core: Add N(naming) ruff rules (#25362)

Public classes/functions are not renamed and rule is ignored for them.

Co-authored-by: Erick Friis <erick@langchain.dev>

libs/core/langchain_core/_api/beta_decorator.py

@@ -155,7 +155,7 @@ def beta(
             _name = _name or obj.fget.__qualname__
             old_doc = obj.__doc__
 
-            class _beta_property(property):
+            class _BetaProperty(property):
                 """A beta property."""
 
                 def __init__(self, fget=None, fset=None, fdel=None, doc=None):
@@ -186,7 +186,7 @@ def beta(
 
             def finalize(wrapper: Callable[..., Any], new_doc: str) -> Any:
                 """Finalize the property."""
-                return _beta_property(
+                return _BetaProperty(
                     fget=obj.fget, fset=obj.fset, fdel=obj.fdel, doc=new_doc
                 )
 

libs/core/langchain_core/_api/deprecation.py

@@ -264,7 +264,7 @@ def deprecated(
             _name = _name or cast(Union[type, Callable], obj.fget).__qualname__
             old_doc = obj.__doc__
 
-            class _deprecated_property(property):
+            class _DeprecatedProperty(property):
                 """A deprecated property."""
 
                 def __init__(self, fget=None, fset=None, fdel=None, doc=None):  # type: ignore[no-untyped-def]
@@ -297,7 +297,7 @@ def deprecated(
                 """Finalize the property."""
                 return cast(
                     T,
-                    _deprecated_property(
+                    _DeprecatedProperty(
                         fget=obj.fget, fset=obj.fset, fdel=obj.fdel, doc=new_doc
                     ),
                 )

libs/core/langchain_core/exceptions.py

@@ -3,7 +3,7 @@
 from typing import Any, Optional
 
 
-class LangChainException(Exception):
+class LangChainException(Exception):  # noqa: N818
     """General LangChain exception."""
 
 
@@ -11,7 +11,7 @@ class TracerException(LangChainException):
     """Base class for exceptions in tracers module."""
 
 
-class OutputParserException(ValueError, LangChainException):
+class OutputParserException(ValueError, LangChainException):  # noqa: N818
     """Exception that output parsers should raise to signify a parsing error.
 
     This exists to differentiate parsing errors from other code or execution errors

libs/core/langchain_core/language_models/base.py

@@ -14,7 +14,7 @@ from typing import (
 )
 
 from pydantic import BaseModel, ConfigDict, Field, field_validator
-from typing_extensions import TypeAlias, TypedDict
+from typing_extensions import TypeAlias, TypedDict, override
 
 from langchain_core._api import deprecated
 from langchain_core.messages import (
@@ -143,6 +143,7 @@ class BaseLanguageModel(
             return verbose
 
     @property
+    @override
     def InputType(self) -> TypeAlias:
         """Get the input type for this runnable."""
         from langchain_core.prompt_values import (

libs/core/langchain_core/language_models/chat_models.py

@@ -26,6 +26,7 @@ from pydantic import (
     Field,
     model_validator,
 )
+from typing_extensions import override
 
 from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
@@ -251,6 +252,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
     # --- Runnable methods ---
 
     @property
+    @override
     def OutputType(self) -> Any:
         """Get the output type for this runnable."""
         return AnyMessage

libs/core/langchain_core/language_models/llms.py

@@ -31,6 +31,7 @@ from tenacity import (
     stop_after_attempt,
     wait_exponential,
 )
+from typing_extensions import override
 
 from langchain_core._api import deprecated
 from langchain_core.caches import BaseCache
@@ -318,6 +319,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
     # --- Runnable methods ---
 
     @property
+    @override
     def OutputType(self) -> type[str]:
         """Get the input type for this runnable."""
         return str

libs/core/langchain_core/output_parsers/base.py

@@ -10,6 +10,8 @@ from typing import (
     Union,
 )
 
+from typing_extensions import override
+
 from langchain_core.language_models import LanguageModelOutput
 from langchain_core.messages import AnyMessage, BaseMessage
 from langchain_core.outputs import ChatGeneration, Generation
@@ -63,11 +65,13 @@ class BaseGenerationOutputParser(
     """Base class to parse the output of an LLM call."""
 
     @property
+    @override
     def InputType(self) -> Any:
         """Return the input type for the parser."""
         return Union[str, AnyMessage]
 
     @property
+    @override
     def OutputType(self) -> type[T]:
         """Return the output type for the parser."""
         # even though mypy complains this isn't valid,
@@ -148,11 +152,13 @@ class BaseOutputParser(
     """  # noqa: E501
 
     @property
+    @override
     def InputType(self) -> Any:
         """Return the input type for the parser."""
         return Union[str, AnyMessage]
 
     @property
+    @override
     def OutputType(self) -> type[T]:
         """Return the output type for the parser.
 

libs/core/langchain_core/output_parsers/pydantic.py

@@ -3,6 +3,7 @@ from typing import Annotated, Generic, Optional
 
 import pydantic
 from pydantic import SkipValidation
+from typing_extensions import override
 
 from langchain_core.exceptions import OutputParserException
 from langchain_core.output_parsers import JsonOutputParser
@@ -107,6 +108,7 @@ class PydanticOutputParser(JsonOutputParser, Generic[TBaseModel]):
         return "pydantic"
 
     @property
+    @override
     def OutputType(self) -> type[TBaseModel]:
         """Return the pydantic model."""
         return self.pydantic_object

libs/core/langchain_core/output_parsers/xml.py

@@ -1,6 +1,6 @@
 import re
 import xml
-import xml.etree.ElementTree as ET
+import xml.etree.ElementTree as ET  # noqa: N817
 from collections.abc import AsyncIterator, Iterator
 from typing import Any, Literal, Optional, Union
 from xml.etree.ElementTree import TreeBuilder
@@ -46,14 +46,14 @@ class _StreamingParser:
         """
         if parser == "defusedxml":
             try:
-                from defusedxml import ElementTree as DET  # type: ignore
+                import defusedxml  # type: ignore
             except ImportError as e:
                 raise ImportError(
                     "defusedxml is not installed. "
                     "Please install it to use the defusedxml parser."
                     "You can install it with `pip install defusedxml` "
                 ) from e
-            _parser = DET.DefusedXMLParser(target=TreeBuilder())
+            _parser = defusedxml.ElementTree.DefusedXMLParser(target=TreeBuilder())
         else:
             _parser = None
         self.pull_parser = ET.XMLPullParser(["start", "end"], _parser=_parser)
@@ -189,7 +189,7 @@ class XMLOutputParser(BaseTransformOutputParser):
         # likely if you're reading this you can move them to the top of the file
         if self.parser == "defusedxml":
             try:
-                from defusedxml import ElementTree as DET  # type: ignore
+                import defusedxml  # type: ignore
             except ImportError as e:
                 raise ImportError(
                     "defusedxml is not installed. "
@@ -197,9 +197,9 @@ class XMLOutputParser(BaseTransformOutputParser):
                     "You can install it with `pip install defusedxml`"
                     "See https://github.com/tiran/defusedxml for more details"
                 ) from e
-            _ET = DET  # Use the defusedxml parser
+            _et = defusedxml.ElementTree  # Use the defusedxml parser
         else:
-            _ET = ET  # Use the standard library parser
+            _et = ET  # Use the standard library parser
 
         match = re.search(r"```(xml)?(.*)```", text, re.DOTALL)
         if match is not None:

libs/core/langchain_core/prompts/base.py

@@ -18,7 +18,7 @@ from typing import (
 
 import yaml
 from pydantic import BaseModel, ConfigDict, Field, model_validator
-from typing_extensions import Self
+from typing_extensions import Self, override
 
 from langchain_core.load import dumpd
 from langchain_core.output_parsers.base import BaseOutputParser
@@ -107,6 +107,7 @@ class BasePromptTemplate(
         return dumpd(self)
 
     @property
+    @override
     def OutputType(self) -> Any:
         """Return the output type of the prompt."""
         return Union[StringPromptValue, ChatPromptValueConcrete]

libs/core/langchain_core/runnables/base.py

@@ -36,7 +36,7 @@ from typing import (
 )
 
 from pydantic import BaseModel, ConfigDict, Field, RootModel
-from typing_extensions import Literal, get_args
+from typing_extensions import Literal, get_args, override
 
 from langchain_core._api import beta_decorator
 from langchain_core.load.serializable import (
@@ -272,7 +272,7 @@ class Runnable(Generic[Input, Output], ABC):
             return name_
 
