feat(langchain): add ruff rules TRY (#32047)

See https://docs.astral.sh/ruff/rules/#tryceratops-try

* TRY004 (replace by TypeError) in main code is escaped with `noqa` to
not break backward compatibility. The rule is still interesting for new
code.
* TRY301 ignored at the moment. This one is quite hard to fix and I'm
not sure it's very interesting to activate it.

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

libs/langchain/langchain/_api/module_import.py

@@ -106,11 +106,12 @@ def create_importer(
                             "<https://python.langchain.com/docs/versions/v0_2/>"
                         ),
                     )
-                return result
             except Exception as e:
                 msg = f"module {new_module} has no attribute {name}"
                 raise AttributeError(msg) from e
 
+            return result
+
         if fallback_module:
             try:
                 module = importlib.import_module(fallback_module)
@@ -139,12 +140,13 @@ def create_importer(
                             "<https://python.langchain.com/docs/versions/v0_2/>"
                         ),
                     )
-                return result
 
             except Exception as e:
                 msg = f"module {fallback_module} has no attribute {name}"
                 raise AttributeError(msg) from e
 
+            return result
+
         msg = f"module {package} has no attribute {name}"
         raise AttributeError(msg)
 

libs/langchain/langchain/agents/agent.py

@@ -1380,7 +1380,7 @@ class AgentExecutor(Chain):
                 observation = self.handle_parsing_errors(e)
             else:
                 msg = "Got unexpected type of `handle_parsing_errors`"
-                raise ValueError(msg) from e
+                raise ValueError(msg) from e  # noqa: TRY004
             output = AgentAction("_Exception", observation, text)
             if run_manager:
                 run_manager.on_agent_action(output, color="green")
@@ -1519,7 +1519,7 @@ class AgentExecutor(Chain):
                 observation = self.handle_parsing_errors(e)
             else:
                 msg = "Got unexpected type of `handle_parsing_errors`"
-                raise ValueError(msg) from e
+                raise ValueError(msg) from e  # noqa: TRY004
             output = AgentAction("_Exception", observation, text)
             tool_run_kwargs = self._action_agent.tool_run_logging_kwargs()
             observation = await ExceptionTool().arun(

libs/langchain/langchain/agents/chat/base.py

@@ -55,7 +55,7 @@ class ChatAgent(Agent):
         agent_scratchpad = super()._construct_scratchpad(intermediate_steps)
         if not isinstance(agent_scratchpad, str):
             msg = "agent_scratchpad should be of type string."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         if agent_scratchpad:
             return (
                 f"This was your previous work "

libs/langchain/langchain/agents/openai_assistant/base.py

@@ -358,12 +358,12 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
             run = self._wait_for_run(run.id, run.thread_id)
         except BaseException as e:
             run_manager.on_chain_error(e)
-            raise e
+            raise
         try:
             response = self._get_response(run)
         except BaseException as e:
             run_manager.on_chain_error(e, metadata=run.dict())
-            raise e
+            raise
         else:
             run_manager.on_chain_end(response)
             return response
@@ -494,12 +494,12 @@ class OpenAIAssistantRunnable(RunnableSerializable[dict, OutputType]):
             run = await self._await_for_run(run.id, run.thread_id)
         except BaseException as e:
             run_manager.on_chain_error(e)
-            raise e
+            raise
         try:
             response = self._get_response(run)
         except BaseException as e:
             run_manager.on_chain_error(e, metadata=run.dict())
-            raise e
+            raise
         else:
             run_manager.on_chain_end(response)
             return response

libs/langchain/langchain/agents/output_parsers/openai_functions.py

@@ -87,7 +87,7 @@ class OpenAIFunctionsAgentOutputParser(AgentOutputParser):
     ) -> Union[AgentAction, AgentFinish]:
         if not isinstance(result[0], ChatGeneration):
             msg = "This output parser only works on ChatGeneration output"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         message = result[0].message
         return self._parse_ai_message(message)
 

libs/langchain/langchain/agents/output_parsers/openai_tools.py

@@ -61,7 +61,7 @@ class OpenAIToolsAgentOutputParser(MultiActionAgentOutputParser):
     ) -> Union[list[AgentAction], AgentFinish]:
         if not isinstance(result[0], ChatGeneration):
             msg = "This output parser only works on ChatGeneration output"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         message = result[0].message
         return parse_ai_message_to_openai_tool_action(message)
 

