removing langchain-core pydantic utilities

libs/langgraph/langgraph/utils/pydantic.py

@@ -1,10 +1,181 @@
 import sys
 import typing
+import warnings
+from contextlib import nullcontext
 from dataclasses import is_dataclass
-from typing import Any, Optional
+from functools import lru_cache
+from typing import (
+    Any,
+    Optional,
+    Union,
+    cast,
+    overload,
+)
 
-import typing_extensions
-from pydantic import BaseModel
+from pydantic import (
+    BaseModel,
+    ConfigDict,
+    Field,
+    RootModel,
+)
+from pydantic import (
+    create_model as _create_model_base,
+)
+from pydantic.fields import FieldInfo
+from pydantic.json_schema import (
+    DEFAULT_REF_TEMPLATE,
+    GenerateJsonSchema,
+    JsonSchemaMode,
+)
+from typing_extensions import TypedDict
+
+
+@overload
+def get_fields(model: type[BaseModel]) -> dict[str, FieldInfo]: ...
+
+
+@overload
+def get_fields(model: BaseModel) -> dict[str, FieldInfo]: ...
+
+
+def get_fields(
+    model: Union[type[BaseModel], BaseModel],
+) -> dict[str, FieldInfo]:
+    """Get the field names of a Pydantic model."""
+    if hasattr(model, "model_fields"):
+        return model.model_fields
+
+    if hasattr(model, "__fields__"):
+        return model.__fields__  # type: ignore[return-value]
+    msg = f"Expected a Pydantic model. Got {type(model)}"
+    raise TypeError(msg)
+
+
+_SchemaConfig = ConfigDict(
+    arbitrary_types_allowed=True, frozen=True, protected_namespaces=()
+)
+
+NO_DEFAULT = object()
+
+
+def _create_root_model(
+    name: str,
+    type_: Any,
+    module_name: Optional[str] = None,
+    default_: object = NO_DEFAULT,
+) -> type[BaseModel]:
+    """Create a base class."""
+
+    def schema(
+        cls: type[BaseModel],
+        by_alias: bool = True,  # noqa: FBT001,FBT002
+        ref_template: str = DEFAULT_REF_TEMPLATE,
+    ) -> dict[str, Any]:
+        # Complains about schema not being defined in superclass
+        schema_ = super(cls, cls).schema(  # type: ignore[misc]
+            by_alias=by_alias, ref_template=ref_template
+        )
+        schema_["title"] = name
+        return schema_
+
+    def model_json_schema(
+        cls: type[BaseModel],
+        by_alias: bool = True,  # noqa: FBT001,FBT002
+        ref_template: str = DEFAULT_REF_TEMPLATE,
+        schema_generator: type[GenerateJsonSchema] = GenerateJsonSchema,
+        mode: JsonSchemaMode = "validation",
+    ) -> dict[str, Any]:
+        # Complains about model_json_schema not being defined in superclass
+        schema_ = super(cls, cls).model_json_schema(  # type: ignore[misc]
+            by_alias=by_alias,
+            ref_template=ref_template,
+            schema_generator=schema_generator,
+            mode=mode,
+        )
+        schema_["title"] = name
+        return schema_
+
+    base_class_attributes = {
+        "__annotations__": {"root": type_},
+        "model_config": ConfigDict(arbitrary_types_allowed=True),
+        "schema": classmethod(schema),
+        "model_json_schema": classmethod(model_json_schema),
+        "__module__": module_name or "langchain_core.runnables.utils",
+    }
+
+    if default_ is not NO_DEFAULT:
+        base_class_attributes["root"] = default_
+    with warnings.catch_warnings():
+        custom_root_type = type(name, (RootModel,), base_class_attributes)
+    return cast("type[BaseModel]", custom_root_type)
+
+
+@lru_cache(maxsize=256)
+def _create_root_model_cached(
+    model_name: str,
+    type_: Any,
+    *,
+    module_name: Optional[str] = None,
+    default_: object = NO_DEFAULT,
+) -> type[BaseModel]:
+    return _create_root_model(
+        model_name, type_, default_=default_, module_name=module_name
+    )
+
+
+@lru_cache(maxsize=256)
+def _create_model_cached(
+    model_name: str,
+    /,
+    **field_definitions: Any,
+) -> type[BaseModel]:
+    return _create_model_base(
+        model_name,
+        __config__=_SchemaConfig,
+        **_remap_field_definitions(field_definitions),
+    )
+
+
+# Reserved names should capture all the `public` names / methods that are
+# used by BaseModel internally. This will keep the reserved names up-to-date.
+# For reference, the reserved names are:
+# "construct", "copy", "dict", "from_orm", "json", "parse_file", "parse_obj",
+# "parse_raw", "schema", "schema_json", "update_forward_refs", "validate",
+# "model_computed_fields", "model_config", "model_construct", "model_copy",
+# "model_dump", "model_dump_json", "model_extra", "model_fields",
+# "model_fields_set", "model_json_schema", "model_parametrized_name",
+# "model_post_init", "model_rebuild", "model_validate", "model_validate_json",
+# "model_validate_strings"
+_RESERVED_NAMES = {key for key in dir(BaseModel) if not key.startswith("_")}
+
+
+def _remap_field_definitions(field_definitions: dict[str, Any]) -> dict[str, Any]:
+    """This remaps fields to avoid colliding with internal pydantic fields."""
+
+    remapped = {}
+    for key, value in field_definitions.items():
+        if key.startswith("_") or key in _RESERVED_NAMES:
+            # Let's add a prefix to avoid colliding with internal pydantic fields
+            if isinstance(value, FieldInfo):
+                msg = (
+                    f"Remapping for fields starting with '_' or fields with a name "
+                    f"matching a reserved name {_RESERVED_NAMES} is not supported if "
+                    f" the field is a pydantic Field instance. Got {key}."
+                )
+                raise NotImplementedError(msg)
+            type_, default_ = value
+            remapped[f"private_{key}"] = (
+                type_,
+                Field(
+                    default=default_,
+                    alias=key,
+                    serialization_alias=key,
+                    title=key.lstrip("_").replace("_", " ").title(),
+                ),
+            )
+        else:
+            remapped[key] = value
+    return remapped
 
