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
This commit is contained in:
朱文辉
@@ -5,9 +5,11 @@
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"""
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from app.core.workflow.nodes.agent import AgentNode
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from app.core.workflow.nodes.assigner import AssignerNode
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from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
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from app.core.workflow.nodes.end import EndNode
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from app.core.workflow.nodes.if_else import IfElseNode
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# from app.core.workflow.nodes.knowledge import KnowledgeRetrievalNode
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from app.core.workflow.nodes.llm import LLMNode
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from app.core.workflow.nodes.node_factory import NodeFactory, WorkflowNode
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from app.core.workflow.nodes.start import StartNode
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@@ -23,5 +25,7 @@ __all__ = [
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"StartNode",
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"EndNode",
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"NodeFactory",
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"WorkflowNode"
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"WorkflowNode",
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# "KnowledgeRetrievalNode",
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"AssignerNode",
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]
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4
api/app/core/workflow/nodes/assigner/__init__.py
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4
api/app/core/workflow/nodes/assigner/__init__.py
Normal file
@@ -0,0 +1,4 @@
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from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
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from app.core.workflow.nodes.assigner.node import AssignerNode
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__all__ = ["AssignerNode", "AssignerNodeConfig"]
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21
api/app/core/workflow/nodes/assigner/config.py
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21
api/app/core/workflow/nodes/assigner/config.py
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@@ -0,0 +1,21 @@
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from pydantic import Field
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from app.core.workflow.nodes.base_config import BaseNodeConfig
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from app.core.workflow.nodes.enums import AssignmentOperator
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class AssignerNodeConfig(BaseNodeConfig):
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variable_selector: str | list[str] = Field(
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...,
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description="Variables to be assigned",
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)
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operation: AssignmentOperator = Field(
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...,
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description="Operator to assign",
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)
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value: str | list[str] = Field(
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...,
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description="Values to assign",
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)
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80
api/app/core/workflow/nodes/assigner/node.py
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80
api/app/core/workflow/nodes/assigner/node.py
Normal file
@@ -0,0 +1,80 @@
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import logging
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from typing import Any
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from app.core.workflow.expression_evaluator import ExpressionEvaluator
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from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
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from app.core.workflow.nodes.base_node import BaseNode, WorkflowState
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from app.core.workflow.nodes.enums import AssignmentOperator
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from app.core.workflow.nodes.operators import AssignmentOperatorInstance
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from app.core.workflow.variable_pool import VariablePool
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logger = logging.getLogger(__name__)
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class AssignerNode(BaseNode):
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def __init__(self, node_config: dict[str, Any], workflow_config: dict[str, Any]):
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super().__init__(node_config, workflow_config)
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self.typed_config = AssignerNodeConfig(**self.config)
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async def execute(self, state: WorkflowState) -> Any:
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"""
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Execute the assignment operation defined by this node.
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Args:
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state: The current workflow state, including conversation variables,
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node outputs, and system variables.
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Returns:
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None or the result of the assignment operation.
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"""
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# Initialize a variable pool for accessing conversation, node, and system variables
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pool = VariablePool(state)
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# Get the target variable selector (e.g., "conv.test")
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variable_selector = self.typed_config.variable_selector
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if isinstance(variable_selector, str):
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# Support dot-separated string paths, e.g., "conv.test" -> ["conv", "test"]
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variable_selector = variable_selector.split('.')
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# Only conversation variables ('conv') are allowed
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if variable_selector[0] != 'conv': # TODO: Loop node variable support (Feature)
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raise ValueError("Only conversation variables can be assigned.")