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

@@ -98,7 +98,7 @@ class ToolsAgentOutputParser(MultiActionAgentOutputParser):
     ) -> Union[list[AgentAction], AgentFinish]:
         if not isinstance(result[0], ChatGeneration):
             msg = "This output parser only works on ChatGeneration output"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         message = result[0].message
         return parse_ai_message_to_tool_action(message)
 

libs/langchain/langchain/agents/structured_chat/base.py

@@ -56,7 +56,7 @@ class StructuredChatAgent(Agent):
         agent_scratchpad = super()._construct_scratchpad(intermediate_steps)
         if not isinstance(agent_scratchpad, str):
             msg = "agent_scratchpad should be of type string."
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         if agent_scratchpad:
             return (
                 f"This was your previous work "

libs/langchain/langchain/agents/structured_chat/output_parser.py

@@ -71,12 +71,8 @@ class StructuredChatOutputParserWithRetries(AgentOutputParser):
     def parse(self, text: str) -> Union[AgentAction, AgentFinish]:
         try:
             if self.output_fixing_parser is not None:
-                parsed_obj: Union[AgentAction, AgentFinish] = (
-                    self.output_fixing_parser.parse(text)
-                )
-            else:
-                parsed_obj = self.base_parser.parse(text)
-            return parsed_obj
+                return self.output_fixing_parser.parse(text)
+            return self.base_parser.parse(text)
         except Exception as e:
             msg = f"Could not parse LLM output: {text}"
             raise OutputParserException(msg) from e

libs/langchain/langchain/chains/base.py

@@ -174,7 +174,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
             )
         except BaseException as e:
             run_manager.on_chain_error(e)
-            raise e
+            raise
         run_manager.on_chain_end(outputs)
 
         if include_run_info:
@@ -228,7 +228,7 @@ class Chain(RunnableSerializable[dict[str, Any], dict[str, Any]], ABC):
             )
         except BaseException as e:
             await run_manager.on_chain_error(e)
-            raise e
+            raise
         await run_manager.on_chain_end(outputs)
 
         if include_run_info:

libs/langchain/langchain/chains/combine_documents/map_rerank.py

@@ -127,7 +127,7 @@ class MapRerankDocumentsChain(BaseCombineDocumentsChain):
                 "Output parser of llm_chain should be a RegexParser,"
                 f" got {output_parser}"
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
         output_keys = output_parser.output_keys
         if self.rank_key not in output_keys:
             msg = (

libs/langchain/langchain/chains/conversational_retrieval/base.py

@@ -57,7 +57,7 @@ def _get_chat_history(chat_history: list[CHAT_TURN_TYPE]) -> str:
                 f"Unsupported chat history format: {type(dialogue_turn)}."
                 f" Full chat history: {chat_history} "
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
     return buffer
 
 

libs/langchain/langchain/chains/elasticsearch_database/base.py

@@ -164,12 +164,13 @@ class ElasticsearchDatabaseChain(Chain):
             chain_result: dict[str, Any] = {self.output_key: final_result}
             if self.return_intermediate_steps:
                 chain_result[INTERMEDIATE_STEPS_KEY] = intermediate_steps
-            return chain_result
         except Exception as exc:
             # Append intermediate steps to exception, to aid in logging and later
             # improvement of few shot prompt seeds
             exc.intermediate_steps = intermediate_steps  # type: ignore[attr-defined]
-            raise exc
+            raise
+
+        return chain_result
 
     @property
     def _chain_type(self) -> str:

libs/langchain/langchain/chains/llm.py

@@ -251,7 +251,7 @@ class LLMChain(Chain):
             response = self.generate(input_list, run_manager=run_manager)
         except BaseException as e:
             run_manager.on_chain_error(e)
-            raise e
+            raise
         outputs = self.create_outputs(response)
         run_manager.on_chain_end({"outputs": outputs})
         return outputs
@@ -276,7 +276,7 @@ class LLMChain(Chain):
             response = await self.agenerate(input_list, run_manager=run_manager)
         except BaseException as e:
             await run_manager.on_chain_error(e)
-            raise e
+            raise
         outputs = self.create_outputs(response)
         await run_manager.on_chain_end({"outputs": outputs})
         return outputs

libs/langchain/langchain/chains/loading.py

@@ -117,7 +117,7 @@ def _load_stuff_documents_chain(config: dict, **kwargs: Any) -> StuffDocumentsCh
 
     if not isinstance(llm_chain, LLMChain):
         msg = f"Expected LLMChain, got {llm_chain}"
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
 
     if "document_prompt" in config:
         prompt_config = config.pop("document_prompt")
@@ -150,7 +150,7 @@ def _load_map_reduce_documents_chain(
 