 
 def create_model(
@@ -15,19 +186,67 @@ def create_model(
 ) -> type[BaseModel]:
     """Create a pydantic model with the given field definitions.
 
+    Attention:
+        Please do not use outside of langchain packages. This API
+        is subject to change at any time.
+
     Args:
         model_name: The name of the model.
+        module_name: The name of the module where the model is defined.
+            This is used by Pydantic to resolve any forward references.
         field_definitions: The field definitions for the model.
         root: Type for a root model (RootModel)
-    """
-    # for langchain-core >= 0.3.0
-    from langchain_core.utils.pydantic import create_model_v2
 
-    return create_model_v2(
-        model_name,
-        field_definitions=field_definitions,
-        root=root,
-    )
+    Returns:
+        Type[BaseModel]: The created model.
+    """
+    field_definitions = field_definitions or {}
+
+    if root:
+        if field_definitions:
+            msg = (
+                "When specifying __root__ no other "
+                f"fields should be provided. Got {field_definitions}"
+            )
+            raise NotImplementedError(msg)
+
+        if isinstance(root, tuple):
+            kwargs = {"type_": root[0], "default_": root[1]}
+        else:
+            kwargs = {"type_": root}
+
+        try:
+            named_root_model = _create_root_model_cached(model_name, **kwargs)
+        except TypeError:
+            # something in the arguments into _create_root_model_cached is not hashable
+            named_root_model = _create_root_model(
+                model_name,
+                **kwargs,
+            )
+        return named_root_model
+
+    # No root, just field definitions
+    names = set(field_definitions.keys())
+
+    capture_warnings = False
+
+    for name in names:
+        # Also if any non-reserved name is used (e.g., model_id or model_name)
+        if name.startswith("model"):
+            capture_warnings = True
+
+    with warnings.catch_warnings() if capture_warnings else nullcontext():
+        if capture_warnings:
+            warnings.filterwarnings(action="ignore")
+        try:
+            return _create_model_cached(model_name, **field_definitions)
+        except TypeError:
+            # something in field definitions is not hashable
+            return _create_model_base(
+                model_name,
+                __config__=_SchemaConfig,
+                **_remap_field_definitions(field_definitions),
+            )
 
