langchain: Add ruff rules SIM (#31881)

See https://docs.astral.sh/ruff/rules/#flake8-simplify-sim

Co-authored-by: Mason Daugherty <mason@langchain.dev>

libs/langchain/langchain/_api/module_import.py

@@ -84,13 +84,13 @@ def create_importer(
                     not is_interactive_env()
                     and deprecated_lookups
                     and name in deprecated_lookups
-                ):
                     # Depth 3:
                     # internal.py
                     # module_import.py
                     # Module in langchain that uses this function
                     # [calling code] whose frame we want to inspect.
-                    if not internal.is_caller_internal(depth=3):
+                    and not internal.is_caller_internal(depth=3)
+                ):
                     warn_deprecated(
                         since="0.1",
                         pending=False,
@@ -115,13 +115,15 @@ def create_importer(
             try:
                 module = importlib.import_module(fallback_module)
                 result = getattr(module, name)
-                if not is_interactive_env():
+                if (
+                    not is_interactive_env()
                     # Depth 3:
                     # internal.py
                     # module_import.py
                     # Module in langchain that uses this function
                     # [calling code] whose frame we want to inspect.
-                    if not internal.is_caller_internal(depth=3):
+                    and not internal.is_caller_internal(depth=3)
+                ):
                     warn_deprecated(
                         since="0.1",
                         pending=False,

libs/langchain/langchain/agents/agent.py

@@ -4,6 +4,7 @@ from __future__ import annotations
 
 import asyncio
 import builtins
+import contextlib
 import json
 import logging
 import time
@@ -196,10 +197,7 @@ class BaseSingleActionAgent(BaseModel):
             agent.agent.save(file_path="path/agent.yaml")
         """
         # Convert file to Path object.
-        if isinstance(file_path, str):
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
 
         directory_path = save_path.parent
         directory_path.mkdir(parents=True, exist_ok=True)
@@ -322,10 +320,8 @@ class BaseMultiActionAgent(BaseModel):
     def dict(self, **kwargs: Any) -> builtins.dict:
         """Return dictionary representation of agent."""
         _dict = super().model_dump()
-        try:
+        with contextlib.suppress(NotImplementedError):
             _dict["_type"] = str(self._agent_type)
-        except NotImplementedError:
-            pass
         return _dict
 
     def save(self, file_path: Union[Path, str]) -> None:
@@ -345,10 +341,7 @@ class BaseMultiActionAgent(BaseModel):
             agent.agent.save(file_path="path/agent.yaml")
         """
         # Convert file to Path object.
-        if isinstance(file_path, str):
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
 
         # Fetch dictionary to save
         agent_dict = self.dict()
@@ -1133,8 +1126,9 @@ class AgentExecutor(Chain):
         agent = self.agent
         tools = self.tools
         allowed_tools = agent.get_allowed_tools()  # type: ignore[union-attr]
-        if allowed_tools is not None:
+        if allowed_tools is not None and set(allowed_tools) != set(
-            if set(allowed_tools) != set([tool.name for tool in tools]):
+            [tool.name for tool in tools]
+        ):
             msg = (
                 f"Allowed tools ({allowed_tools}) different than "
                 f"provided tools ({[tool.name for tool in tools]})"
@@ -1272,13 +1266,7 @@ class AgentExecutor(Chain):
     def _should_continue(self, iterations: int, time_elapsed: float) -> bool:
         if self.max_iterations is not None and iterations >= self.max_iterations:
             return False
-        if (
+        return self.max_execution_time is None or time_elapsed < self.max_execution_time
-            self.max_execution_time is not None
-            and time_elapsed >= self.max_execution_time
-        ):
-            return False
-
-        return True
 
     def _return(
         self,
@@ -1410,10 +1398,7 @@ class AgentExecutor(Chain):
             return
 
         actions: list[AgentAction]
-        if isinstance(output, AgentAction):
+        actions = [output] if isinstance(output, AgentAction) else output
-            actions = [output]
-        else:
-            actions = output
         for agent_action in actions:
             yield agent_action
         for agent_action in actions:
@@ -1547,10 +1532,7 @@ class AgentExecutor(Chain):
             return
 
         actions: list[AgentAction]
-        if isinstance(output, AgentAction):
+        actions = [output] if isinstance(output, AgentAction) else output
-            actions = [output]
-        else:
-            actions = output
         for agent_action in actions:
             yield agent_action
 
@@ -1728,8 +1710,10 @@ class AgentExecutor(Chain):
         if len(self._action_agent.return_values) > 0:
             return_value_key = self._action_agent.return_values[0]
         # Invalid tools won't be in the map, so we return False.
-        if agent_action.tool in name_to_tool_map:
+        if (
-            if name_to_tool_map[agent_action.tool].return_direct:
+            agent_action.tool in name_to_tool_map
+            and name_to_tool_map[agent_action.tool].return_direct
+        ):
             return AgentFinish(
                 {return_value_key: observation},
                 "",

libs/langchain/langchain/agents/initialize.py

@@ -1,5 +1,6 @@
 """Load agent."""
 