     if not isinstance(llm_chain, LLMChain):
         msg = f"Expected LLMChain, got {llm_chain}"
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
 
     if "reduce_documents_chain" in config:
         reduce_documents_chain = load_chain_from_config(

libs/langchain/langchain/chains/openai_functions/openapi.py

@@ -361,13 +361,13 @@ def get_openapi_chain(
             try:
                 spec = conversion(spec)
                 break
-            except ImportError as e:
-                raise e
+            except ImportError:
+                raise
             except Exception:  # noqa: S110
                 pass
         if isinstance(spec, str):
             msg = f"Unable to parse spec from source {spec}"
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
     openai_fns, call_api_fn = openapi_spec_to_openai_fn(spec)
     if not llm:
         msg = (

libs/langchain/langchain/chains/router/llm_router.py

@@ -125,7 +125,7 @@ class LLMRouterChain(RouterChain):
     def _validate_outputs(self, outputs: dict[str, Any]) -> None:
         super()._validate_outputs(outputs)
         if not isinstance(outputs["next_inputs"], dict):
-            raise ValueError
+            raise ValueError  # noqa: TRY004
 
     def _call(
         self,
@@ -178,10 +178,10 @@ class RouterOutputParser(BaseOutputParser[dict[str, str]]):
             parsed = parse_and_check_json_markdown(text, expected_keys)
             if not isinstance(parsed["destination"], str):
                 msg = "Expected 'destination' to be a string."
-                raise ValueError(msg)
+                raise TypeError(msg)
             if not isinstance(parsed["next_inputs"], self.next_inputs_type):
                 msg = f"Expected 'next_inputs' to be {self.next_inputs_type}."
-                raise ValueError(msg)
+                raise TypeError(msg)
             parsed["next_inputs"] = {self.next_inputs_inner_key: parsed["next_inputs"]}
             if (
                 parsed["destination"].strip().lower()
@@ -190,7 +190,7 @@ class RouterOutputParser(BaseOutputParser[dict[str, str]]):
                 parsed["destination"] = None
             else:
                 parsed["destination"] = parsed["destination"].strip()
-            return parsed
         except Exception as e:
             msg = f"Parsing text\n{text}\n raised following error:\n{e}"
             raise OutputParserException(msg) from e
+        return parsed

libs/langchain/langchain/embeddings/cache.py

@@ -340,7 +340,7 @@ class CacheBackedEmbeddings(Embeddings):
                 "key_encoder must be either 'blake2b', 'sha1', 'sha256', 'sha512' "
                 "or a callable that encodes keys."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
         document_embedding_store = EncoderBackedStore[str, list[float]](
             document_embedding_cache,

libs/langchain/langchain/evaluation/embedding_distance/base.py

@@ -23,11 +23,10 @@ from langchain.schema import RUN_KEY
 def _import_numpy() -> Any:
     try:
         import numpy as np
-
-        return np
     except ImportError as e:
         msg = "Could not import numpy, please install with `pip install numpy`."
         raise ImportError(msg) from e
+    return np
 
 
 logger = logging.getLogger(__name__)

libs/langchain/langchain/evaluation/parsing/base.py

@@ -74,9 +74,9 @@ class JsonValidityEvaluator(StringEvaluator):
         """
         try:
             parse_json_markdown(prediction, parser=json.loads)
-            return {"score": 1}
         except Exception as e:
             return {"score": 0, "reasoning": str(e)}
+        return {"score": 1}
 
 
 class JsonEqualityEvaluator(StringEvaluator):

libs/langchain/langchain/evaluation/parsing/json_schema.py

@@ -80,11 +80,9 @@ class JsonSchemaEvaluator(StringEvaluator):
 
         try:
             validate(instance=prediction, schema=schema)
-            return {
-                "score": True,
-            }
         except ValidationError as e:
             return {"score": False, "reasoning": repr(e)}
+        return {"score": True}
 
     @override
     def _evaluate_strings(

libs/langchain/langchain/indexes/_sql_record_manager.py

@@ -153,7 +153,7 @@ class SQLRecordManager(RecordManager):
         """Create the database schema."""
         if isinstance(self.engine, AsyncEngine):
             msg = "This method is not supported for async engines."
-            raise AssertionError(msg)
+            raise AssertionError(msg)  # noqa: TRY004
 
         Base.metadata.create_all(self.engine)
 
