perf(prompt_opt): improve prompt optimization and model output quality

api/app/core/workflow/nodes/configs.py

@@ -19,6 +19,7 @@ from app.core.workflow.nodes.llm.config import LLMNodeConfig, MessageConfig
 from app.core.workflow.nodes.start.config import StartNodeConfig
 from app.core.workflow.nodes.transform.config import TransformNodeConfig
 from app.core.workflow.nodes.variable_aggregator.config import VariableAggregatorNodeConfig
+from app.core.workflow.nodes.parameter_extractor.config import ParameterExtractorNodeConfig
 
 __all__ = [
     # 基础类
@@ -38,4 +39,5 @@ __all__ = [
     "HttpRequestNodeConfig",
     "JinjaRenderNodeConfig",
     "VariableAggregatorNodeConfig",
+    "ParameterExtractorNodeConfig",
 ]

api/app/core/workflow/nodes/parameter_extractor/node.py

@@ -68,10 +68,10 @@ class ParameterExtractorNode(BaseNode):
             config = ModelConfigService.get_model_by_id(db=db, model_id=model_id)
 
             if not config:
-                raise BusinessException("配置的模型不存在", BizCode.NOT_FOUND)
+                raise BusinessException("Configured model does not exist", BizCode.NOT_FOUND)
 
             if not config.api_keys or len(config.api_keys) == 0:
-                raise BusinessException("模型配置缺少 API Key", BizCode.INVALID_PARAMETER)
+                raise BusinessException("Model configuration is missing API Key", BizCode.INVALID_PARAMETER)
 
             api_config = config.api_keys[0]
             model_name = api_config.model_name