Add ruff rules for flake8-simplify (SIM)

libs/core/langchain_core/_api/beta_decorator.py

@@ -127,10 +127,9 @@ async def awarning_emitting_wrapper(*args: Any, **kwargs: Any) -> Any:
 
             def finalize(wrapper: Callable[..., Any], new_doc: str) -> T:
                 """Finalize the annotation of a class."""
-                try:
+                # Can't set new_doc on some extension objects.
+                with contextlib.suppress(AttributeError):
                     obj.__doc__ = new_doc
-                except AttributeError:  # Can't set on some extension objects.
-                    pass
 
                 def warn_if_direct_instance(
                     self: Any, *args: Any, **kwargs: Any

libs/core/langchain_core/_api/deprecation.py

@@ -198,10 +198,9 @@ async def awarning_emitting_wrapper(*args: Any, **kwargs: Any) -> Any:
 
             def finalize(wrapper: Callable[..., Any], new_doc: str) -> T:
                 """Finalize the deprecation of a class."""
-                try:
+                # Can't set new_doc on some extension objects.
+                with contextlib.suppress(AttributeError):
                     obj.__doc__ = new_doc
-                except AttributeError:  # Can't set on some extension objects.
-                    pass
 
                 def warn_if_direct_instance(
                     self: Any, *args: Any, **kwargs: Any

libs/core/langchain_core/callbacks/file.py

@@ -27,7 +27,7 @@ def __init__(
             mode: The mode to open the file in. Defaults to "a".
             color: The color to use for the text. Defaults to None.
         """
-        self.file = cast(TextIO, open(filename, mode, encoding="utf-8"))
+        self.file = cast(TextIO, open(filename, mode, encoding="utf-8"))  # noqa: SIM115
         self.color = color
 
     def __del__(self) -> None:

libs/core/langchain_core/callbacks/manager.py

@@ -2252,14 +2252,14 @@ def _configure(
         else:
             parent_run_id_ = inheritable_callbacks.parent_run_id
             # Break ties between the external tracing context and inherited context
-            if parent_run_id is not None:
-                if parent_run_id_ is None:
-                    parent_run_id_ = parent_run_id
+            if parent_run_id is not None and (
+                parent_run_id_ is None
                 # If the LC parent has already been reflected
                 # in the run tree, we know the run_tree is either the
                 # same parent or a child of the parent.
-                elif run_tree and str(parent_run_id_) in run_tree.dotted_order:
-                    parent_run_id_ = parent_run_id
+                or (run_tree and str(parent_run_id_) in run_tree.dotted_order)
+            ):
+                parent_run_id_ = parent_run_id
                 # Otherwise, we assume the LC context has progressed
                 # beyond the run tree and we should not inherit the parent.
             callback_manager = callback_manager_cls(

libs/core/langchain_core/exceptions.py

@@ -40,12 +40,11 @@ def __init__(
         send_to_llm: bool = False,
     ):
         super().__init__(error)
-        if send_to_llm:
-            if observation is None or llm_output is None:
-                raise ValueError(
-                    "Arguments 'observation' & 'llm_output'"
-                    " are required if 'send_to_llm' is True"
-                )
+        if send_to_llm and (observation is None or llm_output is None):
+            raise ValueError(
+                "Arguments 'observation' & 'llm_output'"
+                " are required if 'send_to_llm' is True"
+            )
         self.observation = observation
         self.llm_output = llm_output
         self.send_to_llm = send_to_llm

libs/core/langchain_core/indexing/api.py

@@ -92,7 +92,7 @@ def calculate_hashes(cls, values: dict[str, Any]) -> Any:
         values["metadata_hash"] = metadata_hash
         values["hash_"] = str(_hash_string_to_uuid(content_hash + metadata_hash))
 
-        _uid = values.get("uid", None)
+        _uid = values.get("uid")
 
         if _uid is None:
             values["uid"] = values["hash_"]

libs/core/langchain_core/language_models/chat_models.py

@@ -802,10 +802,7 @@ def _generate_with_cache(
         run_manager: Optional[CallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> ChatResult:
-        if isinstance(self.cache, BaseCache):
-            llm_cache = self.cache
-        else:
-            llm_cache = get_llm_cache()
+        llm_cache = self.cache if isinstance(self.cache, BaseCache) else get_llm_cache()
         # We should check the cache unless it's explicitly set to False
         # A None cache means we should use the default global cache
         # if it's configured.
@@ -879,10 +876,7 @@ async def _agenerate_with_cache(
         run_manager: Optional[AsyncCallbackManagerForLLMRun] = None,
         **kwargs: Any,
     ) -> ChatResult:
-        if isinstance(self.cache, BaseCache):
-            llm_cache = self.cache
-        else:
-            llm_cache = get_llm_cache()
+        llm_cache = self.cache if isinstance(self.cache, BaseCache) else get_llm_cache()
         # We should check the cache unless it's explicitly set to False
         # A None cache means we should use the default global cache
         # if it's configured.
@@ -1054,10 +1048,7 @@ def call_as_llm(
     def predict(
         self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
     ) -> str:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         result = self([HumanMessage(content=text)], stop=_stop, **kwargs)
         if isinstance(result.content, str):
             return result.content
@@ -1072,20 +1063,14 @@ def predict_messages(
         stop: Optional[Sequence[str]] = None,
         **kwargs: Any,
     ) -> BaseMessage:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         return self(messages, stop=_stop, **kwargs)
 
