core: Add ruff rules TRY (tryceratops) (#29388)

TRY004 ("use TypeError rather than ValueError") existing errors are
marked as ignore to preserve backward compatibility.
LMK if you prefer to fix some of them.

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

libs/core/langchain_core/callbacks/manager.py

@@ -127,7 +127,7 @@ def trace_as_chain_group(
     except Exception as e:
         if not group_cm.ended:
             run_manager.on_chain_error(e)
-        raise e
+        raise
     else:
         if not group_cm.ended:
             run_manager.on_chain_end({})
@@ -207,7 +207,7 @@ async def atrace_as_chain_group(
     except Exception as e:
         if not group_cm.ended:
             await run_manager.on_chain_error(e)
-        raise e
+        raise
     else:
         if not group_cm.ended:
             await run_manager.on_chain_end({})
@@ -289,7 +289,7 @@ def handle_event(
                     f" {repr(e)}"
                 )
                 if handler.raise_error:
-                    raise e
+                    raise
     finally:
         if coros:
             try:
@@ -388,7 +388,7 @@ async def _ahandle_event_for_handler(
             f"Error in {handler.__class__.__name__}.{event_name} callback: {repr(e)}"
         )
         if handler.raise_error:
-            raise e
+            raise
 
 
 async def ahandle_event(

libs/core/langchain_core/language_models/chat_models.py

@@ -268,7 +268,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
                 f"Invalid input type {type(input)}. "
                 "Must be a PromptValue, str, or list of BaseMessages."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     def invoke(
         self,
@@ -407,9 +407,6 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
                         generation = chunk
                     else:
                         generation += chunk
-                if generation is None:
-                    msg = "No generation chunks were returned"
-                    raise ValueError(msg)
             except BaseException as e:
                 run_manager.on_llm_error(
                     e,
@@ -417,9 +414,14 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
                         generations=[[generation]] if generation else []
                     ),
                 )
-                raise e
-            else:
-                run_manager.on_llm_end(LLMResult(generations=[[generation]]))
+                raise
+
+            if generation is None:
+                err = ValueError("No generation chunks were returned")
+                run_manager.on_llm_error(err, response=LLMResult(generations=[]))
+                raise err
+
+            run_manager.on_llm_end(LLMResult(generations=[[generation]]))
 
     async def astream(
         self,
@@ -485,19 +487,21 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
                     generation = chunk
                 else:
                     generation += chunk
-            if generation is None:
-                msg = "No generation chunks were returned"
-                raise ValueError(msg)
         except BaseException as e:
             await run_manager.on_llm_error(
                 e,
                 response=LLMResult(generations=[[generation]] if generation else []),
             )
-            raise e
-        else:
-            await run_manager.on_llm_end(
-                LLMResult(generations=[[generation]]),
-            )
+            raise
+
+        if generation is None:
+            err = ValueError("No generation chunks were returned")
+            await run_manager.on_llm_error(err, response=LLMResult(generations=[]))
+            raise err
+
+        await run_manager.on_llm_end(
+            LLMResult(generations=[[generation]]),
+        )
 
     # --- Custom methods ---
 
@@ -641,7 +645,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             except BaseException as e:
                 if run_managers:
                     run_managers[i].on_llm_error(e, response=LLMResult(generations=[]))
-                raise e
+                raise
         flattened_outputs = [
             LLMResult(generations=[res.generations], llm_output=res.llm_output)  # type: ignore[list-item]
             for res in results
@@ -1022,7 +1026,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             return generation.message
         else:
             msg = "Unexpected generation type"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     async def _call_async(
         self,
@@ -1039,7 +1043,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             return generation.message
         else:
             msg = "Unexpected generation type"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="invoke", removal="1.0")
     def call_as_llm(
@@ -1057,7 +1061,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             return result.content
         else:
             msg = "Cannot use predict when output is not a string."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="invoke", removal="1.0")
     def predict_messages(
@@ -1082,7 +1086,7 @@ class BaseChatModel(BaseLanguageModel[BaseMessage], ABC):
             return result.content
         else:
             msg = "Cannot use predict when output is not a string."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     @deprecated("0.1.7", alternative="ainvoke", removal="1.0")
     async def apredict_messages(

libs/core/langchain_core/language_models/fake_chat_models.py

@@ -242,7 +242,7 @@ class GenericFakeChatModel(BaseChatModel):
                 f"Expected generate to return a ChatResult, "
                 f"but got {type(chat_result)} instead."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         message = chat_result.generations[0].message
 
