core: Bump ruff version to 0.12 (#31846)

libs/core/langchain_core/language_models/base.py

@@ -130,7 +130,7 @@ class BaseLanguageModel(
     )
 
     @field_validator("verbose", mode="before")
-    def set_verbose(cls, verbose: Optional[bool]) -> bool:
+    def set_verbose(cls, verbose: Optional[bool]) -> bool:  # noqa: FBT001
         """If verbose is None, set it.
 
         This allows users to pass in None as verbose to access the global setting.

libs/core/langchain_core/language_models/llms.py

@@ -129,7 +129,7 @@ def create_base_retry_decorator(
     )
 
 
-def _resolve_cache(cache: Union[BaseCache, bool, None]) -> Optional[BaseCache]:
+def _resolve_cache(*, cache: Union[BaseCache, bool, None]) -> Optional[BaseCache]:
     """Resolve the cache."""
     if isinstance(cache, BaseCache):
         llm_cache = cache
@@ -155,7 +155,7 @@ def _resolve_cache(cache: Union[BaseCache, bool, None]) -> Optional[BaseCache]:
 def get_prompts(
     params: dict[str, Any],
     prompts: list[str],
-    cache: Optional[Union[BaseCache, bool, None]] = None,
+    cache: Optional[Union[BaseCache, bool, None]] = None,  # noqa: FBT001
 ) -> tuple[dict[int, list], str, list[int], list[str]]:
     """Get prompts that are already cached.
 
@@ -176,7 +176,7 @@ def get_prompts(
     missing_prompt_idxs = []
     existing_prompts = {}
 
-    llm_cache = _resolve_cache(cache)
+    llm_cache = _resolve_cache(cache=cache)
     for i, prompt in enumerate(prompts):
         if llm_cache:
             cache_val = llm_cache.lookup(prompt, llm_string)
@@ -191,7 +191,7 @@ def get_prompts(
 async def aget_prompts(
     params: dict[str, Any],
     prompts: list[str],
-    cache: Optional[Union[BaseCache, bool, None]] = None,
+    cache: Optional[Union[BaseCache, bool, None]] = None,  # noqa: FBT001
 ) -> tuple[dict[int, list], str, list[int], list[str]]:
     """Get prompts that are already cached. Async version.
 
@@ -211,7 +211,7 @@ async def aget_prompts(
     missing_prompts = []
     missing_prompt_idxs = []
     existing_prompts = {}
-    llm_cache = _resolve_cache(cache)
+    llm_cache = _resolve_cache(cache=cache)
     for i, prompt in enumerate(prompts):
         if llm_cache:
             cache_val = await llm_cache.alookup(prompt, llm_string)
@@ -224,7 +224,7 @@ async def aget_prompts(
 
 
 def update_cache(
-    cache: Union[BaseCache, bool, None],
+    cache: Union[BaseCache, bool, None],  # noqa: FBT001
     existing_prompts: dict[int, list],
     llm_string: str,
     missing_prompt_idxs: list[int],
@@ -247,7 +247,7 @@ def update_cache(
     Raises:
         ValueError: If the cache is not set and cache is True.
     """
-    llm_cache = _resolve_cache(cache)
+    llm_cache = _resolve_cache(cache=cache)
     for i, result in enumerate(new_results.generations):
         existing_prompts[missing_prompt_idxs[i]] = result
         prompt = prompts[missing_prompt_idxs[i]]
@@ -257,7 +257,7 @@ def update_cache(
 
 
 async def aupdate_cache(
-    cache: Union[BaseCache, bool, None],
+    cache: Union[BaseCache, bool, None],  # noqa: FBT001
     existing_prompts: dict[int, list],
     llm_string: str,
     missing_prompt_idxs: list[int],
@@ -280,7 +280,7 @@ async def aupdate_cache(
     Raises:
         ValueError: If the cache is not set and cache is True.
     """
-    llm_cache = _resolve_cache(cache)
+    llm_cache = _resolve_cache(cache=cache)
     for i, result in enumerate(new_results.generations):
         existing_prompts[missing_prompt_idxs[i]] = result
         prompt = prompts[missing_prompt_idxs[i]]

libs/core/langchain_core/messages/utils.py

@@ -1341,8 +1341,8 @@ def _first_max_tokens(
                 excluded.content = list(reversed(excluded.content))
             for _ in range(1, num_block):
                 excluded.content = excluded.content[:-1]
-                if token_counter(messages[:idx] + [excluded]) <= max_tokens:
+                if token_counter([*messages[:idx], excluded]) <= max_tokens:
-                    messages = messages[:idx] + [excluded]
+                    messages = [*messages[:idx], excluded]
                     idx += 1
                     included_partial = True
                     break
@@ -1393,7 +1393,7 @@ def _first_max_tokens(
                     if partial_strategy == "last":
                         content_splits = list(reversed(content_splits))
                     excluded.content = "".join(content_splits)
-                    messages = messages[:idx] + [excluded]
+                    messages = [*messages[:idx], excluded]
                     idx += 1
 
     if end_on:

libs/core/langchain_core/outputs/llm_result.py

@@ -97,3 +97,5 @@ class LLMResult(BaseModel):
             self.generations == other.generations
             and self.llm_output == other.llm_output
         )
+
+    __hash__ = None  # type: ignore[assignment]

libs/core/langchain_core/runnables/base.py

@@ -4205,6 +4205,8 @@ class RunnableGenerator(Runnable[Input, Output]):
             return False
         return False
 