     @property
-    def InputType(self) -> type[Input]:
+    def InputType(self) -> type[Input]:  # noqa: N802
         """The type of input this Runnable accepts specified as a type annotation."""
         # First loop through all parent classes and if any of them is
         # a pydantic model, we will pick up the generic parameterization
@@ -297,7 +297,7 @@ class Runnable(Generic[Input, Output], ABC):
         )
 
     @property
-    def OutputType(self) -> type[Output]:
+    def OutputType(self) -> type[Output]:  # noqa: N802
         """The type of output this Runnable produces specified as a type annotation."""
         # First loop through bases -- this will help generic
         # any pydantic models.
@@ -2811,11 +2811,13 @@ class RunnableSequence(RunnableSerializable[Input, Output]):
     )
 
     @property
+    @override
     def InputType(self) -> type[Input]:
         """The type of the input to the Runnable."""
         return self.first.InputType
 
     @property
+    @override
     def OutputType(self) -> type[Output]:
         """The type of the output of the Runnable."""
         return self.last.OutputType
@@ -3564,6 +3566,7 @@ class RunnableParallel(RunnableSerializable[Input, dict[str, Any]]):
         return super().get_name(suffix, name=name)
 
     @property
+    @override
     def InputType(self) -> Any:
         """The type of the input to the Runnable."""
         for step in self.steps__.values():
@@ -4057,6 +4060,7 @@ class RunnableGenerator(Runnable[Input, Output]):
             self.name = "RunnableGenerator"
 
     @property
+    @override
     def InputType(self) -> Any:
         func = getattr(self, "_transform", None) or self._atransform
         try:
@@ -4097,6 +4101,7 @@ class RunnableGenerator(Runnable[Input, Output]):
         )
 
     @property
+    @override
     def OutputType(self) -> Any:
         func = getattr(self, "_transform", None) or self._atransform
         try:
@@ -4346,6 +4351,7 @@ class RunnableLambda(Runnable[Input, Output]):
             pass
 
     @property
+    @override
     def InputType(self) -> Any:
         """The type of the input to this Runnable."""
         func = getattr(self, "func", None) or self.afunc
@@ -4405,6 +4411,7 @@ class RunnableLambda(Runnable[Input, Output]):
         return super().get_input_schema(config)
 
     @property
+    @override
     def OutputType(self) -> Any:
         """The type of the output of this Runnable as a type annotation.
 
@@ -4958,6 +4965,7 @@ class RunnableEachBase(RunnableSerializable[list[Input], list[Output]]):
     )
 
     @property
+    @override
     def InputType(self) -> Any:
         return list[self.bound.InputType]  # type: ignore[name-defined]
 
@@ -4981,6 +4989,7 @@ class RunnableEachBase(RunnableSerializable[list[Input], list[Output]]):
         )
 
     @property
+    @override
     def OutputType(self) -> type[list[Output]]:
         return list[self.bound.OutputType]  # type: ignore[name-defined]
 
@@ -5274,6 +5283,7 @@ class RunnableBindingBase(RunnableSerializable[Input, Output]):
         return self.bound.get_name(suffix, name=name)
 
     @property
+    @override
     def InputType(self) -> type[Input]:
         return (
             cast(type[Input], self.custom_input_type)
@@ -5282,6 +5292,7 @@ class RunnableBindingBase(RunnableSerializable[Input, Output]):
         )
 
     @property
+    @override
     def OutputType(self) -> type[Output]:
         return (
             cast(type[Output], self.custom_output_type)

libs/core/langchain_core/runnables/configurable.py

@@ -16,6 +16,7 @@ from typing import (
 from weakref import WeakValueDictionary
 
 from pydantic import BaseModel, ConfigDict
+from typing_extensions import override
 
 from langchain_core.runnables.base import Runnable, RunnableSerializable
 from langchain_core.runnables.config import (
@@ -68,10 +69,12 @@ class DynamicRunnable(RunnableSerializable[Input, Output]):
         return ["langchain", "schema", "runnable"]
 
     @property
+    @override
     def InputType(self) -> type[Input]:
         return self.default.InputType
 
     @property
+    @override
     def OutputType(self) -> type[Output]:
         return self.default.OutputType
 

libs/core/langchain_core/runnables/fallbacks.py

@@ -13,6 +13,7 @@ from typing import (
 )
 
 from pydantic import BaseModel, ConfigDict
+from typing_extensions import override
 
 from langchain_core.runnables.base import Runnable, RunnableSerializable
 from langchain_core.runnables.config import (
@@ -106,10 +107,12 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
     )
 
     @property
+    @override
     def InputType(self) -> type[Input]:
         return self.runnable.InputType
 
     @property
+    @override
     def OutputType(self) -> type[Output]:
         return self.runnable.OutputType
 

libs/core/langchain_core/runnables/graph_ascii.py

@@ -246,27 +246,27 @@ def draw_ascii(vertices: Mapping[str, str], edges: Sequence[LangEdge]) -> str:
 
     # NOTE: coordinates might me negative, so we need to shift
     # everything to the positive plane before we actually draw it.
-    Xs = []
+    xlist = []
-    Ys = []
+    ylist = []
 
     sug = _build_sugiyama_layout(vertices, edges)
 
     for vertex in sug.g.sV:
         # NOTE: moving boxes w/2 to the left
-        Xs.append(vertex.view.xy[0] - vertex.view.w / 2.0)
+        xlist.append(vertex.view.xy[0] - vertex.view.w / 2.0)
-        Xs.append(vertex.view.xy[0] + vertex.view.w / 2.0)
+        xlist.append(vertex.view.xy[0] + vertex.view.w / 2.0)
-        Ys.append(vertex.view.xy[1])
+        ylist.append(vertex.view.xy[1])
-        Ys.append(vertex.view.xy[1] + vertex.view.h)
+        ylist.append(vertex.view.xy[1] + vertex.view.h)
 
     for edge in sug.g.sE:
         for x, y in edge.view._pts:
-            Xs.append(x)
+            xlist.append(x)
-            Ys.append(y)
+            ylist.append(y)
 
-    minx = min(Xs)
+    minx = min(xlist)
-    miny = min(Ys)
+    miny = min(ylist)
-    maxx = max(Xs)
+    maxx = max(xlist)
-    maxy = max(Ys)
+    maxy = max(ylist)
 
     canvas_cols = int(math.ceil(math.ceil(maxx) - math.floor(minx))) + 1
     canvas_lines = int(round(maxy - miny))

libs/core/langchain_core/runnables/history.py

@@ -12,6 +12,7 @@ from typing import (
 )
 
 from pydantic import BaseModel
+from typing_extensions import override
 
 from langchain_core.chat_history import BaseChatMessageHistory
 from langchain_core.load.load import load
@@ -396,6 +397,7 @@ class RunnableWithMessageHistory(RunnableBindingBase):
         )
 
     @property
+    @override
     def OutputType(self) -> type[Output]:
         output_type = self._history_chain.OutputType
         return output_type

libs/core/langchain_core/runnables/passthrough.py

@@ -16,6 +16,7 @@ from typing import (
 )
 
 from pydantic import BaseModel, RootModel
+from typing_extensions import override
 
 from langchain_core.runnables.base import (
     Other,
@@ -193,10 +194,12 @@ class RunnablePassthrough(RunnableSerializable[Other, Other]):
         return ["langchain", "schema", "runnable"]
 
     @property
+    @override
     def InputType(self) -> Any:
         return self.input_type or Any
 
     @property
+    @override
     def OutputType(self) -> Any:
         return self.input_type or Any
 

libs/core/langchain_core/runnables/utils.py

@@ -28,7 +28,7 @@ from typing import (
     Union,
 )
 
-from typing_extensions import TypeGuard
+from typing_extensions import TypeGuard, override
 
 from langchain_core.runnables.schema import StreamEvent
 
@@ -135,6 +135,7 @@ class IsLocalDict(ast.NodeVisitor):
         self.name = name
         self.keys = keys
 
+    @override
     def visit_Subscript(self, node: ast.Subscript) -> Any:
         """Visit a subscript node.
 
@@ -154,6 +155,7 @@ class IsLocalDict(ast.NodeVisitor):
             # we've found a subscript access on the name we're looking for
             self.keys.add(node.slice.value)
 
+    @override
     def visit_Call(self, node: ast.Call) -> Any:
         """Visit a call node.
 
@@ -182,6 +184,7 @@ class IsFunctionArgDict(ast.NodeVisitor):
     def __init__(self) -> None:
         self.keys: set[str] = set()
 
+    @override
     def visit_Lambda(self, node: ast.Lambda) -> Any:
         """Visit a lambda function.
 
