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feat(langchain): add ruff rules G (#32029)

Browse Source 
https://docs.astral.sh/ruff/rules/#flake8-logging-format-g
This commit is contained in:
Christophe Bornet 2025-07-14 21:19:36 +02:00 committed by GitHub
parent 19fff8cba9
commit 953592d4f7
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GPG Key ID: B5690EEEBB952194
8 changed files with 56 additions and 30 deletions
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4
libs/langchain/langchain/agents/agent_iterator.py
View File

@ -147,7 +147,9 @@ class AgentExecutorIterator:
self.iterations += 1
self.time_elapsed = time.time() - self.start_time
logger.debug(
f"Agent Iterations: {self.iterations} ({self.time_elapsed:.2f}s elapsed)",
"Agent Iterations: %s (%.2fs elapsed)",
self.iterations,
self.time_elapsed,
)
def make_final_outputs(

18
libs/langchain/langchain/memory/entity.py
View File

@ -146,7 +146,9 @@ class UpstashRedisEntityStore(BaseEntityStore):
or default
or ""
)
logger.debug(f"Upstash Redis MEM get '{self.full_key_prefix}:{key}': '{res}'")
logger.debug(
"Upstash Redis MEM get '%s:%s': '%s'", self.full_key_prefix, key, res
)
return res
def set(self, key: str, value: Optional[str]) -> None:
@ -154,7 +156,11 @@ class UpstashRedisEntityStore(BaseEntityStore):
return self.delete(key)
self.redis_client.set(f"{self.full_key_prefix}:{key}", value, ex=self.ttl)
logger.debug(
f"Redis MEM set '{self.full_key_prefix}:{key}': '{value}' EX {self.ttl}",
"Redis MEM set '%s:%s': '%s' EX %s",
self.full_key_prefix,
key,
value,
self.ttl,
)
return None
@ -249,7 +255,7 @@ class RedisEntityStore(BaseEntityStore):
or default
or ""
)
logger.debug(f"REDIS MEM get '{self.full_key_prefix}:{key}': '{res}'")
logger.debug("REDIS MEM get '%s:%s': '%s'", self.full_key_prefix, key, res)
return res
def set(self, key: str, value: Optional[str]) -> None:
@ -257,7 +263,11 @@ class RedisEntityStore(BaseEntityStore):
return self.delete(key)
self.redis_client.set(f"{self.full_key_prefix}:{key}", value, ex=self.ttl)
logger.debug(
f"REDIS MEM set '{self.full_key_prefix}:{key}': '{value}' EX {self.ttl}",
"REDIS MEM set '%s:%s': '%s' EX %s",
self.full_key_prefix,
key,
value,
self.ttl,
)
return None

4
libs/langchain/langchain/retrievers/multi_query.py
View File

@ -128,7 +128,7 @@ class MultiQueryRetriever(BaseRetriever):
)
lines = response["text"] if isinstance(self.llm_chain, LLMChain) else response
if self.verbose:
logger.info(f"Generated queries: {lines}")
logger.info("Generated queries: %s", lines)
return lines
async def aretrieve_documents(
@ -194,7 +194,7 @@ class MultiQueryRetriever(BaseRetriever):
)
lines = response["text"] if isinstance(self.llm_chain, LLMChain) else response
if self.verbose:
logger.info(f"Generated queries: {lines}")
logger.info("Generated queries: %s", lines)
return lines
def retrieve_documents(

2
libs/langchain/langchain/retrievers/re_phraser.py
View File

@ -74,7 +74,7 @@ class RePhraseQueryRetriever(BaseRetriever):
query,
{"callbacks": run_manager.get_child()},
)
logger.info(f"Re-phrased question: {re_phrased_question}")
logger.info("Re-phrased question: %s", re_phrased_question)
return self.retriever.invoke(
re_phrased_question,
config={"callbacks": run_manager.get_child()},

4
libs/langchain/langchain/retrievers/self_query/base.py
View File

@ -320,7 +320,7 @@ class SelfQueryRetriever(BaseRetriever):
config={"callbacks": run_manager.get_child()},
)
if self.verbose:
logger.info(f"Generated Query: {structured_query}")
logger.info("Generated Query: %s", structured_query)
new_query, search_kwargs = self._prepare_query(query, structured_query)
return self._get_docs_with_query(new_query, search_kwargs)
@ -343,7 +343,7 @@ class SelfQueryRetriever(BaseRetriever):
config={"callbacks": run_manager.get_child()},
)
if self.verbose:
logger.info(f"Generated Query: {structured_query}")
logger.info("Generated Query: %s", structured_query)
new_query, search_kwargs = self._prepare_query(query, structured_query)
return await self._aget_docs_with_query(new_query, search_kwargs)