@@ -251,7 +251,7 @@ class GenericFakeChatModel(BaseChatModel):
                 f"Expected invoke to return an AIMessage, "
                 f"but got {type(message)} instead."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         content = message.content
 

libs/core/langchain_core/language_models/llms.py

@@ -337,7 +337,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 f"Invalid input type {type(input)}. "
                 "Must be a PromptValue, str, or list of BaseMessages."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     def _get_ls_params(
         self,
@@ -448,7 +448,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 if return_exceptions:
                     return cast(list[str], [e for _ in inputs])
                 else:
-                    raise e
+                    raise
         else:
             batches = [
                 inputs[i : i + max_concurrency]
@@ -494,7 +494,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 if return_exceptions:
                     return cast(list[str], [e for _ in inputs])
                 else:
-                    raise e
+                    raise
         else:
             batches = [
                 inputs[i : i + max_concurrency]
@@ -562,9 +562,6 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                         generation = chunk
                     else:
                         generation += chunk
-                if generation is None:
-                    msg = "No generation chunks were returned"
-                    raise ValueError(msg)
             except BaseException as e:
                 run_manager.on_llm_error(
                     e,
@@ -572,9 +569,14 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                         generations=[[generation]] if generation else []
                     ),
                 )
-                raise e
-            else:
-                run_manager.on_llm_end(LLMResult(generations=[[generation]]))
+                raise
+
+            if generation is None:
+                err = ValueError("No generation chunks were returned")
+                run_manager.on_llm_error(err, response=LLMResult(generations=[]))
+                raise err
+
+            run_manager.on_llm_end(LLMResult(generations=[[generation]]))
 
     async def astream(
         self,
@@ -632,17 +634,19 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                     generation = chunk
                 else:
                     generation += chunk
-            if generation is None:
-                msg = "No generation chunks were returned"
-                raise ValueError(msg)
         except BaseException as e:
             await run_manager.on_llm_error(
                 e,
                 response=LLMResult(generations=[[generation]] if generation else []),
             )
-            raise e
-        else:
-            await run_manager.on_llm_end(LLMResult(generations=[[generation]]))
+            raise
+
+        if generation is None:
+            err = ValueError("No generation chunks were returned")
+            await run_manager.on_llm_error(err, response=LLMResult(generations=[]))
+            raise err
+
+        await run_manager.on_llm_end(LLMResult(generations=[[generation]]))
 
     # --- Custom methods ---
 
@@ -790,7 +794,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
         except BaseException as e:
             for run_manager in run_managers:
                 run_manager.on_llm_error(e, response=LLMResult(generations=[]))
-            raise e
+            raise
         flattened_outputs = output.flatten()
         for manager, flattened_output in zip(run_managers, flattened_outputs):
             manager.on_llm_end(flattened_output)
@@ -850,7 +854,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 "Argument 'prompts' is expected to be of type List[str], received"
                 f" argument of type {type(prompts)}."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         # Create callback managers
         if isinstance(metadata, list):
             metadata = [
@@ -1036,7 +1040,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                     for run_manager in run_managers
                 ]
             )
-            raise e
+            raise
         flattened_outputs = output.flatten()
         await asyncio.gather(
             *[
@@ -1289,7 +1293,7 @@ class BaseLLM(BaseLanguageModel[str], ABC):
                 f"{type(prompt)}. If you want to run the LLM on multiple prompts, use "
                 "`generate` instead."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         return (
             self.generate(
                 [prompt],

