Merge #34 into develop from feature/20251219_myh

feat(workflow): add assigner node and fix circular imports with minor code style cleanup

* feature/20251219_myh: (7 commits)
  style(service): workflow
  style(workflow): remove unnecessary indentation
  revert(workflow): read conversation variables from database instead of API input
  feat(workflow): add assigner node and fix circular imports with minor code style cleanup
  fix(workflow): fix incorrect list append/pop logic in assigner node
  fix(workflow): fix incorrect list extend logic in assigner node
  fix(workflow): fix incorrect list append logic in assigner node

Signed-off-by: Eternity <1533512157@qq.com>
Commented-by: Eternity <1533512157@qq.com>
Reviewed-by: zhuwenhui5566@163.com <zhuwenhui5566@163.com>
Merged-by: zhuwenhui5566@163.com <zhuwenhui5566@163.com>

CR-link: https://codeup.aliyun.com/redbearai/python/redbear-mem-open/change/34

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

@@ -5,9 +5,11 @@
 """
 
 from app.core.workflow.nodes.agent import AgentNode
+from app.core.workflow.nodes.assigner import AssignerNode
 from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
 from app.core.workflow.nodes.end import EndNode
 from app.core.workflow.nodes.if_else import IfElseNode
+# from app.core.workflow.nodes.knowledge import KnowledgeRetrievalNode
 from app.core.workflow.nodes.llm import LLMNode
 from app.core.workflow.nodes.node_factory import NodeFactory, WorkflowNode
 from app.core.workflow.nodes.start import StartNode
@@ -23,5 +25,7 @@ __all__ = [
     "StartNode",
     "EndNode",
     "NodeFactory",
-    "WorkflowNode"
+    "WorkflowNode",
+    # "KnowledgeRetrievalNode",
+    "AssignerNode",
 ]

api/app/core/workflow/nodes/assigner/__init__.py

@@ -0,0 +1,4 @@
+from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
+from app.core.workflow.nodes.assigner.node import AssignerNode
+
+__all__ = ["AssignerNode", "AssignerNodeConfig"]

api/app/core/workflow/nodes/assigner/config.py

@@ -0,0 +1,21 @@
+from pydantic import Field
+
+from app.core.workflow.nodes.base_config import BaseNodeConfig
+from app.core.workflow.nodes.enums import AssignmentOperator
+
+
+class AssignerNodeConfig(BaseNodeConfig):
+    variable_selector: str | list[str] = Field(
+        ...,
+        description="Variables to be assigned",
+    )
+
+    operation: AssignmentOperator = Field(
+        ...,
+        description="Operator to assign",
+    )
+
+    value: str | list[str] = Field(
+        ...,
+        description="Values to assign",
+    )

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

@@ -0,0 +1,80 @@
+import logging
+from typing import Any
+
+from app.core.workflow.expression_evaluator import ExpressionEvaluator
+from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
+from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
+from app.core.workflow.nodes.enums import AssignmentOperator
+from app.core.workflow.nodes.operators import AssignmentOperatorInstance
+from app.core.workflow.variable_pool import VariablePool
+
+logger = logging.getLogger(__name__)
+
+
+class AssignerNode(BaseNode):
+    def __init__(self, node_config: dict[str, Any], workflow_config: dict[str, Any]):
+        super().__init__(node_config, workflow_config)
+        self.typed_config = AssignerNodeConfig(**self.config)
+
+    async def execute(self, state: WorkflowState) -> Any:
+        """
+        Execute the assignment operation defined by this node.
+
+        Args:
+            state: The current workflow state, including conversation variables,
+                   node outputs, and system variables.
+
+        Returns:
+            None or the result of the assignment operation.
+        """
+        # Initialize a variable pool for accessing conversation, node, and system variables
+        pool = VariablePool(state)
+
+        # Get the target variable selector (e.g., "conv.test")
+        variable_selector = self.typed_config.variable_selector
+        if isinstance(variable_selector, str):
+            # Support dot-separated string paths, e.g., "conv.test" -> ["conv", "test"]
+            variable_selector = variable_selector.split('.')
+
+        # Only conversation variables ('conv') are allowed
+        if variable_selector[0] != 'conv':  # TODO: Loop node variable support (Feature)
+            raise ValueError("Only conversation variables can be assigned.")
+
+        # Get the value or expression to assign
+        value = self.typed_config.value
+        if isinstance(value, list):
+            value = '.'.join(value)
+        value = ExpressionEvaluator.evaluate(
+            expression=value,
+            variables=pool.get_all_conversation_vars(),
+            node_outputs=pool.get_all_node_outputs(),
+            system_vars=pool.get_all_system_vars(),
+        )
+
+        # Select the appropriate assignment operator instance based on the target variable type
+        operator: AssignmentOperatorInstance = AssignmentOperator.get_operator(pool.get(variable_selector))(
+            pool, variable_selector, value
+        )
+
+        # Execute the configured assignment operation
+        match self.typed_config.operation:
+            case AssignmentOperator.ASSIGN:
+                operator.assign()
+            case AssignmentOperator.CLEAR:
+                operator.clear()
+            case AssignmentOperator.ADD:
+                operator.add()
+            case AssignmentOperator.SUBTRACT:
+                operator.subtract()
+            case AssignmentOperator.MULTIPLY:
+                operator.multiply()
+            case AssignmentOperator.DIVIDE:
+                operator.divide()
+            case AssignmentOperator.APPEND:
+                operator.append()
+            case AssignmentOperator.REMOVE_FIRST:
+                operator.remove_first()
+            case AssignmentOperator.REMOVE_LAST:
+                operator.remove_last()
+            case _:
+                raise ValueError(f"Invalid Operator: {self.typed_config.operation}")