     @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
     async def apredict(
         self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
     ) -> str:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         result = await self._call_async(
             [HumanMessage(content=text)], stop=_stop, **kwargs
         )
@@ -1102,10 +1087,7 @@ async def apredict_messages(
         stop: Optional[Sequence[str]] = None,
         **kwargs: Any,
     ) -> BaseMessage:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         return await self._call_async(messages, stop=_stop, **kwargs)
 
     @property
@@ -1333,9 +1315,12 @@ def _cleanup_llm_representation(serialized: Any, depth: int) -> None:
     if not isinstance(serialized, dict):
         return
 
-    if "type" in serialized and serialized["type"] == "not_implemented":
-        if "repr" in serialized:
-            del serialized["repr"]
+    if (
+        "type" in serialized
+        and serialized["type"] == "not_implemented"
+        and "repr" in serialized
+    ):
+        del serialized["repr"]
 
     if "graph" in serialized:
         del serialized["graph"]

libs/core/langchain_core/language_models/fake_chat_models.py

@@ -194,10 +194,7 @@ def _generate(
     ) -> ChatResult:
         """Top Level call"""
         message = next(self.messages)
-        if isinstance(message, str):
-            message_ = AIMessage(content=message)
-        else:
-            message_ = message
+        message_ = AIMessage(content=message) if isinstance(message, str) else message
         generation = ChatGeneration(message=message_)
         return ChatResult(generations=[generation])
 

libs/core/langchain_core/language_models/llms.py

@@ -1305,10 +1305,7 @@ async def _call_async(
     def predict(
         self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
     ) -> str:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         return self(text, stop=_stop, **kwargs)
 
     @deprecated("0.1.7", alternative="invoke", removal="1.0")
@@ -1320,21 +1317,15 @@ def predict_messages(
         **kwargs: Any,
     ) -> BaseMessage:
         text = get_buffer_string(messages)
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         content = self(text, stop=_stop, **kwargs)
         return AIMessage(content=content)
 
     @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
     async def apredict(
         self, text: str, *, stop: Optional[Sequence[str]] = None, **kwargs: Any
     ) -> str:
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         return await self._call_async(text, stop=_stop, **kwargs)
 
     @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
@@ -1346,10 +1337,7 @@ async def apredict_messages(
         **kwargs: Any,
     ) -> BaseMessage:
         text = get_buffer_string(messages)
-        if stop is None:
-            _stop = None
-        else:
-            _stop = list(stop)
+        _stop = None if stop is None else list(stop)
         content = await self._call_async(text, stop=_stop, **kwargs)
         return AIMessage(content=content)
 
@@ -1384,10 +1372,7 @@ def save(self, file_path: Union[Path, str]) -> None:
             llm.save(file_path="path/llm.yaml")
         """
         # Convert file to Path object.
-        if isinstance(file_path, str):
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
 
         directory_path = save_path.parent
         directory_path.mkdir(parents=True, exist_ok=True)

libs/core/langchain_core/load/load.py

@@ -86,9 +86,9 @@ def __init__(
 
     def __call__(self, value: dict[str, Any]) -> Any:
         if (
-            value.get("lc", None) == 1
-            and value.get("type", None) == "secret"
-            and value.get("id", None) is not None
+            value.get("lc") == 1
+            and value.get("type") == "secret"
+            and value.get("id") is not None
         ):
             [key] = value["id"]
             if key in self.secrets_map:
@@ -99,27 +99,28 @@ def __call__(self, value: dict[str, Any]) -> Any:
                 raise KeyError(f'Missing key "{key}" in load(secrets_map)')
 
         if (
-            value.get("lc", None) == 1
-            and value.get("type", None) == "not_implemented"
-            and value.get("id", None) is not None
+            value.get("lc") == 1
+            and value.get("type") == "not_implemented"
+            and value.get("id") is not None
         ):
             raise NotImplementedError(
                 "Trying to load an object that doesn't implement "
                 f"serialization: {value}"
             )
 
         if (
-            value.get("lc", None) == 1
-            and value.get("type", None) == "constructor"
-            and value.get("id", None) is not None
+            value.get("lc") == 1
+            and value.get("type") == "constructor"
+            and value.get("id") is not None
         ):
             [*namespace, name] = value["id"]
             mapping_key = tuple(value["id"])
 