@@ -196,6 +199,7 @@ class IsFunctionArgDict(ast.NodeVisitor):
         input_arg_name = node.args.args[0].arg
         IsLocalDict(input_arg_name, self.keys).visit(node.body)
 
+    @override
     def visit_FunctionDef(self, node: ast.FunctionDef) -> Any:
         """Visit a function definition.
 
@@ -210,6 +214,7 @@ class IsFunctionArgDict(ast.NodeVisitor):
         input_arg_name = node.args.args[0].arg
         IsLocalDict(input_arg_name, self.keys).visit(node)
 
+    @override
     def visit_AsyncFunctionDef(self, node: ast.AsyncFunctionDef) -> Any:
         """Visit an async function definition.
 
@@ -232,6 +237,7 @@ class NonLocals(ast.NodeVisitor):
         self.loads: set[str] = set()
         self.stores: set[str] = set()
 
+    @override
     def visit_Name(self, node: ast.Name) -> Any:
         """Visit a name node.
 
@@ -246,6 +252,7 @@ class NonLocals(ast.NodeVisitor):
         elif isinstance(node.ctx, ast.Store):
             self.stores.add(node.id)
 
+    @override
     def visit_Attribute(self, node: ast.Attribute) -> Any:
         """Visit an attribute node.
 
@@ -272,6 +279,7 @@ class FunctionNonLocals(ast.NodeVisitor):
     def __init__(self) -> None:
         self.nonlocals: set[str] = set()
 
+    @override
     def visit_FunctionDef(self, node: ast.FunctionDef) -> Any:
         """Visit a function definition.
 
@@ -285,6 +293,7 @@ class FunctionNonLocals(ast.NodeVisitor):
         visitor.visit(node)
         self.nonlocals.update(visitor.loads - visitor.stores)
 
+    @override
     def visit_AsyncFunctionDef(self, node: ast.AsyncFunctionDef) -> Any:
         """Visit an async function definition.
 
@@ -298,6 +307,7 @@ class FunctionNonLocals(ast.NodeVisitor):
         visitor.visit(node)
         self.nonlocals.update(visitor.loads - visitor.stores)
 
+    @override
     def visit_Lambda(self, node: ast.Lambda) -> Any:
         """Visit a lambda function.
 
@@ -320,6 +330,7 @@ class GetLambdaSource(ast.NodeVisitor):
         self.source: Optional[str] = None
         self.count = 0
 
+    @override
     def visit_Lambda(self, node: ast.Lambda) -> Any:
         """Visit a lambda function.
 

libs/core/langchain_core/tools/base.py

@@ -311,7 +311,7 @@ def create_schema_from_function(
     )
 
 
-class ToolException(Exception):
+class ToolException(Exception):  # noqa: N818
     """Optional exception that tool throws when execution error occurs.
 
     When this exception is thrown, the agent will not stop working,

libs/core/langchain_core/tracers/langchain_v1.py

@@ -9,7 +9,7 @@ def get_headers(*args: Any, **kwargs: Any) -> Any:
     )
 
 
-def LangChainTracerV1(*args: Any, **kwargs: Any) -> Any:
+def LangChainTracerV1(*args: Any, **kwargs: Any) -> Any:  # noqa: N802
     """Throw an error because this has been replaced by LangChainTracer."""
     raise RuntimeError(
         "LangChainTracerV1 is no longer supported. Please use LangChainTracer instead."

libs/core/langchain_core/tracers/schemas.py

@@ -18,7 +18,7 @@ from langchain_core._api import deprecated
 
 
 @deprecated("0.1.0", alternative="Use string instead.", removal="1.0")
-def RunTypeEnum() -> type[RunTypeEnumDep]:
+def RunTypeEnum() -> type[RunTypeEnumDep]:  # noqa: N802
     """RunTypeEnum."""
     warnings.warn(
         "RunTypeEnum is deprecated. Please directly use a string instead"

libs/core/langchain_core/utils/aiter.py

@@ -235,7 +235,7 @@ class Tee(Generic[T]):
 atee = Tee
 
 
-class aclosing(AbstractAsyncContextManager):
+class aclosing(AbstractAsyncContextManager):  # noqa: N801
     """Async context manager for safely finalizing an asynchronously cleaned-up
     resource such as an async generator, calling its ``aclose()`` method.
 

libs/core/langchain_core/vectorstores/utils.py

@@ -17,12 +17,12 @@ if TYPE_CHECKING:
 logger = logging.getLogger(__name__)
 
 
-def _cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray:
+def _cosine_similarity(x: Matrix, y: Matrix) -> np.ndarray:
     """Row-wise cosine similarity between two equal-width matrices.
 
     Args:
-        X: A matrix of shape (n, m).
+        x: A matrix of shape (n, m).
-        Y: A matrix of shape (k, m).
+        y: A matrix of shape (k, m).
 
     Returns:
         A matrix of shape (n, k) where each element (i, j) is the cosine similarity
@@ -40,33 +40,33 @@ def _cosine_similarity(X: Matrix, Y: Matrix) -> np.ndarray:
             "Please install numpy with `pip install numpy`."
         ) from e
 
-    if len(X) == 0 or len(Y) == 0:
+    if len(x) == 0 or len(y) == 0:
         return np.array([])
 
-    X = np.array(X)
+    x = np.array(x)
-    Y = np.array(Y)
+    y = np.array(y)
-    if X.shape[1] != Y.shape[1]:
+    if x.shape[1] != y.shape[1]:
         raise ValueError(
-            f"Number of columns in X and Y must be the same. X has shape {X.shape} "
+            f"Number of columns in X and Y must be the same. X has shape {x.shape} "
-            f"and Y has shape {Y.shape}."
+            f"and Y has shape {y.shape}."
         )
     try:
         import simsimd as simd  # type: ignore[import-not-found]
 
-        X = np.array(X, dtype=np.float32)
+        x = np.array(x, dtype=np.float32)
-        Y = np.array(Y, dtype=np.float32)
+        y = np.array(y, dtype=np.float32)
-        Z = 1 - np.array(simd.cdist(X, Y, metric="cosine"))
+        z = 1 - np.array(simd.cdist(x, y, metric="cosine"))
-        return Z
+        return z
     except ImportError:
         logger.debug(
             "Unable to import simsimd, defaulting to NumPy implementation. If you want "
             "to use simsimd please install with `pip install simsimd`."
         )
-        X_norm = np.linalg.norm(X, axis=1)
+        x_norm = np.linalg.norm(x, axis=1)
-        Y_norm = np.linalg.norm(Y, axis=1)
+        y_norm = np.linalg.norm(y, axis=1)
         # Ignore divide by zero errors run time warnings as those are handled below.
         with np.errstate(divide="ignore", invalid="ignore"):
-            similarity = np.dot(X, Y.T) / np.outer(X_norm, Y_norm)
+            similarity = np.dot(x, y.T) / np.outer(x_norm, y_norm)
         similarity[np.isnan(similarity) | np.isinf(similarity)] = 0.0
         return similarity
 

libs/core/pyproject.toml

@@ -44,9 +44,17 @@ python = ">=3.12.4"
 target-version = "py39"
 
 [tool.ruff.lint]
-select = ["B", "E", "F", "I", "T201", "UP"]
+select = ["B", "E", "F", "I", "N", "T201", "UP"]
 ignore = ["UP007"]
 
+[tool.ruff.lint.pep8-naming]
+classmethod-decorators = [
+    "classmethod",
+    "langchain_core.utils.pydantic.pre_init",
+    "pydantic.field_validator",
+    "pydantic.v1.root_validator",
+]
+
 [tool.coverage.run]
 omit = [ "tests/*",]
 

libs/core/tests/unit_tests/fake/test_fake_chat_model.py

@@ -9,9 +9,9 @@ from langchain_core.language_models import GenericFakeChatModel, ParrotFakeChatM
 from langchain_core.messages import AIMessage, AIMessageChunk, BaseMessage
 from langchain_core.outputs import ChatGenerationChunk, GenerationChunk
 from tests.unit_tests.stubs import (
-    _AnyIdAIMessage,
+    _any_id_ai_message,
-    _AnyIdAIMessageChunk,
+    _any_id_ai_message_chunk,
-    _AnyIdHumanMessage,
+    _any_id_human_message,
 )
 