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

@@ -14,6 +14,8 @@ from app.core.workflow.nodes.llm.config import LLMNodeConfig, MessageConfig
 from app.core.workflow.nodes.agent.config import AgentNodeConfig
 from app.core.workflow.nodes.transform.config import TransformNodeConfig
 from app.core.workflow.nodes.if_else.config import IfElseNodeConfig
+# from app.core.workflow.nodes.knowledge.config import KnowledgeRetrievalNodeConfig
+from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
 
 __all__ = [
     # 基础类
@@ -28,4 +30,6 @@ __all__ = [
     "AgentNodeConfig",
     "TransformNodeConfig",
     "IfElseNodeConfig",
+    # "KnowledgeRetrievalNodeConfig",
+    "AssignerNodeConfig",
 ]

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

@@ -33,7 +33,7 @@ class EndNode(BaseNode):
         
         # 获取配置的输出模板
         output_template = self.config.get("output")
-        
+
         # 如果配置了输出模板，使用模板渲染；否则使用默认输出
         if output_template:
             output = self._render_template(output_template, state)
@@ -45,17 +45,17 @@ class EndNode(BaseNode):
         total_nodes = len(node_outputs)
         
         logger.info(f"节点 {self.node_id} (End) 执行完成，共执行 {total_nodes} 个节点")
-        
+
         return output
-    
+
     def _extract_referenced_nodes(self, template: str) -> list[str]:
         """从模板中提取引用的节点 ID
-        
+
         例如：'结果：{{llm_qa.output}}' -> ['llm_qa']
-        
+
         Args:
             template: 模板字符串
-        
+
         Returns:
             引用的节点 ID 列表
         """
@@ -63,44 +63,44 @@ class EndNode(BaseNode):
         pattern = r'\{\{([a-zA-Z0-9_]+)\.[a-zA-Z0-9_]+\}\}'
         matches = re.findall(pattern, template)
         return list(set(matches))  # 去重
-    
+
     def _parse_template_parts(self, template: str, state: WorkflowState) -> list[dict]:
         """解析模板，分离静态文本和动态引用
-        
+
         例如：'你好 {{llm.output}}, 这是后缀'
         返回：[
             {"type": "static", "content": "你好 "},
             {"type": "dynamic", "node_id": "llm", "field": "output"},
             {"type": "static", "content": ", 这是后缀"}
         ]
-        
+
         Args:
             template: 模板字符串
             state: 工作流状态
-        
+
         Returns:
             模板部分列表
         """
         import re
-        
+
         parts = []
         last_end = 0
-        
+
         # 匹配 {{xxx}} 或 {{ xxx }} 格式（支持空格）
         pattern = r'\{\{\s*([^}]+?)\s*\}\}'
-        
+
         for match in re.finditer(pattern, template):
             start, end = match.span()
-            
+
             # 添加前面的静态文本
             if start > last_end:
                 static_text = template[last_end:start]
                 if static_text:
                     parts.append({"type": "static", "content": static_text})
-            
+
             # 解析动态引用
             ref = match.group(1).strip()
-            
+
             # 检查是否是节点引用（如 llm.output 或 llm_qa.output）
             if '.' in ref:
                 node_id, field = ref.split('.', 1)
@@ -115,62 +115,62 @@ class EndNode(BaseNode):
                 # 直接渲染这部分
                 rendered = self._render_template(f"{{{{{ref}}}}}", state)
                 parts.append({"type": "static", "content": rendered})
-            
+
             last_end = end
-        
+
         # 添加最后的静态文本
         if last_end < len(template):
             static_text = template[last_end:]
             if static_text:
                 parts.append({"type": "static", "content": static_text})
-        
+
         return parts
-    
+
