Merge pull request #2691 from langchain-ai/dqbd/enhanced-config-type-…

…extraction

fix(config): extract default values, description from pydantic models, typeddict and dataclass

libs/langgraph/langgraph/pregel/__init__.py

@@ -18,7 +18,6 @@
     Type,
     Union,
     cast,
-    get_type_hints,
     overload,
 )
 from uuid import UUID, uuid5
@@ -117,6 +116,7 @@
     patch_config,
     patch_configurable,
 )
+from langgraph.utils.fields import get_enhanced_type_hints
 from langgraph.utils.pydantic import create_model
 from langgraph.utils.queue import AsyncQueue, SyncQueue  # type: ignore[attr-defined]
 
@@ -319,8 +319,15 @@ def config_specs(self) -> list[ConfigurableFieldSpec]:
                 )
                 + (
                     [
-                        ConfigurableFieldSpec(id=name, annotation=typ)
-                        for name, typ in get_type_hints(self.config_type).items()
+                        ConfigurableFieldSpec(
+                            id=name,
+                            annotation=typ,
+                            default=default,
+                            description=description,
+                        )
+                        for name, typ, default, description in get_enhanced_type_hints(
+                            self.config_type
+                        )
                     ]
                     if self.config_type is not None
                     else []

libs/langgraph/langgraph/utils/fields.py

@@ -1,5 +1,5 @@
 import dataclasses
-from typing import Any, Optional, Type, Union
+from typing import Any, Generator, Optional, Type, Union, get_type_hints
 
 from typing_extensions import Annotated, NotRequired, ReadOnly, Required, get_origin
 
@@ -106,3 +106,44 @@ def get_field_default(name: str, type_: Any, schema: Type[Any]) -> Any:
     if _is_optional_type(type_):
         return None
     return ...
+
+
+def get_enhanced_type_hints(
+    type: Type[Any],
+) -> Generator[tuple[str, Any, Any, Optional[str]], None, None]:
+    """Attempt to extract default values and descriptions from provided type, used for config schema."""
+    for name, typ in get_type_hints(type).items():
+        default = None
+        description = None
+
+        # Pydantic models
+        try:
+            if hasattr(type, "__fields__") and name in type.__fields__:
+                field = type.__fields__[name]
+
+                if hasattr(field, "description") and field.description is not None:
+                    description = field.description
+
+                if hasattr(field, "default") and field.default is not None:
+                    default = field.default
+                    if (
+                        hasattr(default, "__class__")
+                        and getattr(default.__class__, "__name__", "")
+                        == "PydanticUndefinedType"
+                    ):
+                        default = None
+
+        except (AttributeError, KeyError, TypeError):
+            pass
+
+        # TypedDict, dataclass
+        try:
+            if hasattr(type, "__dict__"):
+                type_dict = getattr(type, "__dict__")
+
+                if name in type_dict:
+                    default = type_dict[name]
+        except (AttributeError, KeyError, TypeError):
+            pass
+
+        yield name, typ, default, description

libs/langgraph/tests/test_utils.py

@@ -21,7 +21,11 @@
 
 from langgraph.graph import END, StateGraph
 from langgraph.graph.graph import CompiledGraph
-from langgraph.utils.fields import _is_optional_type, get_field_default
+from langgraph.utils.fields import (
+    _is_optional_type,
+    get_enhanced_type_hints,
+    get_field_default,
+)
 from langgraph.utils.runnable import is_async_callable, is_async_generator
 
 pytestmark = pytest.mark.anyio
@@ -227,3 +231,57 @@ class MyGrandChildDict(MyChildDict, total=False):
     assert get_field_default("val_12", gcannos["val_12"], MyGrandChildDict) is None
     assert get_field_default("val_9", gcannos["val_9"], MyGrandChildDict) is None
     assert get_field_default("val_13", gcannos["val_13"], MyGrandChildDict) == ...
+
+
+def test_enhanced_type_hints() -> None:
+    from dataclasses import dataclass
+    from typing import Annotated
+
+    from pydantic import BaseModel, Field
+
+    class MyTypedDict(TypedDict):
+        val_1: str
+        val_2: int = 42
+        val_3: str = "default"
+
+    hints = list(get_enhanced_type_hints(MyTypedDict))
+    assert len(hints) == 3
+    assert hints[0] == ("val_1", str, None, None)
+    assert hints[1] == ("val_2", int, 42, None)
+    assert hints[2] == ("val_3", str, "default", None)
+
+    @dataclass
+    class MyDataclass:
+        val_1: str
+        val_2: int = 42
+        val_3: str = "default"
+
+    hints = list(get_enhanced_type_hints(MyDataclass))
+    assert len(hints) == 3
+    assert hints[0] == ("val_1", str, None, None)
+    assert hints[1] == ("val_2", int, 42, None)
+    assert hints[2] == ("val_3", str, "default", None)
+
+    class MyPydanticModel(BaseModel):
+        val_1: str
+        val_2: int = 42
+        val_3: str = Field(default="default", description="A description")
+
+    hints = list(get_enhanced_type_hints(MyPydanticModel))
+    assert len(hints) == 3
+    assert hints[0] == ("val_1", str, None, None)
+    assert hints[1] == ("val_2", int, 42, None)
+    assert hints[2] == ("val_3", str, "default", "A description")
+
+    class MyPydanticModelWithAnnotated(BaseModel):
+        val_1: Annotated[str, Field(description="A description")]
+        val_2: Annotated[int, Field(default=42)]
+        val_3: Annotated[
+            str, Field(default="default", description="Another description")
+        ]
+
+    hints = list(get_enhanced_type_hints(MyPydanticModelWithAnnotated))
+    assert len(hints) == 3
+    assert hints[0] == ("val_1", str, None, "A description")
+    assert hints[1] == ("val_2", int, 42, None)
+    assert hints[2] == ("val_3", str, "default", "Another description")