 
@@ -20,11 +20,11 @@ def test_generic_fake_chat_model_invoke() -> None:
     infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
     model = GenericFakeChatModel(messages=infinite_cycle)
     response = model.invoke("meow")
-    assert response == _AnyIdAIMessage(content="hello")
+    assert response == _any_id_ai_message(content="hello")
     response = model.invoke("kitty")
-    assert response == _AnyIdAIMessage(content="goodbye")
+    assert response == _any_id_ai_message(content="goodbye")
     response = model.invoke("meow")
-    assert response == _AnyIdAIMessage(content="hello")
+    assert response == _any_id_ai_message(content="hello")
 
 
 async def test_generic_fake_chat_model_ainvoke() -> None:
@@ -32,11 +32,11 @@ async def test_generic_fake_chat_model_ainvoke() -> None:
     infinite_cycle = cycle([AIMessage(content="hello"), AIMessage(content="goodbye")])
     model = GenericFakeChatModel(messages=infinite_cycle)
     response = await model.ainvoke("meow")
-    assert response == _AnyIdAIMessage(content="hello")
+    assert response == _any_id_ai_message(content="hello")
     response = await model.ainvoke("kitty")
-    assert response == _AnyIdAIMessage(content="goodbye")
+    assert response == _any_id_ai_message(content="goodbye")
     response = await model.ainvoke("meow")
-    assert response == _AnyIdAIMessage(content="hello")
+    assert response == _any_id_ai_message(content="hello")
 
 
 async def test_generic_fake_chat_model_stream() -> None:
@@ -49,17 +49,17 @@ async def test_generic_fake_chat_model_stream() -> None:
     model = GenericFakeChatModel(messages=infinite_cycle)
     chunks = [chunk async for chunk in model.astream("meow")]
     assert chunks == [
-        _AnyIdAIMessageChunk(content="hello"),
+        _any_id_ai_message_chunk(content="hello"),
-        _AnyIdAIMessageChunk(content=" "),
+        _any_id_ai_message_chunk(content=" "),
-        _AnyIdAIMessageChunk(content="goodbye"),
+        _any_id_ai_message_chunk(content="goodbye"),
     ]
     assert len({chunk.id for chunk in chunks}) == 1
 
     chunks = [chunk for chunk in model.stream("meow")]
     assert chunks == [
-        _AnyIdAIMessageChunk(content="hello"),
+        _any_id_ai_message_chunk(content="hello"),
-        _AnyIdAIMessageChunk(content=" "),
+        _any_id_ai_message_chunk(content=" "),
-        _AnyIdAIMessageChunk(content="goodbye"),
+        _any_id_ai_message_chunk(content="goodbye"),
     ]
     assert len({chunk.id for chunk in chunks}) == 1
 
@@ -69,8 +69,8 @@ async def test_generic_fake_chat_model_stream() -> None:
     model = GenericFakeChatModel(messages=cycle([message]))
     chunks = [chunk async for chunk in model.astream("meow")]
     assert chunks == [
-        _AnyIdAIMessageChunk(content="", additional_kwargs={"foo": 42}),
+        _any_id_ai_message_chunk(content="", additional_kwargs={"foo": 42}),
-        _AnyIdAIMessageChunk(content="", additional_kwargs={"bar": 24}),
+        _any_id_ai_message_chunk(content="", additional_kwargs={"bar": 24}),
     ]
     assert len({chunk.id for chunk in chunks}) == 1
 
@@ -88,19 +88,19 @@ async def test_generic_fake_chat_model_stream() -> None:
     chunks = [chunk async for chunk in model.astream("meow")]
 
     assert chunks == [
-        _AnyIdAIMessageChunk(
+        _any_id_ai_message_chunk(
             content="", additional_kwargs={"function_call": {"name": "move_file"}}
         ),
-        _AnyIdAIMessageChunk(
+        _any_id_ai_message_chunk(
             content="",
             additional_kwargs={
                 "function_call": {"arguments": '{\n  "source_path": "foo"'},
             },
         ),
-        _AnyIdAIMessageChunk(
+        _any_id_ai_message_chunk(
             content="", additional_kwargs={"function_call": {"arguments": ","}}
         ),
-        _AnyIdAIMessageChunk(
+        _any_id_ai_message_chunk(
             content="",
             additional_kwargs={
                 "function_call": {"arguments": '\n  "destination_path": "bar"\n}'},
@@ -138,9 +138,9 @@ async def test_generic_fake_chat_model_astream_log() -> None:
     ]
     final = log_patches[-1]
     assert final.state["streamed_output"] == [
-        _AnyIdAIMessageChunk(content="hello"),
+        _any_id_ai_message_chunk(content="hello"),
-        _AnyIdAIMessageChunk(content=" "),
+        _any_id_ai_message_chunk(content=" "),
-        _AnyIdAIMessageChunk(content="goodbye"),
+        _any_id_ai_message_chunk(content="goodbye"),
     ]
     assert len({chunk.id for chunk in final.state["streamed_output"]}) == 1
 
@@ -189,9 +189,9 @@ async def test_callback_handlers() -> None:
     # New model
     results = list(model.stream("meow", {"callbacks": [MyCustomAsyncHandler(tokens)]}))
     assert results == [
-        _AnyIdAIMessageChunk(content="hello"),
+        _any_id_ai_message_chunk(content="hello"),
-        _AnyIdAIMessageChunk(content=" "),
+        _any_id_ai_message_chunk(content=" "),
-        _AnyIdAIMessageChunk(content="goodbye"),
+        _any_id_ai_message_chunk(content="goodbye"),
     ]
     assert tokens == ["hello", " ", "goodbye"]
     assert len({chunk.id for chunk in results}) == 1
@@ -200,6 +200,8 @@ async def test_callback_handlers() -> None:
 def test_chat_model_inputs() -> None:
     fake = ParrotFakeChatModel()
 
-    assert fake.invoke("hello") == _AnyIdHumanMessage(content="hello")
+    assert fake.invoke("hello") == _any_id_human_message(content="hello")
-    assert fake.invoke([("ai", "blah")]) == _AnyIdAIMessage(content="blah")
+    assert fake.invoke([("ai", "blah")]) == _any_id_ai_message(content="blah")
-    assert fake.invoke([AIMessage(content="blah")]) == _AnyIdAIMessage(content="blah")
+    assert fake.invoke([AIMessage(content="blah")]) == _any_id_ai_message(
+        content="blah"
+    )

libs/core/tests/unit_tests/language_models/chat_models/test_base.py

@@ -27,7 +27,7 @@ from tests.unit_tests.fake.callbacks import (
     FakeAsyncCallbackHandler,
     FakeCallbackHandler,
 )
-from tests.unit_tests.stubs import _AnyIdAIMessage, _AnyIdAIMessageChunk
+from tests.unit_tests.stubs import _any_id_ai_message, _any_id_ai_message_chunk
 
 
 @pytest.fixture
@@ -147,10 +147,10 @@ async def test_astream_fallback_to_ainvoke() -> None:
 
     model = ModelWithGenerate()
     chunks = [chunk for chunk in model.stream("anything")]
-    assert chunks == [_AnyIdAIMessage(content="hello")]
+    assert chunks == [_any_id_ai_message(content="hello")]
 
     chunks = [chunk async for chunk in model.astream("anything")]
-    assert chunks == [_AnyIdAIMessage(content="hello")]
+    assert chunks == [_any_id_ai_message(content="hello")]
 
 
 async def test_astream_implementation_fallback_to_stream() -> None:
@@ -185,15 +185,15 @@ async def test_astream_implementation_fallback_to_stream() -> None:
     model = ModelWithSyncStream()
     chunks = [chunk for chunk in model.stream("anything")]
     assert chunks == [
-        _AnyIdAIMessageChunk(content="a"),
+        _any_id_ai_message_chunk(content="a"),
-        _AnyIdAIMessageChunk(content="b"),
+        _any_id_ai_message_chunk(content="b"),
     ]
     assert len({chunk.id for chunk in chunks}) == 1
     assert type(model)._astream == BaseChatModel._astream
     astream_chunks = [chunk async for chunk in model.astream("anything")]
     assert astream_chunks == [
-        _AnyIdAIMessageChunk(content="a"),
+        _any_id_ai_message_chunk(content="a"),
-        _AnyIdAIMessageChunk(content="b"),
+        _any_id_ai_message_chunk(content="b"),
     ]
     assert len({chunk.id for chunk in astream_chunks}) == 1
 
@@ -230,8 +230,8 @@ async def test_astream_implementation_uses_astream() -> None:
     model = ModelWithAsyncStream()
     chunks = [chunk async for chunk in model.astream("anything")]
     assert chunks == [
-        _AnyIdAIMessageChunk(content="a"),
+        _any_id_ai_message_chunk(content="a"),
-        _AnyIdAIMessageChunk(content="b"),
+        _any_id_ai_message_chunk(content="b"),
     ]
     assert len({chunk.id for chunk in chunks}) == 1
 

libs/core/tests/unit_tests/prompts/test_loading.py

@@ -25,7 +25,7 @@ def change_directory(dir: Path) -> Iterator:
         os.chdir(origin)
 