     async def execute_stream(self, state: WorkflowState):
         """流式执行 end 节点业务逻辑
-        
+
         智能输出策略：
         1. 检测模板中是否引用了直接上游节点
         2. 如果引用了，只输出该引用**之后**的部分（后缀）
         3. 前缀和引用内容已经在上游节点流式输出时发送了
-        
+
         示例：'{{start.test}}hahaha {{ llm_qa.output }} lalalalala a'
         - 直接上游节点是 llm_qa
         - 前缀 '{{start.test}}hahaha ' 已在 LLM 节点流式输出前发送
         - LLM 内容在 LLM 节点流式输出
         - End 节点只输出 ' lalalalala a'（后缀，一次性输出）
-        
+
         Args:
             state: 工作流状态
-        
+
         Yields:
             完成标记
         """
         logger.info(f"节点 {self.node_id} (End) 开始执行（流式）")
-        
+
         # 获取配置的输出模板
         output_template = self.config.get("output")
-        
+
         if not output_template:
             output = "工作流已完成"
             yield {"__final__": True, "result": output}
             return
-        
+
         # 找到直接上游节点
         direct_upstream_nodes = []
         for edge in self.workflow_config.get("edges", []):
             if edge.get("target") == self.node_id:
                 source_node_id = edge.get("source")
                 direct_upstream_nodes.append(source_node_id)
-        
+
         logger.info(f"节点 {self.node_id} 的直接上游节点: {direct_upstream_nodes}")
-        
+
         # 解析模板部分
         parts = self._parse_template_parts(output_template, state)
         logger.info(f"节点 {self.node_id} 解析模板，共 {len(parts)} 个部分")
         for i, part in enumerate(parts):
             logger.info(f"[模板解析] part[{i}]: {part}")
-        
+
         # 找到第一个引用直接上游节点的动态引用
         upstream_ref_index = None
         for i, part in enumerate(parts):
@@ -178,12 +178,12 @@ class EndNode(BaseNode):
                 upstream_ref_index = i
                 logger.info(f"节点 {self.node_id} 找到直接上游节点 {part['node_id']} 的引用，索引: {i}")
                 break
-        
+
         if upstream_ref_index is None:
             # 没有引用直接上游节点，输出完整模板内容
             output = self._render_template(output_template, state)
             logger.info(f"节点 {self.node_id} 没有引用直接上游节点，输出完整内容: '{output[:50]}...'")
-            
+
             # 通过 writer 发送完整内容（作为一个 message chunk）
             from langgraph.config import get_stream_writer
             writer = get_stream_writer()
@@ -196,14 +196,14 @@ class EndNode(BaseNode):
                 "is_suffix": False
             })
             logger.info(f"节点 {self.node_id} 已通过 writer 发送完整内容")
-            
+
             # yield 完成标记
             yield {"__final__": True, "result": output}
             return
-        
+
         # 有引用直接上游节点，只输出该引用之后的部分（后缀）
         logger.info(f"节点 {self.node_id} 检测到直接上游节点引用，只输出后缀部分（从索引 {upstream_ref_index + 1} 开始）")
-        
+
         # 收集后缀部分
         suffix_parts = []
         logger.info(f"[后缀调试] 开始收集后缀，从索引 {upstream_ref_index + 1} 到 {len(parts) - 1}")
@@ -214,7 +214,7 @@ class EndNode(BaseNode):
                 # 静态文本
                 logger.info(f"[后缀调试] 添加静态文本: '{part['content']}'")
                 suffix_parts.append(part["content"])
-                
+
             elif part["type"] == "dynamic":
                 # Other dynamic references (if there are multiple references)
                 node_id = part["node_id"]
@@ -229,21 +229,21 @@ class EndNode(BaseNode):
                 except Exception as e:
                     logger.warning(f"[后缀调试] 获取变量 {node_id}.{field} 失败: {e}")
                     content = ""
-                
+
                 # Convert to string if not None
                 suffix_parts.append(str(content) if content is not None else "")
         