libs/core/langchain_core/messages/ai.py

@@ -363,6 +363,17 @@ class AIMessageChunk(AIMessage, BaseMessageChunk):
             return self
         tool_calls = []
         invalid_tool_calls = []
+
+        def add_chunk_to_invalid_tool_calls(chunk: ToolCallChunk) -> None:
+            invalid_tool_calls.append(
+                create_invalid_tool_call(
+                    name=chunk["name"],
+                    args=chunk["args"],
+                    id=chunk["id"],
+                    error=None,
+                )
+            )
+
         for chunk in self.tool_call_chunks:
             try:
                 args_ = parse_partial_json(chunk["args"]) if chunk["args"] != "" else {}  # type: ignore[arg-type]
@@ -375,17 +386,9 @@ class AIMessageChunk(AIMessage, BaseMessageChunk):
                         )
                     )
                 else:
-                    msg = "Malformed args."
-                    raise ValueError(msg)
+                    add_chunk_to_invalid_tool_calls(chunk)
             except Exception:
-                invalid_tool_calls.append(
-                    create_invalid_tool_call(
-                        name=chunk["name"],
-                        args=chunk["args"],
-                        id=chunk["id"],
-                        error=None,
-                    )
-                )
+                add_chunk_to_invalid_tool_calls(chunk)
         self.tool_calls = tool_calls
         self.invalid_tool_calls = invalid_tool_calls
         return self

libs/core/langchain_core/messages/utils.py

@@ -124,7 +124,7 @@ def get_buffer_string(
             role = m.role
         else:
             msg = f"Got unsupported message type: {m}"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         message = f"{role}: {m.content}"
         if isinstance(m, AIMessage) and "function_call" in m.additional_kwargs:
             message += f"{m.additional_kwargs['function_call']}"
@@ -1400,7 +1400,7 @@ def _get_message_openai_role(message: BaseMessage) -> str:
         return message.role
     else:
         msg = f"Unknown BaseMessage type {message.__class__}."
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
 
 
 def _convert_to_openai_tool_calls(tool_calls: list[ToolCall]) -> list[dict]:

libs/core/langchain_core/output_parsers/openai_tools.py

@@ -282,19 +282,20 @@ class PydanticToolsParser(JsonOutputToolsParser):
         name_dict = {tool.__name__: tool for tool in self.tools}
         pydantic_objects = []
         for res in json_results:
-            try:
-                if not isinstance(res["args"], dict):
-                    msg = (
-                        f"Tool arguments must be specified as a dict, received: "
-                        f"{res['args']}"
-                    )
-                    raise ValueError(msg)
-                pydantic_objects.append(name_dict[res["type"]](**res["args"]))
-            except (ValidationError, ValueError) as e:
+            if not isinstance(res["args"], dict):
                 if partial:
                     continue
-                else:
-                    raise e
+                msg = (
+                    f"Tool arguments must be specified as a dict, received: "
+                    f"{res['args']}"
+                )
+                raise ValueError(msg)
+            try:
+                pydantic_objects.append(name_dict[res["type"]](**res["args"]))
+            except (ValidationError, ValueError):
+                if partial:
+                    continue
+                raise
         if self.first_tool_only:
             return pydantic_objects[0] if pydantic_objects else None
         else:

libs/core/langchain_core/output_parsers/pydantic.py

@@ -66,10 +66,10 @@ class PydanticOutputParser(JsonOutputParser, Generic[TBaseModel]):
         try:
             json_object = super().parse_result(result)
             return self._parse_obj(json_object)
-        except OutputParserException as e:
+        except OutputParserException:
             if partial:
                 return None
-            raise e
+            raise
 
     def parse(self, text: str) -> TBaseModel:
         """Parse the output of an LLM call to a pydantic object.