 
 def is_supported_by_pydantic(type_: Any) -> bool:
@@ -45,7 +264,7 @@ def is_supported_by_pydantic(type_: Any) -> bool:
 
     if hasattr(type_, "__orig_bases__"):
         for base in type_.__orig_bases__:
-            if base is typing_extensions.TypedDict:
+            if base is TypedDict:
                 return True
             elif base is typing.TypedDict:  # noqa: TID251
                 # ignoring TID251 since it's OK to use typing.TypedDict in this case.

libs/langgraph/poetry.lock

@@ -26,7 +26,6 @@ description = "Reusable constraint types to use with typing.Annotated"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
-markers = "python_version < \"4.0\""
 files = [
     {file = "annotated_types-0.7.0-py3-none-any.whl", hash = "sha256:1f02e8b43a8fbbc3f3e0d4f0f4bfc8131bcb4eebe8849b8e5c773f3a1c582a53"},
     {file = "annotated_types-0.7.0.tar.gz", hash = "sha256:aff07c09a53a08bc8cfccb9c85b05f1aa9a2a6f23728d790723543408344ce89"},
@@ -2270,7 +2269,6 @@ description = "Data validation using Python type hints"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
-markers = "python_version < \"4.0\""
 files = [
     {file = "pydantic-2.9.2-py3-none-any.whl", hash = "sha256:f048cec7b26778210e28a0459867920654d48e5e62db0958433636cde4254f12"},
     {file = "pydantic-2.9.2.tar.gz", hash = "sha256:d155cef71265d1e9807ed1c32b4c8deec042a44a50a4188b25ac67ecd81a9c0f"},
@@ -2295,7 +2293,6 @@ description = "Core functionality for Pydantic validation and serialization"
 optional = false
 python-versions = ">=3.8"
 groups = ["main", "dev"]
-markers = "python_version < \"4.0\""
 files = [
     {file = "pydantic_core-2.23.4-cp310-cp310-macosx_10_12_x86_64.whl", hash = "sha256:b10bd51f823d891193d4717448fab065733958bdb6a6b351967bd349d48d5c9b"},
     {file = "pydantic_core-2.23.4-cp310-cp310-macosx_11_0_arm64.whl", hash = "sha256:4fc714bdbfb534f94034efaa6eadd74e5b93c8fa6315565a222f7b6f42ca1166"},
@@ -3306,7 +3303,6 @@ files = [
     {file = "typing_extensions-4.12.2-py3-none-any.whl", hash = "sha256:04e5ca0351e0f3f85c6853954072df659d0d13fac324d0072316b67d7794700d"},
     {file = "typing_extensions-4.12.2.tar.gz", hash = "sha256:1a7ead55c7e559dd4dee8856e3a88b41225abfe1ce8df57b7c13915fe121ffb8"},
 ]
-markers = {main = "python_version < \"4.0\""}
 
 [[package]]
 name = "tzdata"
@@ -3677,4 +3673,4 @@ type = ["pytest-mypy"]
 [metadata]
 lock-version = "2.1"
 python-versions = ">=3.9"
-content-hash = "0e0c3fc2d5a5348c8df102497c7221a1f052f37a788b315eb82dfc7d63423e17"
+content-hash = "770dcaa5816fffb667b5e3639c0ee5add24df0a99bb9a89a6d8fb2c4a79fb185"

libs/langgraph/pyproject.toml

@@ -14,6 +14,7 @@ langgraph-checkpoint = "^2.0.10"
 langgraph-sdk = { version = ">=0.1.42", python = "<4.0" }
 langgraph-prebuilt = { version = ">=0.1.8", python = "<4.0" }
 xxhash = "^3.5.0"
+pydantic = { version = ">=2.7.4"}
 
 [tool.poetry.group.dev.dependencies]
 pytest = "^8.3.2"