         # 拼接后缀
         suffix = "".join(suffix_parts)
-        
+
         # 构建完整输出（用于返回，包含前缀 + 动态内容 + 后缀）
         full_output = self._render_template(output_template, state)
-        
+
         logger.info(f"[后缀调试] 节点 {self.node_id} 后缀部分数量: {len(suffix_parts)}")
         logger.info(f"[后缀调试] 后缀内容: '{suffix}'")
         logger.info(f"[后缀调试] 后缀长度: {len(suffix)}")
         logger.info(f"[后缀调试] 后缀是否为空: {not suffix}")
-        
+
         if suffix:
             logger.info(f"节点 {self.node_id} 输出后缀: '{suffix}...' (长度: {len(suffix)})")
             # 一次性输出后缀（作为单个 chunk）
@@ -266,8 +266,8 @@ class EndNode(BaseNode):
         # 统计信息
         node_outputs = state.get("node_outputs", {})
         total_nodes = len(node_outputs)
-        
+
         logger.info(f"节点 {self.node_id} (End) 执行完成（流式），共执行了 {total_nodes} 个节点")
-        
+
         # yield 完成标记（包含完整输出）
         yield {"__final__": True, "result": full_output}

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

@@ -1,5 +1,14 @@
 from enum import StrEnum
 
+from app.core.workflow.nodes.operators import (
+    StringOperator,
+    NumberOperator,
+    AssignmentOperatorType,
+    BooleanOperator,
+    ArrayOperator,
+    ObjectOperator
+)
+
 
 class NodeType(StrEnum):
     START = "start"
@@ -14,6 +23,7 @@ class NodeType(StrEnum):
     HTTP_REQUEST = "http-request"
     TOOL = "tool"
     AGENT = "agent"
+    ASSIGNER = "assigner"
 
 
 class ComparisonOperator(StrEnum):
@@ -34,3 +44,32 @@ class ComparisonOperator(StrEnum):
 class LogicOperator(StrEnum):
     AND = "and"
     OR = "or"
+
+
+class AssignmentOperator(StrEnum):
+    ASSIGN = "assign"
+    CLEAR = "clear"
+
+    ADD = "add"  # +=
+    SUBTRACT = "subtract"  # -=
+    MULTIPLY = "multiply"  # *=
+    DIVIDE = "divide"  # /=
+
+    APPEND = "append"
+    REMOVE_LAST = "remove_last"
+    REMOVE_FIRST = "remove_first"
+
+    @classmethod
+    def get_operator(cls, obj) -> AssignmentOperatorType:
+        if isinstance(obj, str):
+            return StringOperator
+        elif isinstance(obj, bool):
+            return BooleanOperator
+        elif isinstance(obj, (int, float)):
+            return NumberOperator
+        elif isinstance(obj, list):
+            return ArrayOperator
+        elif isinstance(obj, dict):
+            return ObjectOperator
+
+        raise TypeError(f"Unsupported variable type ({type(obj)})")

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

@@ -1,7 +1,7 @@
 import logging
 from typing import Any
 
-from app.core.workflow.nodes import BaseNode, WorkflowState
+from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
 from app.core.workflow.nodes.enums import ComparisonOperator
 from app.core.workflow.nodes.if_else import IfElseNodeConfig
 from app.core.workflow.nodes.if_else.config import ConditionDetail

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

@@ -11,6 +11,7 @@ from langchain_core.messages import AIMessage, SystemMessage, HumanMessage
 from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
 from app.core.models import RedBearLLM, RedBearModelConfig
 from app.db import get_db_context
+from app.models import ModelType
 from app.services.model_service import ModelConfigService
         
 from app.core.exceptions import BusinessException
@@ -136,7 +137,7 @@ class LLMNode(BaseNode):
                 base_url=api_base,
                 extra_params=extra_params
             ), 
-            type=model_type
+            type=ModelType(model_type)
         )
         
         logger.debug(f"创建 LLM 实例: provider={provider}, model={model_name}, streaming={stream}")

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

@@ -7,6 +7,7 @@
 import logging
 from typing import Any, Union
 
+# from app.core.workflow.nodes.knowledge import KnowledgeRetrievalNode
 from app.core.workflow.nodes.agent import AgentNode
 from app.core.workflow.nodes.base_node import BaseNode
 from app.core.workflow.nodes.end import EndNode
@@ -15,6 +16,7 @@ from app.core.workflow.nodes.if_else import IfElseNode
 from app.core.workflow.nodes.llm import LLMNode
 from app.core.workflow.nodes.start import StartNode
 from app.core.workflow.nodes.transform import TransformNode
+from app.core.workflow.nodes.assigner import AssignerNode
 
 logger = logging.getLogger(__name__)
 
@@ -26,6 +28,8 @@ WorkflowNode = Union[
     IfElseNode,
     AgentNode,
     TransformNode,
+    AssignerNode,
+    # KnowledgeRetrievalNode,
 ]
 
 
@@ -42,7 +46,9 @@ class NodeFactory:
         NodeType.LLM: LLMNode,
         NodeType.AGENT: AgentNode,
         NodeType.TRANSFORM: TransformNode,
-        NodeType.IF_ELSE: IfElseNode
+        NodeType.IF_ELSE: IfElseNode,
+        # NodeType.KNOWLEDGE_RETRIEVAL: KnowledgeRetrievalNode,
+        NodeType.ASSIGNER: AssignerNode,
     }
 
     @classmethod
@@ -82,10 +88,6 @@ class NodeFactory:
         """
         node_type = node_config.get("type")
 
-        # 跳过条件节点（由 LangGraph 处理）
-        if node_type == "condition":
-            return None
-
         # 获取节点类
         node_class = cls._node_types.get(node_type)
         if not node_class:

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

@@ -0,0 +1,146 @@
+from abc import ABC
+from typing import Union, Type
+
+from app.core.workflow.variable_pool import VariablePool
+
+
+class OperatorBase(ABC):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        self.pool = pool
+        self.left_selector = left_selector
+        self.right = right
+
+        self.type_limit: type[str, int, dict, list] = None
+
+    def check(self, no_right=False):
+        left = self.pool.get(self.left_selector)
+        if not isinstance(left, self.type_limit):
+            raise TypeError(f"The variable to be operated on must be of {self.type_limit} type")
+
+        if not no_right and not isinstance(self.right, self.type_limit):
+            raise TypeError(f"The value assigned to the string variable must also be of {self.type_limit} type")
+
+
+class StringOperator(OperatorBase):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        super().__init__(pool, left_selector, right)
+        self.type_limit = str
+
+    def assign(self) -> None:
+        self.check()
+        self.pool.set(self.left_selector, self.right)
+
+    def clear(self) -> None:
+        self.check(no_right=True)
+        self.pool.set(self.left_selector, '')
+
+
+class NumberOperator(OperatorBase):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        super().__init__(pool, left_selector, right)
+        self.type_limit = (float, int)
+
+    def assign(self) -> None:
+        self.check()
+        self.pool.set(self.left_selector, self.right)
+
+    def clear(self) -> None:
+        self.check(no_right=True)
+        self.pool.set(self.left_selector, 0)
+
+    def add(self) -> None:
+        self.check()
+        origin = self.pool.get(self.left_selector)
+        self.pool.set(self.left_selector, origin + self.right)
+
+    def subtract(self) -> None:
+        self.check()
+        origin = self.pool.get(self.left_selector)
+        self.pool.set(self.left_selector, origin - self.right)
+
+    def multiply(self) -> None:
+        self.check()
+        origin = self.pool.get(self.left_selector)
+        self.pool.set(self.left_selector, origin * self.right)
+
+    def divide(self) -> None:
+        self.check()
+        origin = self.pool.get(self.left_selector)
+        self.pool.set(self.left_selector, origin / self.right)
+
+
+class BooleanOperator(OperatorBase):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        super().__init__(pool, left_selector, right)
+        self.type_limit = bool
+
+    def assign(self) -> None:
+        self.check()
+        self.pool.set(self.left_selector, self.right)
+
+    def clear(self) -> None:
+        self.check(no_right=True)
+        self.pool.set(self.left_selector, False)
+
+
+class ArrayOperator(OperatorBase):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        super().__init__(pool, left_selector, right)
+        self.type_limit = list
+
+    def assign(self) -> None:
+        self.check()
+        self.pool.set(self.left_selector, self.right)
+
+    def clear(self) -> None:
+        self.check(no_right=True)
+        self.pool.set(self.left_selector, list())
+
+    def append(self) -> None:
+        self.check(no_right=True)
+        # TODO：require type limit in list
+        origin = self.pool.get(self.left_selector)
+        origin.append(self.right)
+        self.pool.set(self.left_selector, origin)
+
+    def extend(self) -> None:
+        self.check(no_right=True)
+        origin = self.pool.get(self.left_selector)
+        origin.extend(self.right)
+        self.pool.set(self.left_selector, origin)
+
+    def remove_last(self) -> None:
+        self.check(no_right=True)
+        origin = self.pool.get(self.left_selector)
+        origin.pop()
+        self.pool.set(self.left_selector, origin)
+
+    def remove_first(self) -> None:
+        self.check(no_right=True)
+        origin = self.pool.get(self.left_selector)
+        origin.pop(0)
+        self.pool.set(self.left_selector, origin)
+
+
+class ObjectOperator(OperatorBase):
+    def __init__(self, pool: VariablePool, left_selector, right):
+        super().__init__(pool, left_selector, right)
+        self.type_limit = object
+
+    def assign(self) -> None:
+        self.check()
+        self.pool.set(self.left_selector, self.right)
+
+    def clear(self) -> None:
+        self.check(no_right=True)
+        self.pool.set(self.left_selector, dict())
+
+
+AssignmentOperatorInstance = Union[
+    StringOperator,
+    NumberOperator,
+    BooleanOperator,
+    ArrayOperator,
+    ObjectOperator
+]
+AssignmentOperatorType = Type[AssignmentOperatorInstance]

api/app/core/workflow/variable_pool.py

@@ -10,7 +10,10 @@
 """
 
 import logging
-from typing import Any
+from typing import Any, TYPE_CHECKING
+
+if TYPE_CHECKING:
+    from app.core.workflow.nodes import WorkflowState
 
 logger = logging.getLogger(__name__)
 
@@ -82,7 +85,7 @@ class VariablePool:
         >>> pool.set(["conv", "user_name"], "张三")
     """
     
-    def __init__(self, state: dict[str, Any]):
+    def __init__(self, state: "WorkflowState"):
         """初始化变量池
         
         Args:

api/app/models/models_model.py

@@ -15,25 +15,6 @@ class ModelType(StrEnum):
     EMBEDDING = "embedding"
     RERANK = "rerank"
 
-    @classmethod
-    def from_str(cls, value: str) -> "ModelType":
-        """
-        Get a ModelType enum instance from a string value.
-
-        Args:
-            value (str): The string representation of the model type.
-
-        Returns:
-            ModelType: The corresponding ModelType enum object.
-
-        Raises:
-            ValueError: If the given value does not match any ModelType.
-        """
-        try:
-            return cls(value)
-        except ValueError:
-            raise ValueError(f"Invalid ModelType: {value}")
-
 
 class ModelProvider(StrEnum):
     """模型提供商枚举"""

api/app/schemas/app_schema.py

@@ -1,6 +1,7 @@
-import uuid
 import datetime
-from typing import Optional, Any, List, Dict, TYPE_CHECKING
+import uuid
+from typing import Optional, Any, List, Dict
+
 from pydantic import BaseModel, Field, ConfigDict, field_serializer, field_validator
 