libs/core/langchain_core/prompts/chat.py

@@ -244,7 +244,7 @@ class MessagesPlaceholder(BaseMessagePromptTemplate):
                 f"variable {self.variable_name} should be a list of base messages, "
                 f"got {value} of type {type(value)}"
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         value = convert_to_messages(value)
         if self.n_messages:
             value = value[-self.n_messages :]
@@ -577,7 +577,7 @@ class _StringImageMessagePromptTemplate(BaseMessagePromptTemplate):
             return cls(prompt=prompt, **kwargs)
         else:
             msg = f"Invalid template: {template}"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     @classmethod
     def from_template_file(
@@ -1225,7 +1225,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
                 result.extend(message)
             else:
                 msg = f"Unexpected input: {message_template}"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
         return result
 
     async def aformat_messages(self, **kwargs: Any) -> list[BaseMessage]:
@@ -1253,7 +1253,7 @@ class ChatPromptTemplate(BaseChatPromptTemplate):
                 result.extend(message)
             else:
                 msg = f"Unexpected input: {message_template}"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa:TRY004
         return result
 
     def partial(self, **kwargs: Any) -> ChatPromptTemplate:
@@ -1399,7 +1399,7 @@ def _create_template_from_message_type(
             var_name_wrapped, is_optional = template
             if not isinstance(var_name_wrapped, str):
                 msg = f"Expected variable name to be a string. Got: {var_name_wrapped}"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa:TRY004
             if var_name_wrapped[0] != "{" or var_name_wrapped[-1] != "}":
                 msg = (
                     f"Invalid placeholder template: {var_name_wrapped}."

libs/core/langchain_core/prompts/loading.py

@@ -78,7 +78,7 @@ def _load_examples(config: dict) -> dict:
         config["examples"] = examples
     else:
         msg = "Invalid examples format. Only list or string are supported."
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa:TRY004
     return config
 
 

libs/core/langchain_core/retrievers.py

@@ -262,7 +262,7 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC):
                 result = self._get_relevant_documents(input, **_kwargs)
         except Exception as e:
             run_manager.on_retriever_error(e)
-            raise e
+            raise
         else:
             run_manager.on_retriever_end(
                 result,
@@ -325,7 +325,7 @@ class BaseRetriever(RunnableSerializable[RetrieverInput, RetrieverOutput], ABC):
                 result = await self._aget_relevant_documents(input, **_kwargs)
         except Exception as e:
             await run_manager.on_retriever_error(e)
-            raise e
+            raise
         else:
             await run_manager.on_retriever_end(
                 result,

libs/core/langchain_core/runnables/fallbacks.py

@@ -188,7 +188,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                 last_error = e
             except BaseException as e:
                 run_manager.on_chain_error(e)
-                raise e
+                raise
             else:
                 run_manager.on_chain_end(output)
                 return output
@@ -241,7 +241,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                 last_error = e
             except BaseException as e:
                 await run_manager.on_chain_error(e)
-                raise e
+                raise
             else:
                 await run_manager.on_chain_end(output)
                 return output
@@ -488,7 +488,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                 last_error = e
             except BaseException as e:
                 run_manager.on_chain_error(e)
-                raise e
+                raise
             else:
                 first_error = None
                 break
@@ -507,7 +507,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                     output = None
         except BaseException as e:
             run_manager.on_chain_error(e)
-            raise e
+            raise
         run_manager.on_chain_end(output)
 
     async def astream(
@@ -558,7 +558,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                 last_error = e
             except BaseException as e:
                 await run_manager.on_chain_error(e)
-                raise e
+                raise
             else:
                 first_error = None
                 break
@@ -577,7 +577,7 @@ class RunnableWithFallbacks(RunnableSerializable[Input, Output]):
                     output = None
         except BaseException as e:
             await run_manager.on_chain_error(e)
-            raise e
+            raise
         await run_manager.on_chain_end(output)
 
     def __getattr__(self, name: str) -> Any:

libs/core/langchain_core/runnables/graph.py

@@ -50,9 +50,9 @@ def is_uuid(value: str) -> bool:
     """
     try:
         UUID(value)
-        return True
     except ValueError:
         return False
+    return True
 
 
 class Edge(NamedTuple):