 
-def test_loading_from_YAML() -> None:
+def test_loading_from_yaml() -> None:
     """Test loading from yaml file."""
     prompt = load_prompt(EXAMPLE_DIR / "simple_prompt.yaml")
     expected_prompt = PromptTemplate(
@@ -36,7 +36,7 @@ def test_loading_from_YAML() -> None:
     assert prompt == expected_prompt
 
 
-def test_loading_from_JSON() -> None:
+def test_loading_from_json() -> None:
     """Test loading from json file."""
     prompt = load_prompt(EXAMPLE_DIR / "simple_prompt.json")
     expected_prompt = PromptTemplate(
@@ -46,14 +46,14 @@ def test_loading_from_JSON() -> None:
     assert prompt == expected_prompt
 
 
-def test_loading_jinja_from_JSON() -> None:
+def test_loading_jinja_from_json() -> None:
     """Test that loading jinja2 format prompts from JSON raises ValueError."""
     prompt_path = EXAMPLE_DIR / "jinja_injection_prompt.json"
     with pytest.raises(ValueError, match=".*can lead to arbitrary code execution.*"):
         load_prompt(prompt_path)
 
 
-def test_loading_jinja_from_YAML() -> None:
+def test_loading_jinja_from_yaml() -> None:
     """Test that loading jinja2 format prompts from YAML raises ValueError."""
     prompt_path = EXAMPLE_DIR / "jinja_injection_prompt.yaml"
     with pytest.raises(ValueError, match=".*can lead to arbitrary code execution.*"):

libs/core/tests/unit_tests/runnables/test_graph.py

@@ -2,6 +2,7 @@ from typing import Optional
 
 from pydantic import BaseModel
 from syrupy import SnapshotAssertion
+from typing_extensions import override
 
 from langchain_core.language_models import FakeListLLM
 from langchain_core.output_parsers.list import CommaSeparatedListOutputParser
@@ -353,9 +354,11 @@ def test_runnable_get_graph_with_invalid_input_type() -> None:
 
     class InvalidInputTypeRunnable(Runnable[int, int]):
         @property
+        @override
         def InputType(self) -> type:
             raise TypeError()
 
+        @override
         def invoke(
             self,
             input: int,
@@ -375,9 +378,11 @@ def test_runnable_get_graph_with_invalid_output_type() -> None:
 
     class InvalidOutputTypeRunnable(Runnable[int, int]):
         @property
+        @override
         def OutputType(self) -> type:
             raise TypeError()
 
+        @override
         def invoke(
             self,
             input: int,

libs/core/tests/unit_tests/runnables/test_history.py

@@ -493,7 +493,7 @@ def test_get_output_schema() -> None:
 def test_get_input_schema_input_messages() -> None:
     from pydantic import RootModel
 
-    RunnableWithMessageHistoryInput = RootModel[Sequence[BaseMessage]]
+    runnable_with_message_history_input = RootModel[Sequence[BaseMessage]]
 
     runnable = RunnableLambda(
         lambda messages: {
@@ -515,7 +515,7 @@ def test_get_input_schema_input_messages() -> None:
     with_history = RunnableWithMessageHistory(
         runnable, get_session_history, output_messages_key="output"
     )
-    expected_schema = _schema(RunnableWithMessageHistoryInput)
+    expected_schema = _schema(runnable_with_message_history_input)
     expected_schema["title"] = "RunnableWithChatHistoryInput"
     assert _schema(with_history.get_input_schema()) == expected_schema
 

libs/core/tests/unit_tests/runnables/test_runnable.py

@@ -87,7 +87,7 @@ from langchain_core.tracers import (
 )
 from langchain_core.tracers.context import collect_runs
 from tests.unit_tests.pydantic_utils import _normalize_schema, _schema
-from tests.unit_tests.stubs import AnyStr, _AnyIdAIMessage, _AnyIdAIMessageChunk
+from tests.unit_tests.stubs import AnyStr, _any_id_ai_message, _any_id_ai_message_chunk
 
 PYDANTIC_VERSION = tuple(map(int, pydantic.__version__.split(".")))
 
@@ -1699,7 +1699,7 @@ def test_prompt_with_chat_model(
     tracer = FakeTracer()
     assert chain.invoke(
         {"question": "What is your name?"}, dict(callbacks=[tracer])
-    ) == _AnyIdAIMessage(content="foo")
+    ) == _any_id_ai_message(content="foo")
     assert prompt_spy.call_args.args[1] == {"question": "What is your name?"}
     assert chat_spy.call_args.args[1] == ChatPromptValue(
         messages=[
@@ -1724,8 +1724,8 @@ def test_prompt_with_chat_model(
         ],
         dict(callbacks=[tracer]),
     ) == [
-        _AnyIdAIMessage(content="foo"),
+        _any_id_ai_message(content="foo"),
-        _AnyIdAIMessage(content="foo"),
+        _any_id_ai_message(content="foo"),
     ]
     assert prompt_spy.call_args.args[1] == [
         {"question": "What is your name?"},
@@ -1765,9 +1765,9 @@ def test_prompt_with_chat_model(
     assert [
         *chain.stream({"question": "What is your name?"}, dict(callbacks=[tracer]))
     ] == [
-        _AnyIdAIMessageChunk(content="f"),
+        _any_id_ai_message_chunk(content="f"),
-        _AnyIdAIMessageChunk(content="o"),
+        _any_id_ai_message_chunk(content="o"),
-        _AnyIdAIMessageChunk(content="o"),
+        _any_id_ai_message_chunk(content="o"),
     ]
     assert prompt_spy.call_args.args[1] == {"question": "What is your name?"}
     assert chat_spy.call_args.args[1] == ChatPromptValue(
@@ -1805,7 +1805,7 @@ async def test_prompt_with_chat_model_async(
     tracer = FakeTracer()
     assert await chain.ainvoke(
         {"question": "What is your name?"}, dict(callbacks=[tracer])
-    ) == _AnyIdAIMessage(content="foo")
+    ) == _any_id_ai_message(content="foo")
     assert prompt_spy.call_args.args[1] == {"question": "What is your name?"}
     assert chat_spy.call_args.args[1] == ChatPromptValue(
         messages=[
@@ -1830,8 +1830,8 @@ async def test_prompt_with_chat_model_async(
         ],
         dict(callbacks=[tracer]),
     ) == [
-        _AnyIdAIMessage(content="foo"),
+        _any_id_ai_message(content="foo"),
-        _AnyIdAIMessage(content="foo"),
+        _any_id_ai_message(content="foo"),
     ]
     assert prompt_spy.call_args.args[1] == [
         {"question": "What is your name?"},
@@ -1874,9 +1874,9 @@ async def test_prompt_with_chat_model_async(
             {"question": "What is your name?"}, dict(callbacks=[tracer])
         )
     ] == [
-        _AnyIdAIMessageChunk(content="f"),
+        _any_id_ai_message_chunk(content="f"),
-        _AnyIdAIMessageChunk(content="o"),
+        _any_id_ai_message_chunk(content="o"),
-        _AnyIdAIMessageChunk(content="o"),
+        _any_id_ai_message_chunk(content="o"),
     ]
     assert prompt_spy.call_args.args[1] == {"question": "What is your name?"}
     assert chat_spy.call_args.args[1] == ChatPromptValue(
@@ -2548,7 +2548,7 @@ def test_prompt_with_chat_model_and_parser(
             HumanMessage(content="What is your name?"),
         ]
     )
-    assert parser_spy.call_args.args[1] == _AnyIdAIMessage(content="foo, bar")
+    assert parser_spy.call_args.args[1] == _any_id_ai_message(content="foo, bar")
 