+import contextlib
 from collections.abc import Sequence
 from typing import Any, Optional
 
@@ -81,11 +82,9 @@ def initialize_agent(
         agent_obj = load_agent(
             agent_path, llm=llm, tools=tools, callback_manager=callback_manager
         )
-        try:
+        with contextlib.suppress(NotImplementedError):
             # TODO: Add tags from the serialized object directly.
             tags_.append(agent_obj._agent_type)
-        except NotImplementedError:
-            pass
     else:
         msg = (
             "Somehow both `agent` and `agent_path` are None, this should never happen."

libs/langchain/langchain/agents/loading.py

@@ -128,10 +128,7 @@ def _load_agent_from_file(
     """Load agent from file."""
     valid_suffixes = {"json", "yaml"}
     # Convert file to Path object.
-    if isinstance(file, str):
+    file_path = Path(file) if isinstance(file, str) else file
-        file_path = Path(file)
-    else:
-        file_path = file
     # Load from either json or yaml.
     if file_path.suffix[1:] == "json":
         with open(file_path) as f:

libs/langchain/langchain/agents/openai_functions_agent/base.py

@@ -230,10 +230,7 @@ class OpenAIFunctionsAgent(BaseSingleActionAgent):
         """
         _prompts = extra_prompt_messages or []
         messages: list[Union[BaseMessagePromptTemplate, BaseMessage]]
-        if system_message:
+        messages = [system_message] if system_message else []
-            messages = [system_message]
-        else:
-            messages = []
 
         messages.extend(
             [

libs/langchain/langchain/agents/openai_functions_multi_agent/base.py

@@ -278,10 +278,7 @@ class OpenAIMultiFunctionsAgent(BaseMultiActionAgent):
         """
         _prompts = extra_prompt_messages or []
         messages: list[Union[BaseMessagePromptTemplate, BaseMessage]]
-        if system_message:
+        messages = [system_message] if system_message else []
-            messages = [system_message]
-        else:
-            messages = []
 
         messages.extend(
             [

libs/langchain/langchain/agents/output_parsers/tools.py

@@ -60,10 +60,7 @@ def parse_ai_message_to_tool_action(
         # Open AI does not support passing in a JSON array as an argument.
         function_name = tool_call["name"]
         _tool_input = tool_call["args"]
-        if "__arg1" in _tool_input:
+        tool_input = _tool_input.get("__arg1", _tool_input)
-            tool_input = _tool_input["__arg1"]
-        else:
-            tool_input = _tool_input
 
         content_msg = f"responded: {message.content}\n" if message.content else "\n"
         log = f"\nInvoking: `{function_name}` with `{tool_input}`\n{content_msg}\n"

libs/langchain/langchain/chains/base.py

@@ -1,6 +1,7 @@
 """Base interface that all chains should implement."""
 
 import builtins
+import contextlib
 import inspect
 import json
 import logging
@@ -727,10 +728,8 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
                 # -> {"_type": "foo", "verbose": False, ...}
         """
         _dict = super().dict(**kwargs)
-        try:
+        with contextlib.suppress(NotImplementedError):
             _dict["_type"] = self._chain_type
-        except NotImplementedError:
-            pass
         return _dict
 
     def save(self, file_path: Union[Path, str]) -> None:
@@ -758,10 +757,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
             raise NotImplementedError(msg)
 
         # Convert file to Path object.
-        if isinstance(file_path, str):
+        save_path = Path(file_path) if isinstance(file_path, str) else file_path
-            save_path = Path(file_path)
-        else:
-            save_path = file_path
 
         directory_path = save_path.parent
         directory_path.mkdir(parents=True, exist_ok=True)

libs/langchain/langchain/chains/loading.py

@@ -683,10 +683,7 @@ def load_chain(path: Union[str, Path], **kwargs: Any) -> Chain:
 def _load_chain_from_file(file: Union[str, Path], **kwargs: Any) -> Chain:
     """Load chain from file."""
     # Convert file to Path object.
-    if isinstance(file, str):
+    file_path = Path(file) if isinstance(file, str) else file
-        file_path = Path(file)
-    else:
-        file_path = file
     # Load from either json or yaml.
     if file_path.suffix == ".json":
         with open(file_path) as f:

