feat(api/workflow): Add Conversation.dialogue_count (#7275)

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

@@ -23,8 +23,9 @@ from core.model_runtime.utils.encoders import jsonable_encoder
 from core.prompt.advanced_prompt_transform import AdvancedPromptTransform
 from core.prompt.entities.advanced_prompt_entities import CompletionModelPromptTemplate, MemoryConfig
 from core.prompt.utils.prompt_message_util import PromptMessageUtil
-from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType, SystemVariable
+from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.enums import SystemVariable
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.llm.entities import (
     LLMNodeChatModelMessage,
@@ -201,8 +202,8 @@ class LLMNode(BaseNode):
             usage = LLMUsage.empty_usage()
 
         return full_text, usage
-    
-    def _transform_chat_messages(self, 
+
+    def _transform_chat_messages(self,
         messages: list[LLMNodeChatModelMessage] | LLMNodeCompletionModelPromptTemplate
     ) -> list[LLMNodeChatModelMessage] | LLMNodeCompletionModelPromptTemplate:
         """
@@ -249,13 +250,13 @@ class LLMNode(BaseNode):
                 # check if it's a context structure
                 if 'metadata' in d and '_source' in d['metadata'] and 'content' in d:
                     return d['content']
-                
+
                 # else, parse the dict
                 try:
                     return json.dumps(d, ensure_ascii=False)
                 except Exception:
                     return str(d)
-                
+
             if isinstance(value, str):
                 value = value
             elif isinstance(value, list):

api/core/workflow/nodes/tool/tool_node.py

@@ -2,19 +2,20 @@ from collections.abc import Mapping, Sequence
 from os import path
 from typing import Any, cast
 
-from core.app.segments import parser
+from core.app.segments import ArrayAnyVariable, parser
 from core.callback_handler.workflow_tool_callback_handler import DifyWorkflowCallbackHandler
 from core.file.file_obj import FileTransferMethod, FileType, FileVar
 from core.tools.entities.tool_entities import ToolInvokeMessage, ToolParameter
 from core.tools.tool_engine import ToolEngine
 from core.tools.tool_manager import ToolManager
 from core.tools.utils.message_transformer import ToolFileMessageTransformer
-from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType, SystemVariable
+from core.workflow.entities.node_entities import NodeRunMetadataKey, NodeRunResult, NodeType
 from core.workflow.entities.variable_pool import VariablePool
+from core.workflow.enums import SystemVariable
 from core.workflow.nodes.base_node import BaseNode
 from core.workflow.nodes.tool.entities import ToolNodeData
 from core.workflow.utils.variable_template_parser import VariableTemplateParser
-from models.workflow import WorkflowNodeExecutionStatus
+from models import WorkflowNodeExecutionStatus
 
 
 class ToolNode(BaseNode):
@@ -140,9 +141,9 @@ class ToolNode(BaseNode):
         return result
 
     def _fetch_files(self, variable_pool: VariablePool) -> list[FileVar]:
-        # FIXME: ensure this is a ArrayVariable contains FileVariable.
         variable = variable_pool.get(['sys', SystemVariable.FILES.value])
-        return [file_var.value for file_var in variable.value] if variable else []
+        assert isinstance(variable, ArrayAnyVariable)
+        return list(variable.value) if variable else []
 
     def _convert_tool_messages(self, messages: list[ToolInvokeMessage]):
         """