move to fields

libs/langgraph/langgraph/graph/state.py

@@ -77,8 +77,8 @@ from langgraph.pregel.write import (
 )
 from langgraph.store.base import BaseStore
 from langgraph.types import All, Checkpointer, Command, RetryPolicy
-from langgraph.utils.fields import get_field_default
-from langgraph.utils.pydantic import create_model, get_update_as_tuples
+from langgraph.utils.fields import get_field_default, get_update_as_tuples
+from langgraph.utils.pydantic import create_model
 from langgraph.utils.runnable import RunnableLike, coerce_to_runnable
 
 logger = logging.getLogger(__name__)

libs/langgraph/langgraph/types.py

@@ -23,7 +23,7 @@ from langchain_core.runnables import Runnable, RunnableConfig
 from typing_extensions import Self
 
 from langgraph.checkpoint.base import BaseCheckpointSaver, CheckpointMetadata
-from langgraph.utils.pydantic import get_update_as_tuples
+from langgraph.utils.fields import get_update_as_tuples
 
 if TYPE_CHECKING:
     from langgraph.pregel.protocol import PregelProtocol

libs/langgraph/langgraph/utils/fields.py

@@ -1,8 +1,14 @@
 import dataclasses
-from typing import Any, Generator, Optional, Type, Union, get_type_hints
+from typing import Any, Generator, Optional, Sequence, Type, Union, get_type_hints
 
+from pydantic import BaseModel
+from pydantic.v1 import BaseModel as BaseModelV1
 from typing_extensions import Annotated, NotRequired, ReadOnly, Required, get_origin
 
+# NOTE: this is redefined here separately from langgraph.constants
+# to avoid a circular import
+MISSING = object()
+
 
 def _is_optional_type(type_: Any) -> bool:
     """Check if a type is Optional."""
@@ -147,3 +153,33 @@ def get_enhanced_type_hints(
             pass
 
         yield name, typ, default, description
+
+
+def get_update_as_tuples(input: Any, keys: Sequence[str]) -> list[tuple[str, Any]]:
+    """Get Pydantic state update as a list of (key, value) tuples."""
+    # Pydantic v1
+    if isinstance(input, BaseModelV1):
+        keep: Optional[set[str]] = input.__fields_set__
+        defaults = {k: v.default for k, v in input.__fields__.items()}
+    # Pydantic v2
+    elif isinstance(input, BaseModel):
+        keep = input.model_fields_set
+        defaults = {k: v.default for k, v in input.model_fields.items()}
+    else:
+        keep = None
+        defaults = {}
+
+    # NOTE: This behavior for Pydantic is somewhat inelegant,
+    # but we keep around for backwards compatibility
+    # if input is a Pydantic model, only update values
+    # that are different from the default values or in the keep set
+    return [
+        (k, value)
+        for k in keys
+        if (value := getattr(input, k, MISSING)) is not MISSING
+        and (
+            value is not None
+            or defaults.get(k, MISSING) is not None
+            or (keep is not None and k in keep)
+        )
+    ]

libs/langgraph/langgraph/utils/pydantic.py

@@ -1,16 +1,12 @@
 import sys
 import typing
 from dataclasses import is_dataclass
-from typing import Any, Dict, Optional, Sequence, Union
+from typing import Any, Dict, Optional, Union
 
 import typing_extensions
 from pydantic import BaseModel
 from pydantic.v1 import BaseModel as BaseModelV1
 
-# NOTE: this is redefined here separately from langgraph.constants
-# to avoid a circular import
-MISSING = object()
-
 
 def create_model(
     model_name: str,
@@ -45,36 +41,6 @@ def create_model(
         return create_model(model_name, **v1_kwargs, **(field_definitions or {}))
 
 
-def get_update_as_tuples(input: Any, keys: Sequence[str]) -> list[tuple[str, Any]]:
-    """Get Pydantic state update as a list of (key, value) tuples."""
-    # Pydantic v1
-    if isinstance(input, BaseModelV1):
-        keep: Optional[set[str]] = input.__fields_set__
-        defaults = {k: v.default for k, v in input.__fields__.items()}
-    # Pydantic v2
-    elif isinstance(input, BaseModel):
-        keep = input.model_fields_set
-        defaults = {k: v.default for k, v in input.model_fields.items()}
-    else:
-        keep = None
-        defaults = {}
-
-    # NOTE: This behavior for Pydantic is somewhat inelegant,
-    # but we keep around for backwards compatibility
-    # if input is a Pydantic model, only update values
-    # that are different from the default values or in the keep set
-    return [
-        (k, value)
-        for k in keys
-        if (value := getattr(input, k, MISSING)) is not MISSING
-        and (
-            value is not None
-            or defaults.get(k, MISSING) is not None
-            or (keep is not None and k in keep)
-        )
-    ]
-
-
 def is_supported_by_pydantic(type_: Any) -> bool:
     """Check if a given "complex" type is supported by pydantic.