libs/langchain/langchain/chains/moderation.py

@@ -95,10 +95,7 @@ class OpenAIModerationChain(Chain):
         return [self.output_key]
 
     def _moderate(self, text: str, results: Any) -> str:
-        if self.openai_pre_1_0:
+        condition = results["flagged"] if self.openai_pre_1_0 else results.flagged
-            condition = results["flagged"]
-        else:
-            condition = results.flagged
         if condition:
             error_str = "Text was found that violates OpenAI's content policy."
             if self.error:

libs/langchain/langchain/chains/query_constructor/parser.py

@@ -108,8 +108,10 @@ class QueryTransformer(Transformer):
 
     def _match_func_name(self, func_name: str) -> Union[Operator, Comparator]:
         if func_name in set(Comparator):
-            if self.allowed_comparators is not None:
+            if (
-                if func_name not in self.allowed_comparators:
+                self.allowed_comparators is not None
+                and func_name not in self.allowed_comparators
+            ):
                 msg = (
                     f"Received disallowed comparator {func_name}. Allowed "
                     f"comparators are {self.allowed_comparators}"
@@ -117,8 +119,10 @@ class QueryTransformer(Transformer):
                 raise ValueError(msg)
             return Comparator(func_name)
         elif func_name in set(Operator):
-            if self.allowed_operators is not None:
+            if (
-                if func_name not in self.allowed_operators:
+                self.allowed_operators is not None
+                and func_name not in self.allowed_operators
+            ):
                 msg = (
                     f"Received disallowed operator {func_name}. Allowed operators"
                     f" are {self.allowed_operators}"

libs/langchain/langchain/evaluation/agents/trajectory_eval_chain.py

@@ -244,10 +244,7 @@ The following is the expected answer. Use this to measure correctness:
         if not isinstance(llm, BaseChatModel):
             msg = "Only chat models supported by the current trajectory eval"
             raise NotImplementedError(msg)
-        if agent_tools:
+        prompt = EVAL_CHAT_PROMPT if agent_tools else TOOL_FREE_EVAL_CHAT_PROMPT
-            prompt = EVAL_CHAT_PROMPT
-        else:
-            prompt = TOOL_FREE_EVAL_CHAT_PROMPT
         eval_chain = LLMChain(llm=llm, prompt=prompt)
         return cls(
             agent_tools=agent_tools,  # type: ignore[arg-type]

libs/langchain/langchain/memory/combined.py

@@ -36,8 +36,7 @@ class CombinedMemory(BaseMemory):
     def check_input_key(cls, value: list[BaseMemory]) -> list[BaseMemory]:
         """Check that if memories are of type BaseChatMemory that input keys exist."""
         for val in value:
-            if isinstance(val, BaseChatMemory):
+            if isinstance(val, BaseChatMemory) and val.input_key is None:
-                if val.input_key is None:
                 warnings.warn(
                     "When using CombinedMemory, "
                     "input keys should be so the input is known. "

libs/langchain/langchain/model_laboratory.py

@@ -51,9 +51,7 @@ class ModelLaboratory:
                     "Currently only support chains with one output variable, "
                     f"got {chain.output_keys}"
                 )
-                raise ValueError(msg)
+        if names is not None and len(names) != len(chains):
-        if names is not None:
-            if len(names) != len(chains):
             msg = "Length of chains does not match length of names."
             raise ValueError(msg)
         self.chains = chains
@@ -93,10 +91,7 @@ class ModelLaboratory:
         """
         print(f"\033[1mInput:\033[0m\n{text}\n")  # noqa: T201
         for i, chain in enumerate(self.chains):
-            if self.names is not None:
+            name = self.names[i] if self.names is not None else str(chain)
-                name = self.names[i]
-            else:
-                name = str(chain)
             print_text(name, end="\n")
             output = chain.run(text)
             print_text(output, color=self.chain_colors[str(i)], end="\n\n")

libs/langchain/langchain/output_parsers/loading.py

@@ -10,8 +10,7 @@ def load_output_parser(config: dict) -> dict:
     Returns:
         config dict with output parser loaded
     """
-    if "output_parsers" in config:
+    if "output_parsers" in config and config["output_parsers"] is not None:
-        if config["output_parsers"] is not None:
         _config = config["output_parsers"]
         output_parser_type = _config["_type"]
         if output_parser_type == "regex_parser":

