Field, root_validator
 
 if TYPE_CHECKING:
     import jsonformer

libs/experimental/langchain_experimental/llms/rellm_decoder.py

@@ -6,7 +6,8 @@ from typing import TYPE_CHECKING, Any, List, Optional, cast
 from langchain.callbacks.manager import CallbackManagerForLLMRun
 from langchain.llms.huggingface_pipeline import HuggingFacePipeline
 from langchain.llms.utils import enforce_stop_tokens
-from pydantic_v1 import Field, root_validator
+
+from langchain_experimental.pydantic_v1 import Field, root_validator
 
 if TYPE_CHECKING:
     import rellm