libs/core/langchain_core/runnables/history.py

@@ -481,7 +481,7 @@ class RunnableWithMessageHistory(RunnableBindingBase):
                 f"Expected str, BaseMessage, List[BaseMessage], or Tuple[BaseMessage]. "
                 f"Got {input_val}."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     def _get_output_messages(
         self, output_val: Union[str, BaseMessage, Sequence[BaseMessage], dict]
@@ -517,7 +517,7 @@ class RunnableWithMessageHistory(RunnableBindingBase):
                 f"Expected str, BaseMessage, List[BaseMessage], or Tuple[BaseMessage]. "
                 f"Got {output_val}."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     def _enter_history(self, input: Any, config: RunnableConfig) -> list[BaseMessage]:
         hist: BaseChatMessageHistory = config["configurable"]["message_history"]

libs/core/langchain_core/runnables/passthrough.py

@@ -474,7 +474,7 @@ class RunnableAssign(RunnableSerializable[dict[str, Any], dict[str, Any]]):
     ) -> dict[str, Any]:
         if not isinstance(input, dict):
             msg = "The input to RunnablePassthrough.assign() must be a dict."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         return {
             **input,
@@ -502,7 +502,7 @@ class RunnableAssign(RunnableSerializable[dict[str, Any], dict[str, Any]]):
     ) -> dict[str, Any]:
         if not isinstance(input, dict):
             msg = "The input to RunnablePassthrough.assign() must be a dict."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         return {
             **input,
@@ -555,7 +555,7 @@ class RunnableAssign(RunnableSerializable[dict[str, Any], dict[str, Any]]):
             for chunk in for_passthrough:
                 if not isinstance(chunk, dict):
                     msg = "The input to RunnablePassthrough.assign() must be a dict."
-                    raise ValueError(msg)
+                    raise ValueError(msg)  # noqa: TRY004
                 # remove mapper keys from passthrough chunk, to be overwritten by map
                 filtered = AddableDict(
                     {k: v for k, v in chunk.items() if k not in mapper_keys}
@@ -605,7 +605,7 @@ class RunnableAssign(RunnableSerializable[dict[str, Any], dict[str, Any]]):
         async for chunk in for_passthrough:
             if not isinstance(chunk, dict):
                 msg = "The input to RunnablePassthrough.assign() must be a dict."
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
 
             # remove mapper keys from passthrough chunk, to be overwritten by map output
             filtered = AddableDict(
@@ -708,7 +708,7 @@ class RunnablePick(RunnableSerializable[dict[str, Any], dict[str, Any]]):
     def _pick(self, input: dict[str, Any]) -> Any:
         if not isinstance(input, dict):
             msg = "The input to RunnablePassthrough.assign() must be a dict."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         if isinstance(self.keys, str):
             return input.get(self.keys)

libs/core/langchain_core/runnables/utils.py

@@ -397,9 +397,9 @@ def get_lambda_source(func: Callable) -> Optional[str]:
         tree = ast.parse(textwrap.dedent(code))
         visitor = GetLambdaSource()
         visitor.visit(tree)
-        return visitor.source if visitor.count == 1 else name
     except (SyntaxError, TypeError, OSError, SystemError):
         return name
+    return visitor.source if visitor.count == 1 else name
 
 
 @lru_cache(maxsize=256)
@@ -440,10 +440,11 @@ def get_function_nonlocals(func: Callable) -> list[Any]:
                                 break
                     else:
                         values.append(vv)
-        return values
     except (SyntaxError, TypeError, OSError, SystemError):
         return []
 
+    return values
+
 
 def indent_lines_after_first(text: str, prefix: str) -> str:
     """Indent all lines of text after the first line.

libs/core/langchain_core/tools/base.py

@@ -680,6 +680,7 @@ class ChildTool(BaseTool):
 
         content = None
         artifact = None
+        status = "success"
         error_to_raise: Union[Exception, KeyboardInterrupt, None] = None
         try:
             child_config = patch_config(config, callbacks=run_manager.get_child())
@@ -699,26 +700,25 @@ class ChildTool(BaseTool):
                         f"expected. Instead generated response of type: "
                         f"{type(response)}."
                     )
-                    raise ValueError(msg)
-                content, artifact = response
+                    error_to_raise = ValueError(msg)
+                else:
+                    content, artifact = response
             else:
                 content = response
-            status = "success"
         except (ValidationError, ValidationErrorV1) as e:
             if not self.handle_validation_error:
                 error_to_raise = e
             else:
                 content = _handle_validation_error(e, flag=self.handle_validation_error)
-            status = "error"
+                status = "error"
         except ToolException as e:
             if not self.handle_tool_error:
                 error_to_raise = e
             else:
                 content = _handle_tool_error(e, flag=self.handle_tool_error)
-            status = "error"
+                status = "error"
         except (Exception, KeyboardInterrupt) as e:
             error_to_raise = e
-            status = "error"
 