libs/langchain/langchain/output_parsers/yaml.py

@@ -27,12 +27,8 @@ class YamlOutputParser(BaseOutputParser[T]):
         try:
             # Greedy search for 1st yaml candidate.
             match = re.search(self.pattern, text.strip())
-            yaml_str = ""
-            if match:
-                yaml_str = match.group("yaml")
-            else:
             # If no backticks were present, try to parse the entire output as yaml.
-                yaml_str = text
+            yaml_str = match.group("yaml") if match else text
 
             json_object = yaml.safe_load(yaml_str)
             if hasattr(self.pydantic_object, "model_validate"):

libs/langchain/langchain/retrievers/multi_query.py

@@ -123,10 +123,7 @@ class MultiQueryRetriever(BaseRetriever):
         response = await self.llm_chain.ainvoke(
             {"question": question}, config={"callbacks": run_manager.get_child()}
         )
-        if isinstance(self.llm_chain, LLMChain):
+        lines = response["text"] if isinstance(self.llm_chain, LLMChain) else response
-            lines = response["text"]
-        else:
-            lines = response
         if self.verbose:
             logger.info(f"Generated queries: {lines}")
         return lines
@@ -186,10 +183,7 @@ class MultiQueryRetriever(BaseRetriever):
         response = self.llm_chain.invoke(
             {"question": question}, config={"callbacks": run_manager.get_child()}
         )
-        if isinstance(self.llm_chain, LLMChain):
+        lines = response["text"] if isinstance(self.llm_chain, LLMChain) else response
-            lines = response["text"]
-        else:
-            lines = response
         if self.verbose:
             logger.info(f"Generated queries: {lines}")
         return lines

libs/langchain/langchain/smith/evaluation/config.py

@@ -57,9 +57,7 @@ class EvalConfig(BaseModel):
         """
         kwargs = {}
         for field, val in self:
-            if field == "evaluator_type":
+            if field == "evaluator_type" or val is None:
-                continue
-            elif val is None:
                 continue
             kwargs[field] = val
         return kwargs

libs/langchain/pyproject.toml

@@ -143,7 +143,7 @@ ignore-regex = ".*(Stati Uniti|Tense=Pres).*"
 ignore-words-list = "momento,collison,ned,foor,reworkd,parth,whats,aapply,mysogyny,unsecure,damon,crate,aadd,symbl,precesses,accademia,nin"
 
 [tool.ruff.lint]
-select = ["A", "E", "F", "I", "EM", "PGH003", "PIE", "T201", "D", "UP", "S", "W"]
+select = ["A", "E", "F", "I", "EM", "PGH003", "PIE", "SIM", "T201", "D", "UP", "S", "W"]
 pydocstyle.convention = "google"
 pyupgrade.keep-runtime-typing = true
 

libs/langchain/tests/unit_tests/agents/test_agent.py

@@ -2,6 +2,8 @@
 
 import asyncio
 import json
+import operator
+from functools import reduce
 from itertools import cycle
 from typing import Any, Optional, Union, cast
 
@@ -520,14 +522,7 @@ async def test_runnable_agent() -> None:
     assert messages != []
 
     # Aggregate state
-    run_log = None
+    run_log = reduce(operator.add, results)
-
-    for result in results:
-        if run_log is None:
-            run_log = result
-        else:
-            # `+` is defined for RunLogPatch
-            run_log = run_log + result
 
     assert isinstance(run_log, RunLog)
 

libs/langchain/tests/unit_tests/chains/test_memory.py

@@ -17,7 +17,7 @@ def test_simple_memory() -> None:
     output = memory.load_memory_variables({})
 
     assert output == {"baz": "foo"}
-    assert ["baz"] == memory.memory_variables
+    assert memory.memory_variables == ["baz"]
 
 
 @pytest.mark.parametrize(

libs/langchain/tests/unit_tests/embeddings/test_caching.py

@@ -1,5 +1,6 @@
 """Embeddings tests."""
 
+import contextlib
 import hashlib
 import importlib
 import warnings
@@ -75,10 +76,8 @@ def test_embed_documents(cache_embeddings: CacheBackedEmbeddings) -> None:
 def test_embed_documents_batch(cache_embeddings_batch: CacheBackedEmbeddings) -> None:
     # "RAISE_EXCEPTION" forces a failure in batch 2
     texts = ["1", "22", "a", "333", "RAISE_EXCEPTION"]
-    try:
+    with contextlib.suppress(ValueError):
         cache_embeddings_batch.embed_documents(texts)
-    except ValueError:
-        pass
     keys = list(cache_embeddings_batch.document_embedding_store.yield_keys())
     # only the first batch of three embeddings should exist
     assert len(keys) == 3
@@ -122,10 +121,8 @@ async def test_aembed_documents_batch(
 ) -> None:
     # "RAISE_EXCEPTION" forces a failure in batch 2
     texts = ["1", "22", "a", "333", "RAISE_EXCEPTION"]
-    try:
+    with contextlib.suppress(ValueError):
         await cache_embeddings_batch.aembed_documents(texts)
-    except ValueError:
-        pass
     keys = [
         key
         async for key in cache_embeddings_batch.document_embedding_store.ayield_keys()

