core[patch]: Add pydantic metadata to subset model (langchain-ai#25032)

- **Description:** This includes Pydantic field metadata in
`_create_subset_model_v2` so that it gets included in the final
serialized form that get sent out.
- **Issue:** langchain-ai#25031 
- **Dependencies:** n/a
- **Twitter handle:** @gramliu

---------

Co-authored-by: Bagatur <baskaryan@gmail.com>
Co-authored-by: Bagatur <22008038+baskaryan@users.noreply.github.com>

libs/core/langchain_core/tools.py

@@ -1055,10 +1055,12 @@ def add(a: int, b: int) -> int:
         )
 
 
+# TODO: Type args_schema as TypeBaseModel if we can get mypy to correctly recognize
+# pydantic v2 BaseModel classes.
 def tool(
     *args: Union[str, Callable, Runnable],
     return_direct: bool = False,
-    args_schema: Optional[Type[BaseModel]] = None,
+    args_schema: Optional[Type] = None,
     infer_schema: bool = True,
     response_format: Literal["content", "content_and_artifact"] = "content",
     parse_docstring: bool = False,

libs/core/langchain_core/utils/pydantic.py

@@ -29,8 +29,6 @@ def get_pydantic_major_version() -> int:
     PydanticBaseModel = pydantic.BaseModel
     TypeBaseModel = Type[BaseModel]
 elif PYDANTIC_MAJOR_VERSION == 2:
-    from pydantic.v1 import BaseModel  # pydantic: ignore
-
     # Union type needs to be last assignment to PydanticBaseModel to make mypy happy.
     PydanticBaseModel = Union[BaseModel, pydantic.BaseModel]  # type: ignore
     TypeBaseModel = Union[Type[BaseModel], Type[pydantic.BaseModel]]  # type: ignore
@@ -199,12 +197,12 @@ def _create_subset_model_v1(
 
 def _create_subset_model_v2(
     name: str,
-    model: Type[BaseModel],
+    model: Type[pydantic.BaseModel],
     field_names: List[str],
     *,
     descriptions: Optional[dict] = None,
     fn_description: Optional[str] = None,
-) -> Type[BaseModel]:
+) -> Type[pydantic.BaseModel]:
     """Create a pydantic model with a subset of the model fields."""
     from pydantic import create_model  # pydantic: ignore
     from pydantic.fields import FieldInfo  # pydantic: ignore
@@ -214,10 +212,10 @@ def _create_subset_model_v2(
     for field_name in field_names:
         field = model.model_fields[field_name]  # type: ignore
         description = descriptions_.get(field_name, field.description)
-        fields[field_name] = (
-            field.annotation,
-            FieldInfo(description=description, default=field.default),
-        )
+        field_info = FieldInfo(description=description, default=field.default)
+        if field.metadata:
+            field_info.metadata = field.metadata
+        fields[field_name] = (field.annotation, field_info)
     rtn = create_model(name, **fields)  # type: ignore
 
     rtn.__doc__ = textwrap.dedent(fn_description or model.__doc__ or "")
@@ -230,7 +228,7 @@ def _create_subset_model_v2(
 # However, can't find a way to type hint this.
 def _create_subset_model(
     name: str,
-    model: Type[BaseModel],
+    model: TypeBaseModel,
     field_names: List[str],
     *,
     descriptions: Optional[dict] = None,

libs/core/tests/unit_tests/test_tools.py

@@ -1863,3 +1863,41 @@ class ModelD(ModelC, Generic[D]):
     }
     actual = _get_all_basemodel_annotations(ModelD[int])
     assert actual == expected
+
+
+@pytest.mark.skipif(PYDANTIC_MAJOR_VERSION != 2, reason="Testing pydantic v2.")
+def test_tool_args_schema_pydantic_v2_with_metadata() -> None:
+    from pydantic import BaseModel as BaseModelV2  # pydantic: ignore
+    from pydantic import Field as FieldV2  # pydantic: ignore
+    from pydantic import ValidationError as ValidationErrorV2  # pydantic: ignore
+
+    class Foo(BaseModelV2):
+        x: List[int] = FieldV2(
+            description="List of integers", min_length=10, max_length=15
+        )
+
+    @tool(args_schema=Foo)
+    def foo(x):  # type: ignore[no-untyped-def]
+        """foo"""
+        return x
+
+    assert foo.tool_call_schema.schema() == {
+        "description": "foo",
+        "properties": {
+            "x": {
+                "description": "List of integers",
+                "items": {"type": "integer"},
+                "maxItems": 15,
+                "minItems": 10,
+                "title": "X",
+                "type": "array",
+            }
+        },
+        "required": ["x"],
+        "title": "foo",
+        "type": "object",
+    }
+
+    assert foo.invoke({"x": [0] * 10})
+    with pytest.raises(ValidationErrorV2):
+        foo.invoke({"x": [0] * 9})

libs/core/tests/unit_tests/utils/test_pydantic.py

@@ -1,10 +1,13 @@
 """Test for some custom pydantic decorators."""
 
-from typing import Any, Dict, Optional
+from typing import Any, Dict, List, Optional
+
+import pytest
 
 from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.utils.pydantic import (
     PYDANTIC_MAJOR_VERSION,
+    _create_subset_model_v2,
     is_basemodel_instance,
     is_basemodel_subclass,
     pre_init,
@@ -121,3 +124,32 @@ class Bar(BaseModelV1):
         assert is_basemodel_instance(Bar(x=5))
     else:
         raise ValueError(f"Unsupported Pydantic version: {PYDANTIC_MAJOR_VERSION}")
+
+
+@pytest.mark.skipif(PYDANTIC_MAJOR_VERSION != 2, reason="Only tests Pydantic v2")
+def test_with_field_metadata() -> None:
+    """Test pydantic with field metadata"""
+    from pydantic import BaseModel as BaseModelV2  # pydantic: ignore
+    from pydantic import Field as FieldV2  # pydantic: ignore
+
+    class Foo(BaseModelV2):
+        x: List[int] = FieldV2(
+            description="List of integers", min_length=10, max_length=15
+        )
+
+    subset_model = _create_subset_model_v2("Foo", Foo, ["x"])
+    assert subset_model.model_json_schema() == {
+        "properties": {
+            "x": {
+                "description": "List of integers",
+                "items": {"type": "integer"},
+                "maxItems": 15,
+                "minItems": 10,
+                "title": "X",
+                "type": "array",
+            }
+        },
+        "required": ["x"],
+        "title": "Foo",
+        "type": "object",
+    }

libs/standard-tests/langchain_standard_tests/integration_tests/chat_models.py

@@ -18,6 +18,8 @@
 from langchain_core.prompts import ChatPromptTemplate
 from langchain_core.pydantic_v1 import BaseModel, Field
 from langchain_core.tools import tool
+from pydantic import BaseModel as RawBaseModel
+from pydantic import Field as RawField
 
 from langchain_standard_tests.unit_tests.chat_models import (
     ChatModelTests,
@@ -26,7 +28,11 @@
 from langchain_standard_tests.utils.pydantic import PYDANTIC_MAJOR_VERSION
 
 
-@tool
+class MagicFunctionSchema(RawBaseModel):
+    input: int = RawField(..., gt=-1000, lt=1000)
+
+
+@tool(args_schema=MagicFunctionSchema)
 def magic_function(input: int) -> int:
     """Applies a magic function to an input."""
     return input + 2