     assert tracer.runs == snapshot
 
@@ -2681,7 +2681,7 @@ Question:
             ),
         ]
     )
-    assert parser_spy.call_args.args[1] == _AnyIdAIMessage(content="foo, bar")
+    assert parser_spy.call_args.args[1] == _any_id_ai_message(content="foo, bar")
     assert len([r for r in tracer.runs if r.parent_run_id is None]) == 1
     parent_run = next(r for r in tracer.runs if r.parent_run_id is None)
     assert len(parent_run.child_runs) == 4
@@ -2727,7 +2727,7 @@ def test_seq_prompt_dict(mocker: MockerFixture, snapshot: SnapshotAssertion) ->
     assert chain.invoke(
         {"question": "What is your name?"}, dict(callbacks=[tracer])
     ) == {
-        "chat": _AnyIdAIMessage(content="i'm a chatbot"),
+        "chat": _any_id_ai_message(content="i'm a chatbot"),
         "llm": "i'm a textbot",
     }
     assert prompt_spy.call_args.args[1] == {"question": "What is your name?"}
@@ -2936,7 +2936,7 @@ def test_seq_prompt_map(mocker: MockerFixture, snapshot: SnapshotAssertion) -> N
     assert chain.invoke(
         {"question": "What is your name?"}, dict(callbacks=[tracer])
     ) == {
-        "chat": _AnyIdAIMessage(content="i'm a chatbot"),
+        "chat": _any_id_ai_message(content="i'm a chatbot"),
         "llm": "i'm a textbot",
         "passthrough": ChatPromptValue(
             messages=[
@@ -3000,7 +3000,7 @@ def test_map_stream() -> None:
     assert streamed_chunks[0] in [
         {"passthrough": prompt.invoke({"question": "What is your name?"})},
         {"llm": "i"},
-        {"chat": _AnyIdAIMessageChunk(content="i")},
+        {"chat": _any_id_ai_message_chunk(content="i")},
     ]
     assert len(streamed_chunks) == len(chat_res) + len(llm_res) + 1
     assert all(len(c.keys()) == 1 for c in streamed_chunks)
@@ -3059,11 +3059,11 @@ def test_map_stream() -> None:
 
     assert streamed_chunks[0] in [
         {"llm": "i"},
-        {"chat": _AnyIdAIMessageChunk(content="i")},
+        {"chat": _any_id_ai_message_chunk(content="i")},
     ]
     if not (  # TODO(Rewrite properly) statement above
         streamed_chunks[0] == {"llm": "i"}
-        or {"chat": _AnyIdAIMessageChunk(content="i")}
+        or {"chat": _any_id_ai_message_chunk(content="i")}
     ):
         raise AssertionError(f"Got an unexpected chunk: {streamed_chunks[0]}")
 
@@ -3108,7 +3108,7 @@ def test_map_stream_iterator_input() -> None:
     assert streamed_chunks[0] in [
         {"passthrough": "i"},
         {"llm": "i"},
-        {"chat": _AnyIdAIMessageChunk(content="i")},
+        {"chat": _any_id_ai_message_chunk(content="i")},
     ]
     assert len(streamed_chunks) == len(chat_res) + len(llm_res) + len(llm_res)
     assert all(len(c.keys()) == 1 for c in streamed_chunks)
@@ -3152,7 +3152,7 @@ async def test_map_astream() -> None:
     assert streamed_chunks[0] in [
         {"passthrough": prompt.invoke({"question": "What is your name?"})},
         {"llm": "i"},
-        {"chat": _AnyIdAIMessageChunk(content="i")},
+        {"chat": _any_id_ai_message_chunk(content="i")},
     ]
     assert len(streamed_chunks) == len(chat_res) + len(llm_res) + 1
     assert all(len(c.keys()) == 1 for c in streamed_chunks)

libs/core/tests/unit_tests/runnables/test_runnable_events_v1.py

@@ -32,7 +32,7 @@ from langchain_core.runnables import (
 from langchain_core.runnables.history import RunnableWithMessageHistory
 from langchain_core.runnables.schema import StreamEvent
 from langchain_core.tools import tool
-from tests.unit_tests.stubs import _AnyIdAIMessage, _AnyIdAIMessageChunk
+from tests.unit_tests.stubs import _any_id_ai_message, _any_id_ai_message_chunk
 
 
 def _with_nulled_run_id(events: Sequence[StreamEvent]) -> list[StreamEvent]:
@@ -503,7 +503,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {"a": "b"},
                 "name": "my_model",
@@ -512,7 +512,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {"a": "b"},
                 "name": "my_model",
@@ -521,7 +521,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {"a": "b"},
                 "name": "my_model",
@@ -530,7 +530,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"output": _AnyIdAIMessageChunk(content="hello world!")},
+                "data": {"output": _any_id_ai_message_chunk(content="hello world!")},
                 "event": "on_chat_model_end",
                 "metadata": {"a": "b"},
                 "name": "my_model",
@@ -575,7 +575,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -588,7 +588,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -601,7 +601,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -621,7 +621,9 @@ async def test_astream_events_from_model() -> None:
                             [
                                 {
                                     "generation_info": None,
-                                    "message": _AnyIdAIMessage(content="hello world!"),
+                                    "message": _any_id_ai_message(
+                                        content="hello world!"
+                                    ),
                                     "text": "hello world!",
                                     "type": "ChatGeneration",
                                 }
@@ -644,7 +646,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessage(content="hello world!")},
+                "data": {"chunk": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_stream",
                 "metadata": {},
                 "name": "i_dont_stream",
@@ -653,7 +655,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": [],
             },
             {
-                "data": {"output": _AnyIdAIMessage(content="hello world!")},
+                "data": {"output": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_end",
                 "metadata": {},
                 "name": "i_dont_stream",
@@ -698,7 +700,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -711,7 +713,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -724,7 +726,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -744,7 +746,9 @@ async def test_astream_events_from_model() -> None:
                             [
                                 {
                                     "generation_info": None,
-                                    "message": _AnyIdAIMessage(content="hello world!"),
+                                    "message": _any_id_ai_message(
+                                        content="hello world!"
+                                    ),
                                     "text": "hello world!",
                                     "type": "ChatGeneration",
                                 }
@@ -767,7 +771,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessage(content="hello world!")},
+                "data": {"chunk": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_stream",
                 "metadata": {},
                 "name": "ai_dont_stream",
@@ -776,7 +780,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": [],
             },
             {
-                "data": {"output": _AnyIdAIMessage(content="hello world!")},
+                "data": {"output": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_end",
                 "metadata": {},
                 "name": "ai_dont_stream",

libs/core/tests/unit_tests/runnables/test_runnable_events_v2.py

@@ -47,7 +47,7 @@ from langchain_core.utils.aiter import aclosing
 from tests.unit_tests.runnables.test_runnable_events_v1 import (
     _assert_events_equal_allow_superset_metadata,
 )
-from tests.unit_tests.stubs import _AnyIdAIMessage, _AnyIdAIMessageChunk
+from tests.unit_tests.stubs import _any_id_ai_message, _any_id_ai_message_chunk
 
 
 def _with_nulled_run_id(events: Sequence[StreamEvent]) -> list[StreamEvent]:
@@ -533,7 +533,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -546,7 +546,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -559,7 +559,7 @@ async def test_astream_events_from_model() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -573,7 +573,7 @@ async def test_astream_events_from_model() -> None:
             },
             {
                 "data": {
-                    "output": _AnyIdAIMessageChunk(content="hello world!"),
+                    "output": _any_id_ai_message_chunk(content="hello world!"),
                 },
                 "event": "on_chat_model_end",
                 "metadata": {
@@ -640,7 +640,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -653,7 +653,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -666,7 +666,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -681,7 +681,7 @@ async def test_astream_with_model_in_chain() -> None:
             {
                 "data": {
                     "input": {"messages": [[HumanMessage(content="hello")]]},
-                    "output": _AnyIdAIMessage(content="hello world!"),
+                    "output": _any_id_ai_message(content="hello world!"),
                 },
                 "event": "on_chat_model_end",
                 "metadata": {
@@ -695,7 +695,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessage(content="hello world!")},
+                "data": {"chunk": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_stream",
                 "metadata": {},
                 "name": "i_dont_stream",
@@ -704,7 +704,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": [],
             },
             {
-                "data": {"output": _AnyIdAIMessage(content="hello world!")},
+                "data": {"output": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_end",
                 "metadata": {},
                 "name": "i_dont_stream",
@@ -749,7 +749,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="hello")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="hello")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -762,7 +762,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content=" ")},
+                "data": {"chunk": _any_id_ai_message_chunk(content=" ")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -775,7 +775,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessageChunk(content="world!")},
+                "data": {"chunk": _any_id_ai_message_chunk(content="world!")},
                 "event": "on_chat_model_stream",
                 "metadata": {
                     "a": "b",
@@ -790,7 +790,7 @@ async def test_astream_with_model_in_chain() -> None:
             {
                 "data": {
                     "input": {"messages": [[HumanMessage(content="hello")]]},
-                    "output": _AnyIdAIMessage(content="hello world!"),
+                    "output": _any_id_ai_message(content="hello world!"),
                 },
                 "event": "on_chat_model_end",
                 "metadata": {
@@ -804,7 +804,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": ["my_model"],
             },
             {
-                "data": {"chunk": _AnyIdAIMessage(content="hello world!")},
+                "data": {"chunk": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_stream",
                 "metadata": {},
                 "name": "ai_dont_stream",
@@ -813,7 +813,7 @@ async def test_astream_with_model_in_chain() -> None:
                 "tags": [],
             },
             {
-                "data": {"output": _AnyIdAIMessage(content="hello world!")},
+                "data": {"output": _any_id_ai_message(content="hello world!")},
                 "event": "on_chain_end",
                 "metadata": {},
                 "name": "ai_dont_stream",

libs/core/tests/unit_tests/stubs.py

@@ -16,28 +16,28 @@ class AnyStr(str):
 # subclassed strings.
 