+    __hash__ = None  # type: ignore[assignment]
+
     @override
     def __repr__(self) -> str:
         return f"RunnableGenerator({self.name})"
@@ -4588,6 +4590,8 @@ class RunnableLambda(Runnable[Input, Output]):
             return False
         return False
 
+    __hash__ = None  # type: ignore[assignment]
+
     def __repr__(self) -> str:
         """A string representation of this Runnable."""
         if self._repr is None:

libs/core/langchain_core/runnables/router.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 from collections.abc import Mapping
-from itertools import starmap
 from typing import (
     TYPE_CHECKING,
     Any,
@@ -206,7 +205,7 @@ class RouterRunnable(RunnableSerializable[RouterInput, Output]):
         configs = get_config_list(config, len(inputs))
         return await gather_with_concurrency(
             configs[0].get("max_concurrency"),
-            *starmap(ainvoke, zip(runnables, actual_inputs, configs)),
+            *map(ainvoke, runnables, actual_inputs, configs),
         )
 
     @override

libs/core/langchain_core/tools/base.py

@@ -776,7 +776,7 @@ class ChildTool(BaseTool):
     def run(
         self,
         tool_input: Union[str, dict[str, Any]],
-        verbose: Optional[bool] = None,
+        verbose: Optional[bool] = None,  # noqa: FBT001
         start_color: Optional[str] = "green",
         color: Optional[str] = "green",
         callbacks: Callbacks = None,
@@ -888,7 +888,7 @@ class ChildTool(BaseTool):
     async def arun(
         self,
         tool_input: Union[str, dict],
-        verbose: Optional[bool] = None,
+        verbose: Optional[bool] = None,  # noqa: FBT001
         start_color: Optional[str] = "green",
         color: Optional[str] = "green",
         callbacks: Callbacks = None,

libs/core/langchain_core/tracers/log_stream.py

@@ -130,6 +130,8 @@ class RunLogPatch:
     def __eq__(self, other: object) -> bool:
         return isinstance(other, RunLogPatch) and self.ops == other.ops
 
+    __hash__ = None  # type: ignore[assignment]
+
 
 class RunLog(RunLogPatch):
     """Run log."""
@@ -174,6 +176,8 @@ class RunLog(RunLogPatch):
         # Then compare that the ops are the same
         return super().__eq__(other)
 
+    __hash__ = None  # type: ignore[assignment]
+
 
 T = TypeVar("T")
 

libs/core/pyproject.toml

@@ -27,7 +27,7 @@ repository = "https://github.com/langchain-ai/langchain"
 
 [dependency-groups]
 lint = [
-    "ruff<0.12.0,>=0.11.2",
+    "ruff<0.13.0,>=0.12.2",
 ]
 typing = [
     "mypy<1.16,>=1.15",
@@ -95,12 +95,12 @@ ignore = [
     "TC003", # Doesn't play well with Pydantic
     "TD002", # Missing author in TODO
     "TD003", # Missing issue link in TODO
-    "UP007", # Doesn't play well with Pydantic in Python 3.9
 
     # TODO rules
     "ANN401",
     "BLE",
     "ERA",
+    "PLC0415",
     "PLR2004",
 ]
 flake8-type-checking.runtime-evaluated-base-classes = ["pydantic.BaseModel","langchain_core.load.serializable.Serializable","langchain_core.runnables.base.RunnableSerializable"]
@@ -108,6 +108,7 @@ flake8-annotations.allow-star-arg-any = true
 flake8-annotations.mypy-init-return = true
 pydocstyle.convention = "google"
 pydocstyle.ignore-var-parameters = true
+pyupgrade.keep-runtime-typing = true
 
 [tool.coverage.run]
 omit = [ "tests/*",]

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

@@ -329,6 +329,7 @@ class StreamingModel(NoStreamingModel):
 
 @pytest.mark.parametrize("disable_streaming", [True, False, "tool_calling"])
 def test_disable_streaming(
+    *,
     disable_streaming: Union[bool, Literal["tool_calling"]],
 ) -> None:
     model = StreamingModel(disable_streaming=disable_streaming)
@@ -353,6 +354,7 @@ def test_disable_streaming(
 
 @pytest.mark.parametrize("disable_streaming", [True, False, "tool_calling"])
 async def test_disable_streaming_async(
+    *,
     disable_streaming: Union[bool, Literal["tool_calling"]],
 ) -> None:
     model = StreamingModel(disable_streaming=disable_streaming)
@@ -379,6 +381,7 @@ async def test_disable_streaming_async(
 