libs/langchain/tests/unit_tests/evaluation/string_distance/test_base.py

@@ -70,7 +70,7 @@ def test_non_zero_distance(distance: StringDistance, normalize_score: bool) -> N
     reference = "I like apples."
     result = eval_chain.evaluate_strings(prediction=prediction, reference=reference)
     assert "score" in result
-    assert 0 < result["score"]
+    assert result["score"] > 0
     if normalize_score:
         assert result["score"] < 1.0
 

libs/langchain/tests/unit_tests/output_parsers/test_combining_parser.py

@@ -45,7 +45,7 @@ def test_combining_dict_result() -> None:
     ]
     combining_parser = CombiningOutputParser(parsers=parsers)
     result_dict = combining_parser.parse(DEF_README)
-    assert DEF_EXPECTED_RESULT == result_dict
+    assert result_dict == DEF_EXPECTED_RESULT
 
 
 def test_combining_output_parser_output_type() -> None:

libs/langchain/tests/unit_tests/output_parsers/test_pandas_dataframe_parser.py

@@ -47,7 +47,7 @@ def test_pandas_output_parser_col_first_elem() -> None:
 def test_pandas_output_parser_col_multi_elem() -> None:
     expected_output = {"chicken": pd.Series([1, 2], name="chicken", dtype="int64")}
     actual_output = parser.parse("column:chicken[0, 1]")
-    for key in actual_output.keys():
+    for key in actual_output:
         assert expected_output["chicken"].equals(actual_output[key])
 
 

libs/langchain/tests/unit_tests/output_parsers/test_regex.py

@@ -23,7 +23,7 @@ def test_regex_parser_parse() -> None:
         output_keys=["confidence", "explanation"],
         default_output_key="noConfidence",
     )
-    assert DEF_EXPECTED_RESULT == parser.parse(DEF_README)
+    assert parser.parse(DEF_README) == DEF_EXPECTED_RESULT
 
 
 def test_regex_parser_output_type() -> None:

libs/langchain/tests/unit_tests/output_parsers/test_regex_dict.py

@@ -35,7 +35,7 @@ def test_regex_dict_result() -> None:
     )
     result_dict = regex_dict_parser.parse(DEF_README)
     print("parse_result:", result_dict)  # noqa: T201
-    assert DEF_EXPECTED_RESULT == result_dict
+    assert result_dict == DEF_EXPECTED_RESULT
 
 
 def test_regex_dict_output_type() -> None:

libs/langchain/tests/unit_tests/output_parsers/test_yaml_parser.py

@@ -76,7 +76,7 @@ def test_yaml_output_parser(result: str) -> None:
 
     model = yaml_parser.parse(result)
     print("parse_result:", result)  # noqa: T201
-    assert DEF_EXPECTED_RESULT == model
+    assert model == DEF_EXPECTED_RESULT
 
 
 def test_yaml_output_parser_fail() -> None:

libs/langchain/tests/unit_tests/test_imports.py

@@ -124,8 +124,11 @@ def extract_deprecated_lookup(file_path: str) -> Optional[dict[str, Any]]:
     for node in ast.walk(tree):
         if isinstance(node, ast.Assign):
             for target in node.targets:
-                if isinstance(target, ast.Name) and target.id == "DEPRECATED_LOOKUP":
+                if (
-                    if isinstance(node.value, ast.Dict):
+                    isinstance(target, ast.Name)
+                    and target.id == "DEPRECATED_LOOKUP"
+                    and isinstance(node.value, ast.Dict)
+                ):
                     return _dict_from_ast(node.value)
     return None
 
@@ -156,8 +159,10 @@ def _literal_eval_str(node: ast.AST) -> str:
     Returns:
         str: The corresponding string value.
     """
-    if isinstance(node, ast.Constant):  # Python 3.8+
+    if (
-        if isinstance(node.value, str):
+        isinstance(node, ast.Constant)  # Python 3.8+
+        and isinstance(node.value, str)
+    ):
         return node.value
     msg = f"Invalid DEPRECATED_LOOKUP format: expected str, got {type(node).__name__}"
     raise AssertionError(msg)