 
-def _AnyIdDocument(**kwargs: Any) -> Document:
+def _any_id_document(**kwargs: Any) -> Document:
     """Create a document with an id field."""
     message = Document(**kwargs)
     message.id = AnyStr()
     return message
 
 
-def _AnyIdAIMessage(**kwargs: Any) -> AIMessage:
+def _any_id_ai_message(**kwargs: Any) -> AIMessage:
     """Create ai message with an any id field."""
     message = AIMessage(**kwargs)
     message.id = AnyStr()
     return message
 
 
-def _AnyIdAIMessageChunk(**kwargs: Any) -> AIMessageChunk:
+def _any_id_ai_message_chunk(**kwargs: Any) -> AIMessageChunk:
     """Create ai message with an any id field."""
     message = AIMessageChunk(**kwargs)
     message.id = AnyStr()
     return message
 
 
-def _AnyIdHumanMessage(**kwargs: Any) -> HumanMessage:
+def _any_id_human_message(**kwargs: Any) -> HumanMessage:
     """Create a human with an any id field."""
     message = HumanMessage(**kwargs)
     message.id = AnyStr()

libs/core/tests/unit_tests/test_messages.py

@@ -781,7 +781,7 @@ def test_convert_to_messages() -> None:
 
 
 @pytest.mark.parametrize(
-    "MessageClass",
+    "message_class",
     [
         AIMessage,
         AIMessageChunk,
@@ -790,39 +790,39 @@ def test_convert_to_messages() -> None:
         SystemMessage,
     ],
 )
-def test_message_name(MessageClass: type) -> None:
+def test_message_name(message_class: type) -> None:
-    msg = MessageClass(content="foo", name="bar")
+    msg = message_class(content="foo", name="bar")
     assert msg.name == "bar"
 
-    msg2 = MessageClass(content="foo", name=None)
+    msg2 = message_class(content="foo", name=None)
     assert msg2.name is None
 
-    msg3 = MessageClass(content="foo")
+    msg3 = message_class(content="foo")
     assert msg3.name is None
 
 
 @pytest.mark.parametrize(
-    "MessageClass",
+    "message_class",
     [FunctionMessage, FunctionMessageChunk],
 )
-def test_message_name_function(MessageClass: type) -> None:
+def test_message_name_function(message_class: type) -> None:
     # functionmessage doesn't support name=None
-    msg = MessageClass(name="foo", content="bar")
+    msg = message_class(name="foo", content="bar")
     assert msg.name == "foo"
 
 
 @pytest.mark.parametrize(
-    "MessageClass",
+    "message_class",
     [ChatMessage, ChatMessageChunk],
 )
-def test_message_name_chat(MessageClass: type) -> None:
+def test_message_name_chat(message_class: type) -> None:
-    msg = MessageClass(content="foo", role="user", name="bar")
+    msg = message_class(content="foo", role="user", name="bar")
     assert msg.name == "bar"
 
-    msg2 = MessageClass(content="foo", role="user", name=None)
+    msg2 = message_class(content="foo", role="user", name=None)
     assert msg2.name is None
 
-    msg3 = MessageClass(content="foo", role="user")
+    msg3 = message_class(content="foo", role="user")
     assert msg3.name is None
 
 

libs/core/tests/unit_tests/test_pydantic_serde.py

@@ -51,14 +51,14 @@ def test_serde_any_message() -> None:
         ),
     ]
 
-    Model = RootModel[AnyMessage]
+    model = RootModel[AnyMessage]
 
     for lc_object in lc_objects:
         d = lc_object.model_dump()
         assert "type" in d, f"Missing key `type` for {type(lc_object)}"
-        obj1 = Model.model_validate(d)
+        obj1 = model.model_validate(d)
         assert type(obj1.root) is type(lc_object), f"failed for {type(lc_object)}"
 
     with pytest.raises((TypeError, ValidationError)):
         # Make sure that specifically validation error is raised
-        Model.model_validate({})
+        model.model_validate({})

libs/core/tests/unit_tests/test_tools.py

@@ -1421,7 +1421,7 @@ class InjectedTool(BaseTool):
         return y
 
 
-class fooSchema(BaseModel):
+class fooSchema(BaseModel):  # noqa: N801
     """foo."""
 
     x: int = Field(..., description="abc")
@@ -1568,14 +1568,14 @@ def test_tool_injected_arg() -> None:
 
 
 def test_tool_inherited_injected_arg() -> None:
-    class barSchema(BaseModel):
+    class BarSchema(BaseModel):
         """bar."""
 
         y: Annotated[str, "foobar comment", InjectedToolArg()] = Field(
             ..., description="123"
         )
 
-    class fooSchema(barSchema):
+    class FooSchema(BarSchema):
         """foo."""
 
         x: int = Field(..., description="abc")
@@ -1583,14 +1583,14 @@ def test_tool_inherited_injected_arg() -> None:
     class InheritedInjectedArgTool(BaseTool):
         name: str = "foo"
         description: str = "foo."
-        args_schema: type[BaseModel] = fooSchema
+        args_schema: type[BaseModel] = FooSchema
 
         def _run(self, x: int, y: str) -> Any:
             return y
 
     tool_ = InheritedInjectedArgTool()
     assert tool_.get_input_schema().model_json_schema() == {
-        "title": "fooSchema",  # Matches the title from the provided schema
+        "title": "FooSchema",  # Matches the title from the provided schema
         "description": "foo.",
         "type": "object",
         "properties": {
@@ -1877,15 +1877,15 @@ def test__get_all_basemodel_annotations_v2(use_v1_namespace: bool) -> None:
     A = TypeVar("A")
 
     if use_v1_namespace:
-        from pydantic.v1 import BaseModel as BM1
+        from pydantic.v1 import BaseModel as BaseModel1
 
-        class ModelA(BM1, Generic[A], extra="allow"):
+        class ModelA(BaseModel1, Generic[A], extra="allow"):
             a: A
     else:
-        from pydantic import BaseModel as BM2
+        from pydantic import BaseModel as BaseModel2
         from pydantic import ConfigDict
 
-        class ModelA(BM2, Generic[A]):  # type: ignore[no-redef]
+        class ModelA(BaseModel2, Generic[A]):  # type: ignore[no-redef]
             a: A
             model_config = ConfigDict(arbitrary_types_allowed=True, extra="allow")
 
@@ -2081,13 +2081,13 @@ def test_structured_tool_direct_init() -> None:
     def foo(bar: str) -> str:
         return bar
 
-    async def asyncFoo(bar: str) -> str:
+    async def async_foo(bar: str) -> str:
         return bar
 
-    class fooSchema(BaseModel):
+    class FooSchema(BaseModel):
         bar: str = Field(..., description="The bar")
 
-    tool = StructuredTool(name="foo", args_schema=fooSchema, coroutine=asyncFoo)
+    tool = StructuredTool(name="foo", args_schema=FooSchema, coroutine=async_foo)
 
     with pytest.raises(NotImplementedError):
         assert tool.invoke("hello") == "hello"

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

@@ -38,7 +38,7 @@ from langchain_core.utils.function_calling import (
 
 @pytest.fixture()
 def pydantic() -> type[BaseModel]:
-    class dummy_function(BaseModel):
+    class dummy_function(BaseModel):  # noqa: N801
         """dummy function"""
 
         arg1: int = Field(..., description="foo")
@@ -48,7 +48,7 @@ def pydantic() -> type[BaseModel]:
 
 
 @pytest.fixture()
-def Annotated_function() -> Callable:
+def annotated_function() -> Callable:
     def dummy_function(
         arg1: ExtensionsAnnotated[int, "foo"],
         arg2: ExtensionsAnnotated[Literal["bar", "baz"], "one of 'bar', 'baz'"],
@@ -118,7 +118,7 @@ def dummy_structured_tool() -> StructuredTool:
 