@@ -162,7 +162,7 @@ class SQLRecordManager(RecordManager):
 
         if not isinstance(self.engine, AsyncEngine):
             msg = "This method is not supported for sync engines."
-            raise AssertionError(msg)
+            raise AssertionError(msg)  # noqa: TRY004
 
         async with self.engine.begin() as session:
             await session.run_sync(Base.metadata.create_all)
@@ -173,7 +173,7 @@ class SQLRecordManager(RecordManager):
 
         if isinstance(self.session_factory, async_sessionmaker):
             msg = "This method is not supported for async engines."
-            raise AssertionError(msg)
+            raise AssertionError(msg)  # noqa: TRY004
 
         session = self.session_factory()
         try:
@@ -187,7 +187,7 @@ class SQLRecordManager(RecordManager):
 
         if not isinstance(self.session_factory, async_sessionmaker):
             msg = "This method is not supported for sync engines."
-            raise AssertionError(msg)
+            raise AssertionError(msg)  # noqa: TRY004
 
         async with self.session_factory() as session:
             yield session
@@ -221,7 +221,7 @@ class SQLRecordManager(RecordManager):
                 dt = float(dt)
             if not isinstance(dt, float):
                 msg = f"Unexpected type for datetime: {type(dt)}"
-                raise AssertionError(msg)
+                raise AssertionError(msg)  # noqa: TRY004
             return dt
 
     async def aget_time(self) -> float:
@@ -254,7 +254,7 @@ class SQLRecordManager(RecordManager):
                 dt = float(dt)
             if not isinstance(dt, float):
                 msg = f"Unexpected type for datetime: {type(dt)}"
-                raise AssertionError(msg)
+                raise AssertionError(msg)  # noqa: TRY004
             return dt
 
     def update(

libs/langchain/langchain/memory/entity.py

@@ -128,7 +128,7 @@ class UpstashRedisEntityStore(BaseEntityStore):
             self.redis_client = Redis(url=url, token=token)
         except Exception as exc:
             error_msg = "Upstash Redis instance could not be initiated"
-            logger.error(error_msg)
+            logger.exception(error_msg)
             raise RuntimeError(error_msg) from exc
 
         self.session_id = session_id
@@ -237,8 +237,8 @@ class RedisEntityStore(BaseEntityStore):
 
         try:
             self.redis_client = get_client(redis_url=url, decode_responses=True)
-        except redis.exceptions.ConnectionError as error:
-            logger.error(error)
+        except redis.exceptions.ConnectionError:
+            logger.exception("Redis client could not connect")
 
         self.session_id = session_id
         self.key_prefix = key_prefix

libs/langchain/langchain/model_laboratory.py

@@ -39,7 +39,7 @@ class ModelLaboratory:
                     "If you want to initialize with LLMs, use the `from_llms` method "
                     "instead (`ModelLaboratory.from_llms(...)`)"
                 )
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
             if len(chain.input_keys) != 1:
                 msg = (
                     "Currently only support chains with one input variable, "

libs/langchain/langchain/output_parsers/fix.py

@@ -70,7 +70,7 @@ class OutputFixingParser(BaseOutputParser[T]):
                 return self.parser.parse(completion)
             except OutputParserException as e:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "run"):
                     completion = self.retry_chain.run(
@@ -107,7 +107,7 @@ class OutputFixingParser(BaseOutputParser[T]):
                 return await self.parser.aparse(completion)
             except OutputParserException as e:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "arun"):
                     completion = await self.retry_chain.arun(

libs/langchain/langchain/output_parsers/retry.py

@@ -104,9 +104,9 @@ class RetryOutputParser(BaseOutputParser[T]):
         while retries <= self.max_retries:
             try:
                 return self.parser.parse(completion)
-            except OutputParserException as e:
+            except OutputParserException:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "run"):
                     completion = self.retry_chain.run(
@@ -141,7 +141,7 @@ class RetryOutputParser(BaseOutputParser[T]):
                 return await self.parser.aparse(completion)
             except OutputParserException as e:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "arun"):
                     completion = await self.retry_chain.arun(
@@ -232,7 +232,7 @@ class RetryWithErrorOutputParser(BaseOutputParser[T]):
                 return self.parser.parse(completion)
             except OutputParserException as e:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "run"):
                     completion = self.retry_chain.run(
@@ -260,7 +260,7 @@ class RetryWithErrorOutputParser(BaseOutputParser[T]):
                 return await self.parser.aparse(completion)
             except OutputParserException as e:
                 if retries == self.max_retries:
-                    raise e
+                    raise
                 retries += 1
                 if self.legacy and hasattr(self.retry_chain, "arun"):
                     completion = await self.retry_chain.arun(

libs/langchain/langchain/retrievers/document_compressors/base.py

@@ -48,7 +48,7 @@ class DocumentCompressorPipeline(BaseDocumentCompressor):
                 documents = _transformer.transform_documents(documents)
             else:
                 msg = f"Got unexpected transformer type: {_transformer}"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
         return documents
 
