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Refactor: use logger = logging.getLogger(__name__) in logging (#24515)

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Co-authored-by: Yongtao Huang <99629139+hyongtao-db@users.noreply.github.com>
Co-authored-by: autofix-ci[bot] <114827586+autofix-ci[bot]@users.noreply.github.com>
Co-authored-by: crazywoola <100913391+crazywoola@users.noreply.github.com>
This commit is contained in:
Yongtao Huang
2025-08-26 18:10:31 +08:00
committed by GitHub
parent 8af2ae973f
commit fa753239ad
102 changed files with 565 additions and 401 deletions
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16
api/core/llm_generator/llm_generator.py
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@@ -31,6 +31,8 @@ from core.workflow.entities.workflow_node_execution import WorkflowNodeExecution
from core.workflow.graph_engine.entities.event import AgentLogEvent
from models import App, Message, WorkflowNodeExecutionModel, db
logger = logging.getLogger(__name__)
class LLMGenerator:
@classmethod
@@ -68,7 +70,7 @@ class LLMGenerator:
result_dict = json.loads(cleaned_answer)
answer = result_dict["Your Output"]
except json.JSONDecodeError as e:
logging.exception("Failed to generate name after answer, use query instead")
logger.exception("Failed to generate name after answer, use query instead")
answer = query
name = answer.strip()
@@ -125,7 +127,7 @@ class LLMGenerator:
except InvokeError:
questions = []
except Exception:
logging.exception("Failed to generate suggested questions after answer")
logger.exception("Failed to generate suggested questions after answer")
questions = []
return questions
@@ -173,7 +175,7 @@ class LLMGenerator:
error = str(e)
error_step = "generate rule config"
except Exception as e:
logging.exception("Failed to generate rule config, model: %s", model_config.get("name"))
logger.exception("Failed to generate rule config, model: %s", model_config.get("name"))
rule_config["error"] = str(e)
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
@@ -270,7 +272,7 @@ class LLMGenerator:
error_step = "generate conversation opener"
except Exception as e:
logging.exception("Failed to generate rule config, model: %s", model_config.get("name"))
logger.exception("Failed to generate rule config, model: %s", model_config.get("name"))
rule_config["error"] = str(e)
rule_config["error"] = f"Failed to {error_step}. Error: {error}" if error else ""
@@ -319,7 +321,7 @@ class LLMGenerator:
error = str(e)
return {"code": "", "language": code_language, "error": f"Failed to generate code. Error: {error}"}
except Exception as e:
logging.exception(
logger.exception(
"Failed to invoke LLM model, model: %s, language: %s", model_config.get("name"), code_language
)
return {"code": "", "language": code_language, "error": f"An unexpected error occurred: {str(e)}"}
@@ -392,7 +394,7 @@ class LLMGenerator:
error = str(e)
return {"output": "", "error": f"Failed to generate JSON Schema. Error: {error}"}
except Exception as e:
logging.exception("Failed to invoke LLM model, model: %s", model_config.get("name"))
logger.exception("Failed to invoke LLM model, model: %s", model_config.get("name"))
return {"output": "", "error": f"An unexpected error occurred: {str(e)}"}
@staticmethod
@@ -570,5 +572,5 @@ class LLMGenerator:
error = str(e)
return {"error": f"Failed to generate code. Error: {error}"}
except Exception as e:
logging.exception("Failed to invoke LLM model, model: %s", model_config.get("name"), exc_info=e)
logger.exception("Failed to invoke LLM model, model: " + json.dumps(model_config.get("name")), exc_info=e)
return {"error": f"An unexpected error occurred: {str(e)}"}