-            if namespace[0] not in self.valid_namespaces:
-                raise ValueError(f"Invalid namespace: {value}")
-            # The root namespace ["langchain"] is not a valid identifier.
-            elif namespace == ["langchain"]:
+            if (
+                namespace[0] not in self.valid_namespaces
+                # The root namespace ["langchain"] is not a valid identifier.
+                or namespace == ["langchain"]
+            ):
                 raise ValueError(f"Invalid namespace: {value}")
             # Has explicit import path.
             elif mapping_key in self.import_mappings:

libs/core/langchain_core/load/serializable.py

@@ -1,3 +1,4 @@
+import contextlib
 from abc import ABC
 from typing import (
     Any,
@@ -238,7 +239,7 @@ def to_json(self) -> Union[SerializedConstructor, SerializedNotImplemented]:
 
         # include all secrets, even if not specified in kwargs
         # as these secrets may be passed as an environment variable instead
-        for key in secrets.keys():
+        for key in secrets:
             secret_value = getattr(self, key, None) or lc_kwargs.get(key)
             if secret_value is not None:
                 lc_kwargs.update({key: secret_value})
@@ -357,8 +358,6 @@ def to_json_not_implemented(obj: object) -> SerializedNotImplemented:
         "id": _id,
         "repr": None,
     }
-    try:
+    with contextlib.suppress(Exception):
         result["repr"] = repr(obj)
-    except Exception:
-        pass
     return result

libs/core/langchain_core/messages/utils.py

@@ -435,23 +435,22 @@ def filter_messages(
     messages = convert_to_messages(messages)
     filtered: list[BaseMessage] = []
     for msg in messages:
-        if exclude_names and msg.name in exclude_names:
-            continue
-        elif exclude_types and _is_message_type(msg, exclude_types):
-            continue
-        elif exclude_ids and msg.id in exclude_ids:
+        if (
+            (exclude_names and msg.name in exclude_names)
+            or (exclude_types and _is_message_type(msg, exclude_types))
+            or (exclude_ids and msg.id in exclude_ids)
+        ):
             continue
         else:
             pass
 
         # default to inclusion when no inclusion criteria given.
-        if not (include_types or include_ids or include_names):
-            filtered.append(msg)
-        elif include_names and msg.name in include_names:
-            filtered.append(msg)
-        elif include_types and _is_message_type(msg, include_types):
-            filtered.append(msg)
-        elif include_ids and msg.id in include_ids:
+        if (
+            not (include_types or include_ids or include_names)
+            or (include_names and msg.name in include_names)
+            or (include_types and _is_message_type(msg, include_types))
+            or (include_ids and msg.id in include_ids)
+        ):
             filtered.append(msg)
         else:
             pass
@@ -960,10 +959,7 @@ def _last_max_tokens(
         while messages and not _is_message_type(messages[-1], end_on):
             messages.pop()
     swapped_system = include_system and isinstance(messages[0], SystemMessage)
-    if swapped_system:
-        reversed_ = messages[:1] + messages[1:][::-1]
-    else:
-        reversed_ = messages[::-1]
+    reversed_ = messages[:1] + messages[1:][::-1] if swapped_system else messages[::-1]
 
     reversed_ = _first_max_tokens(
         reversed_,

libs/core/langchain_core/output_parsers/base.py

@@ -1,5 +1,6 @@
 from __future__ import annotations
 
+import contextlib
 from abc import ABC, abstractmethod
 from typing import (
     TYPE_CHECKING,
@@ -311,8 +312,6 @@ def _type(self) -> str:
     def dict(self, **kwargs: Any) -> dict:
         """Return dictionary representation of output parser."""
         output_parser_dict = super().dict(**kwargs)
-        try:
+        with contextlib.suppress(NotImplementedError):
             output_parser_dict["_type"] = self._type
-        except NotImplementedError:
-            pass
         return output_parser_dict

libs/core/langchain_core/output_parsers/json.py

@@ -49,12 +49,10 @@ def _diff(self, prev: Optional[Any], next: Any) -> Any:
         return jsonpatch.make_patch(prev, next).patch
 
     def _get_schema(self, pydantic_object: type[TBaseModel]) -> dict[str, Any]:
-        if PYDANTIC_MAJOR_VERSION == 2:
-            if issubclass(pydantic_object, pydantic.BaseModel):
-                return pydantic_object.model_json_schema()
-            elif issubclass(pydantic_object, pydantic.v1.BaseModel):
-                return pydantic_object.model_json_schema()
-        return pydantic_object.model_json_schema()
+        if issubclass(pydantic_object, pydantic.BaseModel):
+            return pydantic_object.model_json_schema()
+        elif issubclass(pydantic_object, pydantic.v1.BaseModel):
+            return pydantic_object.schema()
 
     def parse_result(self, result: list[Generation], *, partial: bool = False) -> Any:
         """Parse the result of an LLM call to a JSON object.