 @pytest.fixture()
 def dummy_pydantic() -> type[BaseModel]:
-    class dummy_function(BaseModel):
+    class dummy_function(BaseModel):  # noqa: N801
         """dummy function"""
 
         arg1: int = Field(..., description="foo")
@@ -129,7 +129,7 @@ def dummy_pydantic() -> type[BaseModel]:
 
 @pytest.fixture()
 def dummy_pydantic_v2() -> type[BaseModelV2Maybe]:
-    class dummy_function(BaseModelV2Maybe):
+    class dummy_function(BaseModelV2Maybe):  # noqa: N801
         """dummy function"""
 
         arg1: int = FieldV2Maybe(..., description="foo")
@@ -142,7 +142,7 @@ def dummy_pydantic_v2() -> type[BaseModelV2Maybe]:
 
 @pytest.fixture()
 def dummy_typing_typed_dict() -> type:
-    class dummy_function(TypingTypedDict):
+    class dummy_function(TypingTypedDict):  # noqa: N801
         """dummy function"""
 
         arg1: TypingAnnotated[int, ..., "foo"]  # noqa: F821
@@ -153,7 +153,7 @@ def dummy_typing_typed_dict() -> type:
 
 @pytest.fixture()
 def dummy_typing_typed_dict_docstring() -> type:
-    class dummy_function(TypingTypedDict):
+    class dummy_function(TypingTypedDict):  # noqa: N801
         """dummy function
 
         Args:
@@ -169,7 +169,7 @@ def dummy_typing_typed_dict_docstring() -> type:
 
 @pytest.fixture()
 def dummy_extensions_typed_dict() -> type:
-    class dummy_function(ExtensionsTypedDict):
+    class dummy_function(ExtensionsTypedDict):  # noqa: N801
         """dummy function"""
 
         arg1: ExtensionsAnnotated[int, ..., "foo"]
@@ -180,7 +180,7 @@ def dummy_extensions_typed_dict() -> type:
 
 @pytest.fixture()
 def dummy_extensions_typed_dict_docstring() -> type:
-    class dummy_function(ExtensionsTypedDict):
+    class dummy_function(ExtensionsTypedDict):  # noqa: N801
         """dummy function
 
         Args:
@@ -241,7 +241,7 @@ def test_convert_to_openai_function(
     dummy_structured_tool: StructuredTool,
     dummy_tool: BaseTool,
     json_schema: dict,
-    Annotated_function: Callable,
+    annotated_function: Callable,
     dummy_pydantic: type[BaseModel],
     runnable: Runnable,
     dummy_typing_typed_dict: type,
@@ -275,7 +275,7 @@ def test_convert_to_openai_function(
         expected,
         Dummy.dummy_function,
         DummyWithClassMethod.dummy_function,
-        Annotated_function,
+        annotated_function,
         dummy_pydantic,
         dummy_typing_typed_dict,
         dummy_typing_typed_dict_docstring,
@@ -523,20 +523,20 @@ def test__convert_typed_dict_to_openai_function(
     use_extension_typed_dict: bool, use_extension_annotated: bool
 ) -> None:
     if use_extension_typed_dict:
-        TypedDict = ExtensionsTypedDict
+        typed_dict = ExtensionsTypedDict
     else:
-        TypedDict = TypingTypedDict
+        typed_dict = TypingTypedDict
     if use_extension_annotated:
-        Annotated = TypingAnnotated
+        annotated = TypingAnnotated
     else:
-        Annotated = TypingAnnotated
+        annotated = TypingAnnotated
 
-    class SubTool(TypedDict):
+    class SubTool(typed_dict):
         """Subtool docstring"""
 
-        args: Annotated[dict[str, Any], {}, "this does bar"]  # noqa: F722  # type: ignore
+        args: annotated[dict[str, Any], {}, "this does bar"]  # noqa: F722  # type: ignore
 
-    class Tool(TypedDict):
+    class Tool(typed_dict):
         """Docstring
 
         Args:
@@ -546,20 +546,20 @@ def test__convert_typed_dict_to_openai_function(
         arg1: str
         arg2: Union[int, str, bool]
         arg3: Optional[list[SubTool]]
-        arg4: Annotated[Literal["bar", "baz"], ..., "this does foo"]  # noqa: F722
+        arg4: annotated[Literal["bar", "baz"], ..., "this does foo"]  # noqa: F722
-        arg5: Annotated[Optional[float], None]
+        arg5: annotated[Optional[float], None]
-        arg6: Annotated[
+        arg6: annotated[
             Optional[Sequence[Mapping[str, tuple[Iterable[Any], SubTool]]]], []
         ]
-        arg7: Annotated[list[SubTool], ...]
+        arg7: annotated[list[SubTool], ...]
-        arg8: Annotated[tuple[SubTool], ...]
+        arg8: annotated[tuple[SubTool], ...]
-        arg9: Annotated[Sequence[SubTool], ...]
+        arg9: annotated[Sequence[SubTool], ...]
-        arg10: Annotated[Iterable[SubTool], ...]
+        arg10: annotated[Iterable[SubTool], ...]
-        arg11: Annotated[set[SubTool], ...]
+        arg11: annotated[set[SubTool], ...]
-        arg12: Annotated[dict[str, SubTool], ...]
+        arg12: annotated[dict[str, SubTool], ...]
-        arg13: Annotated[Mapping[str, SubTool], ...]
+        arg13: annotated[Mapping[str, SubTool], ...]
-        arg14: Annotated[MutableMapping[str, SubTool], ...]
+        arg14: annotated[MutableMapping[str, SubTool], ...]
-        arg15: Annotated[bool, False, "flag"]  # noqa: F821  # type: ignore
+        arg15: annotated[bool, False, "flag"]  # noqa: F821  # type: ignore
 
     expected = {
         "name": "Tool",

libs/core/tests/unit_tests/vectorstores/test_in_memory.py

@@ -10,7 +10,7 @@ from langchain_standard_tests.integration_tests.vectorstores import (
 from langchain_core.documents import Document
 from langchain_core.embeddings.fake import DeterministicFakeEmbedding
 from langchain_core.vectorstores import InMemoryVectorStore
-from tests.unit_tests.stubs import _AnyIdDocument
+from tests.unit_tests.stubs import _any_id_document
 
 
 class TestInMemoryReadWriteTestSuite(ReadWriteTestSuite):
@@ -33,13 +33,13 @@ async def test_inmemory_similarity_search() -> None:
 
     # Check sync version
     output = store.similarity_search("foo", k=1)
-    assert output == [_AnyIdDocument(page_content="foo")]
+    assert output == [_any_id_document(page_content="foo")]
 
     # Check async version
     output = await store.asimilarity_search("bar", k=2)
     assert output == [
-        _AnyIdDocument(page_content="bar"),
+        _any_id_document(page_content="bar"),
-        _AnyIdDocument(page_content="baz"),
+        _any_id_document(page_content="baz"),
     ]
 
 
@@ -80,16 +80,16 @@ async def test_inmemory_mmr() -> None:
     # make sure we can k > docstore size
     output = docsearch.max_marginal_relevance_search("foo", k=10, lambda_mult=0.1)
     assert len(output) == len(texts)
-    assert output[0] == _AnyIdDocument(page_content="foo")
+    assert output[0] == _any_id_document(page_content="foo")
-    assert output[1] == _AnyIdDocument(page_content="foy")
+    assert output[1] == _any_id_document(page_content="foy")
 
     # Check async version
     output = await docsearch.amax_marginal_relevance_search(
         "foo", k=10, lambda_mult=0.1
     )
     assert len(output) == len(texts)
-    assert output[0] == _AnyIdDocument(page_content="foo")
+    assert output[0] == _any_id_document(page_content="foo")
-    assert output[1] == _AnyIdDocument(page_content="foy")
+    assert output[1] == _any_id_document(page_content="foy")
 
 
 async def test_inmemory_dump_load(tmp_path: Path) -> None:
@@ -117,7 +117,7 @@ async def test_inmemory_filter() -> None:
 
     # Check sync version
     output = store.similarity_search("fee", filter=lambda doc: doc.metadata["id"] == 1)
-    assert output == [_AnyIdDocument(page_content="foo", metadata={"id": 1})]
+    assert output == [_any_id_document(page_content="foo", metadata={"id": 1})]
 
     # filter with not stored document id
     output = await store.asimilarity_search(

libs/core/tests/unit_tests/vectorstores/test_vectorstore.py

@@ -50,6 +50,7 @@ class CustomAddTextsVectorstore(VectorStore):
     def get_by_ids(self, ids: Sequence[str], /) -> list[Document]:
         return [self.store[id] for id in ids if id in self.store]
 
+    @classmethod
     def from_texts(  # type: ignore
         cls,
         texts: list[str],