 @pytest.mark.parametrize("disable_streaming", [True, False, "tool_calling"])
 def test_disable_streaming_no_streaming_model(
+    *,
     disable_streaming: Union[bool, Literal["tool_calling"]],
 ) -> None:
     model = NoStreamingModel(disable_streaming=disable_streaming)
@@ -393,6 +396,7 @@ def test_disable_streaming_no_streaming_model(
 
 @pytest.mark.parametrize("disable_streaming", [True, False, "tool_calling"])
 async def test_disable_streaming_no_streaming_model_async(
+    *,
     disable_streaming: Union[bool, Literal["tool_calling"]],
 ) -> None:
     model = NoStreamingModel(disable_streaming=disable_streaming)

libs/core/tests/unit_tests/load/test_serializable.py

@@ -21,6 +21,8 @@ class NonBoolObj:
     def __repr__(self) -> str:
         return self.__class__.__name__
 
+    __hash__ = None  # type: ignore[assignment]
+
 
 def test_simple_serialization() -> None:
     class Foo(Serializable):
@@ -100,6 +102,8 @@ def test__is_field_useful() -> None:
         def __eq__(self, other: object) -> bool:
             return self  # type: ignore[return-value]
 
+        __hash__ = None  # type: ignore[assignment]
+
     default_x = ArrayObj()
     default_y = NonBoolObj()
 

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

@@ -266,7 +266,7 @@ def test_prompt_jinja2_missing_input_variables(
     suffix = "Ending with {{ bar }}"
 
     # Test when missing in suffix
-    with pytest.warns(UserWarning):
+    with pytest.warns(UserWarning, match="Missing variables: {'bar'}"):
         FewShotPromptTemplate(
             input_variables=[],
             suffix=suffix,
@@ -284,7 +284,7 @@ def test_prompt_jinja2_missing_input_variables(
     ).input_variables == ["bar"]
 
     # Test when missing in prefix
-    with pytest.warns(UserWarning):
+    with pytest.warns(UserWarning, match="Missing variables: {'foo'}"):
         FewShotPromptTemplate(
             input_variables=["bar"],
             suffix=suffix,
@@ -311,7 +311,7 @@ def test_prompt_jinja2_extra_input_variables(
     """Test error is raised when there are too many input variables."""
     prefix = "Starting with {{ foo }}"
     suffix = "Ending with {{ bar }}"
-    with pytest.warns(UserWarning):
+    with pytest.warns(UserWarning, match="Extra variables:"):
         FewShotPromptTemplate(
             input_variables=["bar", "foo", "extra", "thing"],
             suffix=suffix,

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

@@ -509,7 +509,7 @@ def test_prompt_jinja2_missing_input_variables() -> None:
     """Test error is raised when input variables are not provided."""
     template = "This is a {{ foo }} test."
     input_variables: list = []
-    with pytest.warns(UserWarning):
+    with pytest.warns(UserWarning, match="Missing variables: {'foo'}"):
         PromptTemplate(
             input_variables=input_variables,
             template=template,
@@ -526,7 +526,7 @@ def test_prompt_jinja2_extra_input_variables() -> None:
     """Test error is raised when there are too many input variables."""
     template = "This is a {{ foo }} test."
     input_variables = ["foo", "bar"]
-    with pytest.warns(UserWarning):
+    with pytest.warns(UserWarning, match="Extra variables: {'bar'}"):
         PromptTemplate(
             input_variables=input_variables,
             template=template,
@@ -543,7 +543,9 @@ def test_prompt_jinja2_wrong_input_variables() -> None:
     """Test error is raised when name of input variable is wrong."""
     template = "This is a {{ foo }} test."
     input_variables = ["bar"]
-    with pytest.warns(UserWarning):
+    with pytest.warns(
+        UserWarning, match="Missing variables: {'foo'} Extra variables: {'bar'}"
+    ):
         PromptTemplate(
             input_variables=input_variables,
             template=template,

libs/core/tests/unit_tests/stubs.py

@@ -10,6 +10,8 @@ class AnyStr(str):
     def __eq__(self, other: object) -> bool:
         return isinstance(other, str)
 
+    __hash__ = str.__hash__
+
 
 # The code below creates version of pydantic models
 # that will work in unit tests with AnyStr as id field

libs/core/tests/unit_tests/test_tools.py

@@ -884,6 +884,7 @@ def test_validation_error_handling_callable() -> None:
     ],
 )
 def test_validation_error_handling_non_validation_error(
+    *,
     handler: Union[
         bool, str, Callable[[Union[ValidationError, ValidationErrorV1]], str]
     ],
@@ -949,6 +950,7 @@ async def test_async_validation_error_handling_callable() -> None:
     ],
 )
 async def test_async_validation_error_handling_non_validation_error(
+    *,
     handler: Union[
         bool, str, Callable[[Union[ValidationError, ValidationErrorV1]], str]
     ],
@@ -2331,6 +2333,9 @@ def test_tool_return_output_mixin() -> None:
         def __eq__(self, other: object) -> bool:
             return isinstance(other, self.__class__) and self.x == other.x
 
+        def __hash__(self) -> int:
+            return hash(self.x)
+
     @tool
     def foo(x: int) -> Bar:
         """Foo."""