 
@@ -20,20 +21,19 @@ class KnowledgeBaseConfig(BaseModel):
 class KnowledgeRetrievalConfig(BaseModel):
     """知识库检索配置（支持多个知识库，每个有独立配置）"""
     knowledge_bases: List[KnowledgeBaseConfig] = Field(
-        default_factory=list, 
+        default_factory=list,
         description="关联的知识库列表，每个知识库有独立配置"
     )
-    
+
     # 多知识库融合策略
     merge_strategy: str = Field(
-        default="weighted", 
+        default="weighted",
         description="多知识库结果融合策略: weighted | rrf | concat"
     )
     reranker_id: Optional[str] = Field(default=None, description="多知识库结果融合的模型ID")
     reranker_top_k: int = Field(default=10, ge=0, le=1024, description="多知识库结果融合的模型参数")
 
 
-
 class ToolConfig(BaseModel):
     """工具配置"""
     enabled: bool = Field(default=False, description="是否启用该工具")
@@ -63,7 +63,7 @@ class VariableDefinition(BaseModel):
     name: str = Field(..., description="变量名称（标识符）")
     display_name: Optional[str] = Field(None, description="显示名称（用户看到的名称）")
     type: str = Field(
-        default="string", 
+        default="string",
         description="变量类型: string(单行文本) | text(多行文本) | number(数字)"
     )
     required: bool = Field(default=False, description="是否必填")
@@ -75,32 +75,32 @@ class AgentConfigCreate(BaseModel):
     """Agent 行为配置"""
     # 提示词配置
     system_prompt: Optional[str] = Field(default=None, description="系统提示词，定义 Agent 的角色和行为准则")
-    
+
     # 模型配置
     default_model_config_id: Optional[uuid.UUID] = Field(default=None, description="默认使用的模型配置ID")
     model_parameters: ModelParameters = Field(
         default_factory=ModelParameters,
         description="模型参数配置（temperature、max_tokens 等）"
     )
-    
+
     # 知识库关联
     knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = Field(
         default=None,
         description="知识库检索配置"
     )
-    
+
     # 记忆配置
     memory: MemoryConfig = Field(
         default_factory=lambda: MemoryConfig(enabled=True),
         description="对话历史记忆配置"
     )
-    
+
     # 变量配置
     variables: List[VariableDefinition] = Field(
         default_factory=list,
         description="Agent 可用的变量列表"
     )
-    
+
     # 工具配置
     tools: Dict[str, ToolConfig] = Field(
         default_factory=dict,
@@ -120,7 +120,7 @@ class AppCreate(BaseModel):
 
     # only for type=agent
     agent_config: Optional[AgentConfigCreate] = None
-    
+
     # only for type=multi_agent
     multi_agent_config: Optional[Dict[str, Any]] = None
 
@@ -139,23 +139,23 @@ class AgentConfigUpdate(BaseModel):
     """更新 Agent 行为配置"""
     # 提示词配置
     system_prompt: Optional[str] = Field(default=None, description="系统提示词")
-    
+
     # 模型配置
     default_model_config_id: Optional[uuid.UUID] = Field(default=None, description="默认模型配置ID")
     model_parameters: Optional[ModelParameters] = Field(default=None, description="模型参数配置")
-    
+
     # 知识库关联
     knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = Field(
         default=None,
         description="知识库检索配置"
     )
-    
+
     # 记忆配置
     memory: Optional[MemoryConfig] = Field(default=None, description="对话历史记忆配置")
-    
+
     # 变量配置
     variables: Optional[List[VariableDefinition]] = Field(default=None, description="变量列表")
-    
+
     # 工具配置
     tools: Optional[Dict[str, ToolConfig]] = Field(default=None, description="工具配置")
 
@@ -185,7 +185,7 @@ class App(BaseModel):
     @field_serializer("created_at", when_used="json")
     def _serialize_created_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-    
+
     @field_serializer("updated_at", when_used="json")
     def _serialize_updated_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
@@ -197,26 +197,26 @@ class AgentConfig(BaseModel):
 
     id: uuid.UUID
     app_id: uuid.UUID
-    
+
     # 提示词
     system_prompt: Optional[str] = None
-    
+
     # 模型配置
     default_model_config_id: Optional[uuid.UUID] = None
     model_parameters: ModelParameters = Field(default_factory=ModelParameters)
-    
+
     # 知识库检索
     knowledge_retrieval: Optional[KnowledgeRetrievalConfig] = None
-    
+
     # 记忆配置
     memory: MemoryConfig = Field(default_factory=lambda: MemoryConfig(enabled=True))
-    
+
     # 变量配置
     variables: List[VariableDefinition] = []
-    
+
     # 工具配置
     tools: Dict[str, ToolConfig] = {}
-    
+
     is_active: bool
     created_at: datetime.datetime
     updated_at: datetime.datetime
@@ -228,7 +228,7 @@ class AgentConfig(BaseModel):
         if v is None:
             return ModelParameters()
         return v
-    
+
     @field_validator("memory", mode="before")
     @classmethod
     def validate_memory(cls, v):
@@ -236,7 +236,7 @@ class AgentConfig(BaseModel):
         if v is None:
             return MemoryConfig(enabled=True)
         return v
-    
+
     @field_validator("variables", mode="before")
     @classmethod
     def validate_variables(cls, v):
@@ -244,7 +244,7 @@ class AgentConfig(BaseModel):
         if v is None:
             return []
         return v
-    
+
     @field_validator("tools", mode="before")
     @classmethod
     def validate_tools(cls, v):
@@ -256,7 +256,7 @@ class AgentConfig(BaseModel):
     @field_serializer("created_at", when_used="json")
     def _serialize_created_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-    
+
     @field_serializer("updated_at", when_used="json")
     def _serialize_updated_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
@@ -294,15 +294,15 @@ class AppRelease(BaseModel):
     @field_serializer("created_at", when_used="json")
     def _serialize_created_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-    
+
     @field_serializer("updated_at", when_used="json")
     def _serialize_updated_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-        
+
     @field_serializer("published_at", when_used="json")
     def _serialize_published_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-    
+
 
