removing remaining v1 logic

libs/langgraph/langgraph/graph/schema_utils.py

@@ -13,7 +13,7 @@ from typing import (
     get_type_hints,
 )
 
-from pydantic import BaseModel
+from pydantic import BaseModel, TypeAdapter
 
 __all__ = ["SchemaCoercionMapper"]
 
@@ -243,67 +243,10 @@ _IDENTITY_TYPES: tuple[type[Any], ...] = (
     type(None),
 )
 
-try:
-    # Pydantic v2.
-    from pydantic import TypeAdapter
 
-    try:
-        import pydantic.v1.types as v1_types_
-        from pydantic.v1 import parse_obj_as
-
-        v1_types = tuple(
-            v for k, v in vars(v1_types_).items() if k in v1_types_.__all__
-        )
-    except ImportError:
-        v1_types = ()
-
-        def parse_obj_as(tp: Any, v: Any) -> Any:  # type: ignore
-            return v
-
-    try:
-        from pydantic.v1 import parse_obj_as
-        from pydantic.v1.main import create_model
-    except ImportError:
-        create_model = None  # type: ignore
-
-    def _get_v1_parser(tp: Any) -> Any:
-        if create_model is not None:
-            try:
-                parser = create_model(
-                    f"ParsingModel[{tp}]",
-                    __root__=(tp, ...),
-                )
-                return lambda v: parser(__root__=v).__root__  # type: ignore
-            except RuntimeError:
-                return lambda v: v
-        return lambda v: parse_obj_as(tp, v)
-
-    @functools.lru_cache(maxsize=2048)
-    def _adapter_for(tp: Any) -> Callable[[Any], Any]:  # noqa: D401
-        if tp in v1_types:
-            return _get_v1_parser(tp)
-        try:
-            return TypeAdapter(
-                tp, config={"arbitrary_types_allowed": True}
-            ).validate_python
-        except TypeError:
-            # Delayed classes like ConstrainedList
-            return _get_v1_parser(tp)
-
-except ImportError:
-    # Pydantic V1
-    from pydantic.v1.main import create_model
-
-    @functools.lru_cache(maxsize=2048)
-    def _adapter_for(tp: Any) -> Callable[[Any], Any]:  # noqa: D401
-        try:
-            parser = create_model(
-                f"ParsingModel[{tp}]",
-                __root__=(tp, ...),
-            )
-            return lambda v: parser(__root__=v).__root__  # type: ignore
-        except RuntimeError:
-            return lambda v: v
+@functools.lru_cache(maxsize=2048)
+def _adapter_for(tp: Any) -> Callable[[Any], Any]:  # noqa: D401
+    return TypeAdapter(tp, config={"arbitrary_types_allowed": True}).validate_python
 
 
 def _get_adapter(tp: Any) -> Callable[[Any], Any]:

libs/langgraph/tests/test_pydantic.py

@@ -8,8 +8,18 @@ import uuid
 from enum import Enum
 from typing import Annotated, Literal, Optional, Union
 
-import pytest
-from pydantic import BaseModel, field_validator, model_validator
+from pydantic import (
+    BaseModel,
+    ByteSize,
+    Field,
+    SecretStr,
+    confloat,
+    conint,
+    conlist,
+    constr,
+    field_validator,
+    model_validator,
+)
 
 from langgraph.constants import END, START
 from langgraph.graph.state import StateGraph
@@ -47,36 +57,9 @@ def test_is_supported_by_pydantic() -> None:
     assert is_supported_by_pydantic(PydanticModel) is True
 
 
-@pytest.mark.parametrize("version", ["v1", "v2"])
 def test_nested_pydantic_models(version: str) -> None:
     """Test that nested Pydantic models are properly constructed from leaf nodes up."""
 
-    # Define nested Pydantic models
-    # Import necessary modules
-
-    if version == "v1":
-        from pydantic.v1 import (  # type: ignore
-            BaseModel,
-            ByteSize,
-            Field,
-            SecretStr,
-            confloat,
-            conint,
-            conlist,
-            constr,
-        )
-    else:
-        from pydantic import (  # type: ignore
-            BaseModel,
-            ByteSize,
-            Field,
-            SecretStr,
-            confloat,
-            conint,
-            conlist,
-            constr,
-        )
-
     class NestedModel(BaseModel):
         value: int
         name: str

libs/langgraph/tests/test_state.py

@@ -7,7 +7,7 @@ from typing import Annotated as Annotated2
 
 import pytest
 from langchain_core.runnables import RunnableConfig, RunnableLambda
-from pydantic.v1 import BaseModel
+from pydantic import BaseModel
 from typing_extensions import NotRequired, Required, TypedDict
 
 from langgraph.graph.state import StateGraph, _get_node_name, _warn_invalid_state_schema