Merge branch 'refs/heads/main' into feat/workflow-parallel-support

# Conflicts:
#	api/core/workflow/nodes/llm/llm_node.py
#	api/core/workflow/nodes/question_classifier/question_classifier_node.py

api/core/workflow/nodes/code/code_node.py

@@ -67,7 +67,6 @@ class CodeNode(BaseNode):
                 language=code_language,
                 code=code,
                 inputs=variables,
-                dependencies=node_data.dependencies
             )
 
             # Transform result

api/core/workflow/nodes/code/entities.py

@@ -3,7 +3,6 @@ from typing import Literal, Optional
 from pydantic import BaseModel
 
 from core.helper.code_executor.code_executor import CodeLanguage
-from core.helper.code_executor.entities import CodeDependency
 from core.workflow.entities.base_node_data_entities import BaseNodeData
 from core.workflow.entities.variable_entities import VariableSelector
 
@@ -16,8 +15,12 @@ class CodeNodeData(BaseNodeData):
         type: Literal['string', 'number', 'object', 'array[string]', 'array[number]', 'array[object]']
         children: Optional[dict[str, 'Output']] = None
 
+    class Dependency(BaseModel):
+        name: str
+        version: str
+
     variables: list[VariableSelector]
     code_language: Literal[CodeLanguage.PYTHON3, CodeLanguage.JAVASCRIPT]
     code: str
     outputs: dict[str, Output]
-    dependencies: Optional[list[CodeDependency]] = None
+    dependencies: Optional[list[Dependency]] = None

api/core/workflow/nodes/llm/llm_node.py

@@ -138,12 +138,14 @@ class LLMNode(BaseNode):
 
             result_text = ''
             usage = LLMUsage.empty_usage()
+            finish_reason = None
             for event in generator:
                 if isinstance(event, RunStreamChunkEvent):
                     yield event
                 elif isinstance(event, ModelInvokeCompleted):
                     result_text = event.text
                     usage = event.usage
+                    finish_reason = event.finish_reason
                     break
         except Exception as e:
             yield RunCompletedEvent(
@@ -158,7 +160,8 @@ class LLMNode(BaseNode):
 
         outputs = {
             'text': result_text,
-            'usage': jsonable_encoder(usage)
+            'usage': jsonable_encoder(usage),
+            'finish_reason': finish_reason
         }
 
         yield RunCompletedEvent(
@@ -227,6 +230,7 @@ class LLMNode(BaseNode):
         prompt_messages: list[PromptMessage] = []
         full_text = ''
         usage = None
+        finish_reason = None
         for result in invoke_result:
             text = result.delta.message.content
             full_text += text
@@ -245,12 +249,16 @@ class LLMNode(BaseNode):
             if not usage and result.delta.usage:
                 usage = result.delta.usage
 
+            if not finish_reason and result.delta.finish_reason:
+                finish_reason = result.delta.finish_reason
+
         if not usage:
             usage = LLMUsage.empty_usage()
 
         yield ModelInvokeCompleted(
             text=full_text,
-            usage=usage
+            usage=usage,
+            finish_reason=finish_reason
         )
 
     def _transform_chat_messages(self,

api/core/workflow/nodes/question_classifier/question_classifier_node.py

@@ -74,10 +74,12 @@ class QuestionClassifierNode(LLMNode):
 
         result_text = ''
         usage = LLMUsage.empty_usage()
+        finished_reason = None
         for event in generator:
             if isinstance(event, ModelInvokeCompleted):
                 result_text = event.text
                 usage = event.usage
+                finished_reason = event.finished_reason
                 break
 
         category_name = node_data.classes[0].name
@@ -104,6 +106,7 @@ class QuestionClassifierNode(LLMNode):
                     prompt_messages=prompt_messages
                 ),
                 'usage': jsonable_encoder(usage),
+                'finish_reason': finish_reason
             }
             outputs = {
                 'class_name': category_name