 # ---------- App Share Schemas ----------
 
@@ -314,7 +314,7 @@ class AppShareCreate(BaseModel):
 class AppShare(BaseModel):
     """应用分享输出"""
     model_config = ConfigDict(from_attributes=True)
-    
+
     id: uuid.UUID
     source_app_id: uuid.UUID
     source_workspace_id: uuid.UUID
@@ -322,11 +322,11 @@ class AppShare(BaseModel):
     shared_by: uuid.UUID
     created_at: datetime.datetime
     updated_at: datetime.datetime
-    
+
     @field_serializer("created_at", when_used="json")
     def _serialize_created_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
-    
+
     @field_serializer("updated_at", when_used="json")
     def _serialize_updated_at(self, dt: datetime.datetime):
         return int(dt.timestamp() * 1000) if dt else None
@@ -382,14 +382,14 @@ class DraftRunCompareRequest(BaseModel):
     conversation_id: Optional[str] = Field(None, description="会话ID")
     user_id: Optional[str] = Field(None, description="用户ID")
     variables: Optional[Dict[str, Any]] = Field(None, description="变量参数")
-    
+
     models: List[ModelCompareItem] = Field(
         ...,
         min_length=1,
         max_length=5,
         description="要对比的模型列表（1-5个）"
     )
-    
+
     parallel: bool = Field(True, description="是否并行执行")
     stream: bool = Field(False, description="是否流式返回")
     timeout: Optional[int] = Field(60, ge=10, le=300, description="超时时间（秒）")
@@ -400,14 +400,14 @@ class ModelRunResult(BaseModel):
     model_config_id: uuid.UUID
     model_name: str
     label: Optional[str] = None
-    
+
     parameters_used: Dict[str, Any] = Field(..., description="实际使用的参数")
-    
+
     message: Optional[str] = None
     usage: Optional[Dict[str, Any]] = None
     elapsed_time: float
     error: Optional[str] = None
-    
+
     tokens_per_second: Optional[float] = None
     cost_estimate: Optional[float] = None
     conversation_id: Optional[str] = None
@@ -416,10 +416,10 @@ class ModelRunResult(BaseModel):
 class DraftRunCompareResponse(BaseModel):
     """多模型对比响应"""
     results: List[ModelRunResult]
-    
+
     total_elapsed_time: float
     successful_count: int
     failed_count: int
-    
+
     fastest_model: Optional[str] = None
     cheapest_model: Optional[str] = None

api/app/services/prompt_optimizer_service.py

@@ -169,7 +169,7 @@ class PromptOptimizerService:
             provider=api_config.provider,
             api_key=api_config.api_key,
             base_url=api_config.api_base
-        ), type=ModelType.from_str(model_config.type))
+        ), type=ModelType(model_config.type))
 
         # build message
         messages = [

api/app/services/workflow_service.py

@@ -39,14 +39,14 @@ class WorkflowService:
     # ==================== 配置管理 ====================
 
     def create_workflow_config(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        nodes: list[dict[str, Any]],
+            nodes: list[dict[str, Any]],
-        edges: list[dict[str, Any]],
+            edges: list[dict[str, Any]],
-        variables: list[dict[str, Any]] | None = None,
+            variables: list[dict[str, Any]] | None = None,
-        execution_config: dict[str, Any] | None = None,
+            execution_config: dict[str, Any] | None = None,
-        triggers: list[dict[str, Any]] | None = None,
+            triggers: list[dict[str, Any]] | None = None,
-        validate: bool = True
+            validate: bool = True
     ) -> WorkflowConfig:
         """创建工作流配置
 
@@ -109,14 +109,14 @@ class WorkflowService:
         return self.config_repo.get_by_app_id(app_id)
 
     def update_workflow_config(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        nodes: list[dict[str, Any]] | None = None,
+            nodes: list[dict[str, Any]] | None = None,
-        edges: list[dict[str, Any]] | None = None,
+            edges: list[dict[str, Any]] | None = None,
-        variables: list[dict[str, Any]] | None = None,
+            variables: list[dict[str, Any]] | None = None,
-        execution_config: dict[str, Any] | None = None,
+            execution_config: dict[str, Any] | None = None,
-        triggers: list[dict[str, Any]] | None = None,
+            triggers: list[dict[str, Any]] | None = None,
-        validate: bool = True
+            validate: bool = True
     ) -> WorkflowConfig:
         """更新工作流配置
 