         if error_to_raise:
             run_manager.on_tool_error(error_to_raise)
@@ -789,6 +789,7 @@ class ChildTool(BaseTool):
         )
         content = None
         artifact = None
+        status = "success"
         error_to_raise: Optional[Union[Exception, KeyboardInterrupt]] = None
         try:
             tool_args, tool_kwargs = self._to_args_and_kwargs(tool_input, tool_call_id)
@@ -816,26 +817,25 @@ class ChildTool(BaseTool):
                         f"expected. Instead generated response of type: "
                         f"{type(response)}."
                     )
-                    raise ValueError(msg)
-                content, artifact = response
+                    error_to_raise = ValueError(msg)
+                else:
+                    content, artifact = response
             else:
                 content = response
-            status = "success"
         except ValidationError as e:
             if not self.handle_validation_error:
                 error_to_raise = e
             else:
                 content = _handle_validation_error(e, flag=self.handle_validation_error)
-            status = "error"
+                status = "error"
         except ToolException as e:
             if not self.handle_tool_error:
                 error_to_raise = e
             else:
                 content = _handle_tool_error(e, flag=self.handle_tool_error)
-            status = "error"
+                status = "error"
         except (Exception, KeyboardInterrupt) as e:
             error_to_raise = e
-            status = "error"
 
         if error_to_raise:
             await run_manager.on_tool_error(error_to_raise)
@@ -873,7 +873,7 @@ def _handle_validation_error(
             f"Got unexpected type of `handle_validation_error`. Expected bool, "
             f"str or callable. Received: {flag}"
         )
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
     return content
 
 
@@ -893,7 +893,7 @@ def _handle_tool_error(
             f"Got unexpected type of `handle_tool_error`. Expected bool, str "
             f"or callable. Received: {flag}"
         )
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
     return content
 
 

libs/core/langchain_core/tracers/evaluation.py

@@ -139,7 +139,7 @@ class EvaluatorCallbackHandler(BaseTracer):
                 f"{evaluator.__class__.__name__}: {repr(e)}",
                 exc_info=True,
             )
-            raise e
+            raise
         example_id = str(run.reference_example_id)
         with self.lock:
             for res in eval_results:

libs/core/langchain_core/utils/html.py

@@ -97,8 +97,7 @@ def extract_sub_links(
             if continue_on_failure:
                 logger.warning(f"Unable to load link {link}. Raised exception:\n\n{e}")
                 continue
-            else:
-                raise e
+            raise
 
     results = []
     for path in absolute_paths:

libs/core/langchain_core/utils/mustache.py

@@ -53,13 +53,14 @@ def grab_literal(template: str, l_del: str) -> tuple[str, str]:
         # Look for the next tag and move the template to it
         literal, template = template.split(l_del, 1)
         _CURRENT_LINE += literal.count("\n")
-        return (literal, template)
 
     # There are no more tags in the template?
     except ValueError:
         # Then the rest of the template is a literal
         return (template, "")
 
+    return (literal, template)
+
 
 def l_sa_check(template: str, literal: str, is_standalone: bool) -> bool:
     """Do a preliminary check to see if a tag could be a standalone.