     async def acompress_documents(
@@ -78,5 +78,5 @@ class DocumentCompressorPipeline(BaseDocumentCompressor):
                 documents = await _transformer.atransform_documents(documents)
             else:
                 msg = f"Got unexpected transformer type: {_transformer}"
-                raise ValueError(msg)
+                raise ValueError(msg)  # noqa: TRY004
         return documents

libs/langchain/langchain/retrievers/ensemble.py

@@ -116,7 +116,7 @@ class EnsembleRetriever(BaseRetriever):
             result = self.rank_fusion(input, run_manager=run_manager, config=config)
         except Exception as e:
             run_manager.on_retriever_error(e)
-            raise e
+            raise
         else:
             run_manager.on_retriever_end(
                 result,
@@ -157,7 +157,7 @@ class EnsembleRetriever(BaseRetriever):
             )
         except Exception as e:
             await run_manager.on_retriever_error(e)
-            raise e
+            raise
         else:
             await run_manager.on_retriever_end(
                 result,

libs/langchain/langchain/smith/evaluation/runner_utils.py

@@ -558,7 +558,7 @@ def _construct_run_evaluator(
         return run_evaluator_dec(eval_config)
     else:
         msg = f"Unknown evaluator type: {type(eval_config)}"
-        raise ValueError(msg)
+        raise ValueError(msg)  # noqa: TRY004
 
     if isinstance(evaluator_, StringEvaluator):
         if evaluator_.requires_reference and reference_key is None:
@@ -668,7 +668,7 @@ def _load_run_evaluators(
                 f"Unsupported custom evaluator: {custom_evaluator}."
                 f" Expected RunEvaluator or StringEvaluator."
             )
-            raise ValueError(msg)
+            raise ValueError(msg)  # noqa: TRY004
 
     return run_evaluators
 
@@ -1040,7 +1040,7 @@ def _prepare_eval_run(
         )
     except (HTTPError, ValueError, LangSmithError) as e:
         if "already exists " not in str(e):
-            raise e
+            raise
         uid = uuid.uuid4()
         example_msg = f"""
 run_on_dataset(
@@ -1123,9 +1123,9 @@ class _DatasetRunContainer:
                         run_id=None,
                         project_id=self.project.id,
                     )
-                except Exception as e:
+                except Exception:
                     logger.exception(
-                        "Error running batch evaluator %s: %s", repr(evaluator), e
+                        "Error running batch evaluator %s", repr(evaluator)
                     )
         return aggregate_feedback
 

libs/langchain/pyproject.toml

@@ -181,6 +181,7 @@ select = [
     "T10",    # flake8-debugger
     "T20",    # flake8-print
     "TID",    # flake8-tidy-imports
+    "TRY",    # tryceratops
     "UP",     # pyupgrade
     "W",      # pycodestyle warning
     "YTT",    # flake8-2020
@@ -201,6 +202,9 @@ ignore = [
     "RUF012",  # Doesn't play well with Pydantic
     "SLF001",  # Private member access
     "UP007",   # pyupgrade: non-pep604-annotation-union
+
+    # TODO
+    "TRY301", # tryceratops: raise-within-try
 ]
 unfixable = ["B028"] # People should intentionally tune the stacklevel
 

libs/langchain/tests/unit_tests/llms/fake_chat_model.py

@@ -105,7 +105,7 @@ class GenericFakeChatModel(BaseChatModel):
                 f"Expected generate to return a ChatResult, "
                 f"but got {type(chat_result)} instead."
             )
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         message = chat_result.generations[0].message
 
@@ -114,7 +114,7 @@ class GenericFakeChatModel(BaseChatModel):
                 f"Expected invoke to return an AIMessage, "
                 f"but got {type(message)} instead."
             )
-            raise ValueError(msg)
+            raise TypeError(msg)
 
         content = message.content
 

libs/langchain/uv.lock

@@ -2721,7 +2721,7 @@ dependencies = [
 requires-dist = [
     { name = "jsonpatch", specifier = ">=1.33,<2.0" },
     { name = "langsmith", specifier = ">=0.3.45" },
-    { name = "packaging", specifier = ">=23.2,<25" },
+    { name = "packaging", specifier = ">=23.2" },
     { name = "pydantic", specifier = ">=2.7.4" },
     { name = "pyyaml", specifier = ">=5.3" },
     { name = "tenacity", specifier = ">=8.1.0,!=8.4.0,<10.0.0" },