@@ -226,8 +226,8 @@ class WorkflowService:
         return config
 
     def validate_workflow_config_for_publish(
-        self,
+            self,
-        app_id: uuid.UUID
+            app_id: uuid.UUID
     ) -> tuple[bool, list[str]]:
         """验证工作流配置是否可以发布
 
@@ -260,13 +260,13 @@ class WorkflowService:
     # ==================== 执行管理 ====================
 
     def create_execution(
-        self,
+            self,
-        workflow_config_id: uuid.UUID,
+            workflow_config_id: uuid.UUID,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        trigger_type: str,
+            trigger_type: str,
-        triggered_by: uuid.UUID | None = None,
+            triggered_by: uuid.UUID | None = None,
-        conversation_id: uuid.UUID | None = None,
+            conversation_id: uuid.UUID | None = None,
-        input_data: dict[str, Any] | None = None
+            input_data: dict[str, Any] | None = None
     ) -> WorkflowExecution:
         """创建工作流执行记录
 
@@ -314,10 +314,10 @@ class WorkflowService:
         return self.execution_repo.get_by_execution_id(execution_id)
 
     def get_executions_by_app(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        limit: int = 50,
+            limit: int = 50,
-        offset: int = 0
+            offset: int = 0
     ) -> list[WorkflowExecution]:
         """获取应用的执行记录列表
 
@@ -332,12 +332,12 @@ class WorkflowService:
         return self.execution_repo.get_by_app_id(app_id, limit, offset)
 
     def update_execution_status(
-        self,
+            self,
-        execution_id: str,
+            execution_id: str,
-        status: str,
+            status: str,
-        output_data: dict[str, Any] | None = None,
+            output_data: dict[str, Any] | None = None,
-        error_message: str | None = None,
+            error_message: str | None = None,
-        error_node_id: str | None = None
+            error_node_id: str | None = None
     ) -> WorkflowExecution:
         """更新执行状态
 
@@ -407,10 +407,10 @@ class WorkflowService:
     # ==================== 工作流执行 ====================
 
     async def run(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        payload: DraftRunRequest,
+            payload: DraftRunRequest,
-        config: WorkflowConfig
+            config: WorkflowConfig
     ):
         """运行工作流
 
@@ -527,10 +527,10 @@ class WorkflowService:
             )
 
     async def run_stream(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        payload: DraftRunRequest,
+            payload: DraftRunRequest,
-        config: WorkflowConfig
+            config: WorkflowConfig
     ):
         """运行工作流（流式）
 
@@ -600,11 +600,11 @@ class WorkflowService:
 
             # 调用流式执行（executor 会发送 workflow_start 和 workflow_end 事件）
             async for event in self._run_workflow_stream(
-                workflow_config=workflow_config_dict,
+                    workflow_config=workflow_config_dict,
-                input_data=input_data,
+                    input_data=input_data,
-                execution_id=execution.execution_id,
+                    execution_id=execution.execution_id,
-                workspace_id="",
+                    workspace_id="",
-                user_id=payload.user_id
+                    user_id=payload.user_id
             ):
                 # 直接转发 executor 的事件（已经是正确的格式）
                 yield event
@@ -626,12 +626,12 @@ class WorkflowService:
             }
 
     async def run_workflow(
-        self,
+            self,
-        app_id: uuid.UUID,
+            app_id: uuid.UUID,
-        input_data: dict[str, Any],
+            input_data: dict[str, Any],
-        triggered_by: uuid.UUID,
+            triggered_by: uuid.UUID,
-        conversation_id: uuid.UUID | None = None,
+            conversation_id: uuid.UUID | None = None,
-        stream: bool = False
+            stream: bool = False
     ) -> AsyncGenerator | dict:
         """运行工作流
 
@@ -778,12 +778,12 @@ class WorkflowService:
         return clean_value(event)
 
     async def _run_workflow_stream(
-        self,
+            self,
-        workflow_config: dict[str, Any],
+            workflow_config: dict[str, Any],
-        input_data: dict[str, Any],
+            input_data: dict[str, Any],
-        execution_id: str,
+            execution_id: str,
-        workspace_id: str,
+            workspace_id: str,
-        user_id: str):
+            user_id: str):
         """运行工作流（流式，内部方法）
 
         Args:
@@ -800,11 +800,11 @@ class WorkflowService:
 
         try:
             async for event in execute_workflow_stream(
-                workflow_config=workflow_config,
+                    workflow_config=workflow_config,
-                input_data=input_data,
+                    input_data=input_data,
-                execution_id=execution_id,
+                    execution_id=execution_id,
-                workspace_id=workspace_id,
+                    workspace_id=workspace_id,
-                user_id=user_id
+                    user_id=user_id
             ):
                 # 直接转发事件（executor 已经返回正确格式）
                 yield event
@@ -828,7 +828,7 @@ class WorkflowService:
 # ==================== 依赖注入函数 ====================
 
 def get_workflow_service(
-    db: Annotated[Session, Depends(get_db)]
+        db: Annotated[Session, Depends(get_db)]
 ) -> WorkflowService:
     """获取工作流服务（依赖注入）"""
     return WorkflowService(db)