fix(core): avoid dict shadowing in language models (#38480)

Fixes #37835

---

When Pydantic collects fields for a `BaseLanguageModel` subclass that
defines a `dict()` method, inherited annotations can resolve `dict`
against the subclass namespace instead of the builtin. With Pydantic
2.14.0a1 this caused `BaseLanguageModel.metadata: dict[str, Any] | None`
to fail during rebuild/import with `'function' object is not
subscriptable`.

This qualifies the inherited `metadata` field annotation as
`builtins.dict[...]`, matching the existing pattern in chat models, and
documents why the runtime import cannot move behind `TYPE_CHECKING`. It
also adds a regression test that rebuilds a `BaseLanguageModel` subclass
with a `dict()` method so core catches this failure before partner
packages hit it at import time.

Related to #37924, which hardens `_create_subset_model_v2`; this PR
fixes the `BaseLanguageModel` class-construction failure directly.

libs/core/langchain_core/language_models/base.py

@@ -2,6 +2,7 @@
 
 from __future__ import annotations
 
+import builtins  # noqa: TC003  # runtime-evaluated; subclass `dict()` shadows the builtin
 import warnings
 from abc import ABC, abstractmethod
 from collections.abc import Callable, Mapping, Sequence
@@ -191,7 +192,7 @@ class BaseLanguageModel(
     tags: list[str] | None = Field(default=None, exclude=True)
     """Tags to add to the run trace."""
 
-    metadata: dict[str, Any] | None = Field(default=None, exclude=True)
+    metadata: builtins.dict[str, Any] | None = Field(default=None, exclude=True)
     """Metadata to add to the run trace."""
 
     custom_get_token_ids: Callable[[str], list[int]] | None = Field(

libs/core/langchain_core/language_models/chat_models.py

@@ -3,7 +3,7 @@
 from __future__ import annotations
 
 import asyncio
-import builtins  # noqa: TC003
+import builtins  # noqa: TC003  # runtime-evaluated; subclass `dict()` shadows the builtin
 import contextlib
 import inspect
 import json

libs/core/tests/unit_tests/language_models/test_imports.py

@@ -1,4 +1,9 @@
-from langchain_core.language_models import __all__
+from typing import Any
+
+from langchain_core.callbacks import Callbacks
+from langchain_core.language_models import BaseLanguageModel, __all__
+from langchain_core.outputs import LLMResult
+from langchain_core.prompt_values import PromptValue
 
 EXPECTED_ALL = [
     "BaseLanguageModel",
@@ -26,3 +31,41 @@ EXPECTED_ALL = [
 
 def test_all_imports() -> None:
     assert set(__all__) == set(EXPECTED_ALL)
+
+
+def test_pydantic_rebuild_handles_subclass_dict_method_shadowing_builtin() -> None:
+    """Regression for Pydantic field collection with subclasses that define `dict()`.
+
+    Pydantic 2.14.0a1 evaluates inherited field annotations during subclass
+    rebuilds. If `BaseLanguageModel.metadata` uses a plain `dict[...]`
+    annotation, the subclass `dict()` method can shadow the builtin and make
+    annotation evaluation fail with `'function' object is not subscriptable`.
+    """
+
+    class DictMethodLanguageModel(BaseLanguageModel[str]):
+        name: str = "test"
+
+        def generate_prompt(
+            self,
+            prompts: list[PromptValue],
+            stop: list[str] | None = None,
+            callbacks: Callbacks = None,
+            **kwargs: Any,
+        ) -> LLMResult:
+            raise NotImplementedError
+
+        async def agenerate_prompt(
+            self,
+            prompts: list[PromptValue],
+            stop: list[str] | None = None,
+            callbacks: Callbacks = None,
+            **kwargs: Any,
+        ) -> LLMResult:
+            raise NotImplementedError
+
+        def dict(self, **_kwargs: Any) -> dict[str, Any]:
+            return {}
+
+    DictMethodLanguageModel.model_rebuild(force=True)
+
+    assert "metadata" in DictMethodLanguageModel.model_fields