51
libs/langchain/langchain/smith/evaluation/runner_utils.py
View File

@ -207,7 +207,7 @@ def _wrap_in_chain_factory(
# It's an arbitrary function, wrap it in a RunnableLambda
user_func = cast(Callable, llm_or_chain_factory)
sig = inspect.signature(user_func)
logger.info(f"Wrapping function {sig} as RunnableLambda.")
logger.info("Wrapping function %s as RunnableLambda.", sig)
wrapped = RunnableLambda(user_func)
return lambda: wrapped
constructor = cast(Callable, llm_or_chain_factory)
@ -416,7 +416,7 @@ def _validate_example_inputs(
# Otherwise it's a runnable
_validate_example_inputs_for_chain(example, chain, input_mapper)
elif isinstance(chain, Runnable):
logger.debug(f"Skipping input validation for {chain}")
logger.debug("Skipping input validation for %s", chain)
## Shared Evaluator Setup Utilities
@ -461,16 +461,19 @@ def _determine_input_key(
input_key = config.input_key
if run_inputs and input_key not in run_inputs:
logger.warning(
f"Input key {input_key} not in chain's specified"
f" input keys {run_inputs}. Evaluation behavior may be undefined.",
"Input key %s not in chain's specified input keys %s. "
"Evaluation behavior may be undefined.",
input_key,
run_inputs,
)
elif run_inputs and len(run_inputs) == 1:
input_key = run_inputs[0]
elif run_inputs is not None and len(run_inputs) > 1:
logger.warning(
f"Chain expects multiple input keys: {run_inputs},"
f" Evaluator is likely to fail. Evaluation behavior may be undefined."
"Chain expects multiple input keys: %s,"
" Evaluator is likely to fail. Evaluation behavior may be undefined."
" Specify an input_key in the RunEvalConfig to avoid this warning.",
run_inputs,
)
return input_key
@ -485,16 +488,19 @@ def _determine_prediction_key(
prediction_key = config.prediction_key
if run_outputs and prediction_key not in run_outputs:
logger.warning(
f"Prediction key {prediction_key} not in chain's specified"
f" output keys {run_outputs}. Evaluation behavior may be undefined.",
"Prediction key %s not in chain's specified output keys %s. "
"Evaluation behavior may be undefined.",
prediction_key,
run_outputs,
)
elif run_outputs and len(run_outputs) == 1:
prediction_key = run_outputs[0]
elif run_outputs is not None and len(run_outputs) > 1:
logger.warning(
f"Chain expects multiple output keys: {run_outputs},"
f" Evaluation behavior may be undefined. Specify a prediction_key"
"Chain expects multiple output keys: %s,"
" Evaluation behavior may be undefined. Specify a prediction_key"
" in the RunEvalConfig to avoid this warning.",
run_outputs,
)
return prediction_key
@ -820,9 +826,11 @@ async def _arun_llm_or_chain(
result = output
except Exception as e:
logger.warning(
f"{chain_or_llm} failed for example {example.id} "
f"with inputs {example.inputs}"
f"\n{e!r}",
"%s failed for example %s with inputs %s\n%s",
chain_or_llm,
example.id,
example.inputs,
e,
)
result = EvalError(Error=e)
return result
@ -981,9 +989,12 @@ def _run_llm_or_chain(
except Exception as e:
error_type = type(e).__name__
logger.warning(
f"{chain_or_llm} failed for example {example.id} "
f"with inputs {example.inputs}"
f"\nError Type: {error_type}, Message: {e}",
"%s failed for example %s with inputs %s\nError Type: %s, Message: %s",
chain_or_llm,
example.id,
example.inputs,
error_type,
e,
)
result = EvalError(Error=e)
return result
@ -1113,7 +1124,9 @@ class _DatasetRunContainer:
project_id=self.project.id,
)
except Exception as e:
logger.error(f"Error running batch evaluator {evaluator!r}: {e}")
logger.exception(
"Error running batch evaluator %s: %s", repr(evaluator), e
)
return aggregate_feedback
def _collect_metrics(self) -> tuple[dict[str, _RowResult], dict[str, Run]]:
@ -1174,7 +1187,7 @@ class _DatasetRunContainer:
agg_feedback = results.get_aggregate_feedback()
_display_aggregate_results(agg_feedback)
except Exception as e:
logger.debug(f"Failed to print aggregate feedback: {e!r}")
logger.debug("Failed to print aggregate feedback: %s", e, exc_info=True)
try:
# Closing the project permits name changing and metric optimizations
self.client.update_project(
@ -1182,7 +1195,7 @@ class _DatasetRunContainer:
end_time=datetime.now(timezone.utc),
)
except Exception as e:
logger.debug(f"Failed to close project: {e!r}")
logger.debug("Failed to close project: %s", e, exc_info=True)
return results
@classmethod

1
libs/langchain/pyproject.toml
View File

@ -159,6 +159,7 @@ select = [
"FA", # flake8-future-annotations
"FBT", # flake8-boolean-trap
"FLY", # flake8-flynt
"G", # flake8-logging-format
"I", # isort
"ICN", # flake8-import-conventions
"INT", # flake8-gettext

2
libs/langchain/uv.lock
View File

@ -2882,7 +2882,7 @@ wheels = [
[[package]]
name = "langchain-openai"
version = "0.3.27"
version = "0.3.28"
source = { editable = "../partners/openai" }
dependencies = [
{ name = "langchain-core" },