libs/core/langchain_core/utils/usage.py

@@ -33,5 +33,5 @@ def _dict_int_op(
             msg = (
                 f"Unknown value types: {types}. Only dict and int values are supported."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
     return combined

libs/core/langchain_core/vectorstores/utils.py

@@ -54,11 +54,6 @@ def _cosine_similarity(x: Matrix, y: Matrix) -> np.ndarray:
         raise ValueError(msg)
     try:
         import simsimd as simd  # type: ignore
-
-        x = np.array(x, dtype=np.float32)
-        y = np.array(y, dtype=np.float32)
-        z = 1 - np.array(simd.cdist(x, y, metric="cosine"))
-        return z
     except ImportError:
         logger.debug(
             "Unable to import simsimd, defaulting to NumPy implementation. If you want "
@@ -72,6 +67,10 @@ def _cosine_similarity(x: Matrix, y: Matrix) -> np.ndarray:
         similarity[np.isnan(similarity) | np.isinf(similarity)] = 0.0
         return similarity
 
+    x = np.array(x, dtype=np.float32)
+    y = np.array(y, dtype=np.float32)
+    return 1 - np.array(simd.cdist(x, y, metric="cosine"))
+
 
 def maximal_marginal_relevance(
     query_embedding: np.ndarray,

libs/core/pyproject.toml

@@ -44,7 +44,7 @@ python = ">=3.12.4"
 [tool.poetry.extras]
 
 [tool.ruff.lint]
-select = [ "ASYNC", "B", "C4", "COM", "DJ", "E", "EM", "EXE", "F", "FLY", "FURB", "I", "ICN", "INT", "LOG", "N", "NPY", "PD", "PIE", "Q", "RSE", "S", "SIM", "SLOT", "T10", "T201", "TID", "UP", "W", "YTT",]
+select = [ "ASYNC", "B", "C4", "COM", "DJ", "E", "EM", "EXE", "F", "FLY", "FURB", "I", "ICN", "INT", "LOG", "N", "NPY", "PD", "PIE", "Q", "RSE", "S", "SIM", "SLOT", "T10", "T201", "TID", "TRY", "UP", "W", "YTT",]
 ignore = [ "COM812", "UP007", "S110", "S112",]
 
 [tool.coverage.run]

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

@@ -103,7 +103,7 @@ def _runnable(inputs: dict) -> str:
     if inputs["text"] == "bar":
         return "second"
     if isinstance(inputs["exception"], ValueError):
-        raise RuntimeError
+        raise RuntimeError  # noqa: TRY004
     return "third"
 
 

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

@@ -1600,7 +1600,7 @@ async def test_event_stream_with_retry() -> None:
     def fail(inputs: str) -> None:
         """Simple func."""
         msg = "fail"
-        raise Exception(msg)
+        raise ValueError(msg)
 
     chain = RunnableLambda(success) | RunnableLambda(fail).with_retry(
         stop_after_attempt=1,

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

@@ -1556,7 +1556,7 @@ async def test_event_stream_with_retry() -> None:
     def fail(inputs: str) -> None:
         """Simple func."""
         msg = "fail"
-        raise Exception(msg)
+        raise ValueError(msg)
 
     chain = RunnableLambda(success) | RunnableLambda(fail).with_retry(
         stop_after_attempt=1,
@@ -1906,7 +1906,7 @@ async def test_runnable_with_message_history() -> None:
                 return fn(*args, **kwargs)
             except Exception as e:
                 raised_errors.append(e)
-                raise e
+                raise
 
         return _get_output_messages
 
@@ -2097,7 +2097,7 @@ class StreamingRunnable(Runnable[Input, Output]):
             final_output = None
             for element in self.iterable:
                 if isinstance(element, BaseException):
-                    raise element
+                    raise element  # noqa: TRY301
                 yield element
 
                 if final_output is None:
@@ -2409,10 +2409,10 @@ async def test_break_astream_events() -> None:
             self.started = True
             try:
                 await asyncio.sleep(0.5)
-                return input
             except asyncio.CancelledError:
                 self.cancelled = True
                 raise
+            return input
 
         def reset(self) -> None:
             self.started = False
@@ -2474,10 +2474,10 @@ async def test_cancel_astream_events() -> None:
             self.started = True
             try:
                 await asyncio.sleep(0.5)
-                return input
             except asyncio.CancelledError:
                 self.cancelled = True
                 raise
+            return input
 
         def reset(self) -> None:
             self.started = False