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# Get the value or expression to assign
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value = self.typed_config.value
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if isinstance(value, list):
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value = '.'.join(value)
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value = ExpressionEvaluator.evaluate(
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expression=value,
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variables=pool.get_all_conversation_vars(),
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node_outputs=pool.get_all_node_outputs(),
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system_vars=pool.get_all_system_vars(),
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)
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# Select the appropriate assignment operator instance based on the target variable type
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operator: AssignmentOperatorInstance = AssignmentOperator.get_operator(pool.get(variable_selector))(
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pool, variable_selector, value
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)
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# Execute the configured assignment operation
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match self.typed_config.operation:
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case AssignmentOperator.ASSIGN:
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operator.assign()
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case AssignmentOperator.CLEAR:
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operator.clear()
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case AssignmentOperator.ADD:
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operator.add()
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case AssignmentOperator.SUBTRACT:
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operator.subtract()
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case AssignmentOperator.MULTIPLY:
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operator.multiply()
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case AssignmentOperator.DIVIDE:
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operator.divide()
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case AssignmentOperator.APPEND:
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operator.append()
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case AssignmentOperator.REMOVE_FIRST:
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operator.remove_first()
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case AssignmentOperator.REMOVE_LAST:
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operator.remove_last()
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case _:
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raise ValueError(f"Invalid Operator: {self.typed_config.operation}")
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@@ -14,6 +14,8 @@ from app.core.workflow.nodes.llm.config import LLMNodeConfig, MessageConfig
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from app.core.workflow.nodes.agent.config import AgentNodeConfig
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from app.core.workflow.nodes.transform.config import TransformNodeConfig
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from app.core.workflow.nodes.if_else.config import IfElseNodeConfig
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# from app.core.workflow.nodes.knowledge.config import KnowledgeRetrievalNodeConfig
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from app.core.workflow.nodes.assigner.config import AssignerNodeConfig
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__all__ = [
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# 基础类
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@@ -28,4 +30,6 @@ __all__ = [
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"AgentNodeConfig",
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"TransformNodeConfig",
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"IfElseNodeConfig",
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# "KnowledgeRetrievalNodeConfig",
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"AssignerNodeConfig",
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]
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@@ -33,7 +33,7 @@ class EndNode(BaseNode):
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# 获取配置的输出模板
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output_template = self.config.get("output")
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# 如果配置了输出模板，使用模板渲染；否则使用默认输出
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if output_template:
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output = self._render_template(output_template, state)
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@@ -45,17 +45,17 @@ class EndNode(BaseNode):
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total_nodes = len(node_outputs)
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logger.info(f"节点 {self.node_id} (End) 执行完成，共执行 {total_nodes} 个节点")
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return output
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def _extract_referenced_nodes(self, template: str) -> list[str]:
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"""从模板中提取引用的节点 ID
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例如：'结果：{{llm_qa.output}}' -> ['llm_qa']
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Args:
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template: 模板字符串
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Returns:
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引用的节点 ID 列表
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"""
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@@ -63,44 +63,44 @@ class EndNode(BaseNode):
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pattern = r'\{\{([a-zA-Z0-9_]+)\.[a-zA-Z0-9_]+\}\}'
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matches = re.findall(pattern, template)
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return list(set(matches)) # 去重
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def _parse_template_parts(self, template: str, state: WorkflowState) -> list[dict]:
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"""解析模板，分离静态文本和动态引用
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例如：'你好 {{llm.output}}, 这是后缀'
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返回：[
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{"type": "static", "content": "你好 "},
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{"type": "dynamic", "node_id": "llm", "field": "output"},
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{"type": "static", "content": ", 这是后缀"}
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]
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Args:
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template: 模板字符串
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state: 工作流状态
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Returns:
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模板部分列表
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"""
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import re
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parts = []
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last_end = 0
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# 匹配 {{xxx}} 或 {{ xxx }} 格式（支持空格）
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pattern = r'\{\{\s*([^}]+?)\s*\}\}'
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for match in re.finditer(pattern, template):
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start, end = match.span()
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# 添加前面的静态文本
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if start > last_end:
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static_text = template[last_end:start]
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if static_text:
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parts.append({"type": "static", "content": static_text})
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# 解析动态引用
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ref = match.group(1).strip()
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# 检查是否是节点引用（如 llm.output 或 llm_qa.output）
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if '.' in ref:
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node_id, field = ref.split('.', 1)
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@@ -115,62 +115,62 @@ class EndNode(BaseNode):
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# 直接渲染这部分
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rendered = self._render_template(f"{{{{{ref}}}}}", state)
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parts.append({"type": "static", "content": rendered})
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last_end = end
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# 添加最后的静态文本
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if last_end < len(template):
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static_text = template[last_end:]
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if static_text:
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parts.append({"type": "static", "content": static_text})
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return parts
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async def execute_stream(self, state: WorkflowState):
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"""流式执行 end 节点业务逻辑
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智能输出策略：
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1. 检测模板中是否引用了直接上游节点
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2. 如果引用了，只输出该引用**之后**的部分（后缀）
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3. 前缀和引用内容已经在上游节点流式输出时发送了
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示例：'{{start.test}}hahaha {{ llm_qa.output }} lalalalala a'
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- 直接上游节点是 llm_qa
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- 前缀 '{{start.test}}hahaha ' 已在 LLM 节点流式输出前发送
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- LLM 内容在 LLM 节点流式输出
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- End 节点只输出 ' lalalalala a'（后缀，一次性输出）
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Args:
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state: 工作流状态
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Yields:
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完成标记
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"""
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logger.info(f"节点 {self.node_id} (End) 开始执行（流式）")
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# 获取配置的输出模板
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output_template = self.config.get("output")
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if not output_template:
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output = "工作流已完成"
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yield {"__final__": True, "result": output}
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return
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# 找到直接上游节点
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direct_upstream_nodes = []
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for edge in self.workflow_config.get("edges", []):
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if edge.get("target") == self.node_id:
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source_node_id = edge.get("source")
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direct_upstream_nodes.append(source_node_id)
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logger.info(f"节点 {self.node_id} 的直接上游节点: {direct_upstream_nodes}")
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# 解析模板部分
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parts = self._parse_template_parts(output_template, state)
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logger.info(f"节点 {self.node_id} 解析模板，共 {len(parts)} 个部分")
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for i, part in enumerate(parts):
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logger.info(f"[模板解析] part[{i}]: {part}")
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# 找到第一个引用直接上游节点的动态引用
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upstream_ref_index = None
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for i, part in enumerate(parts):
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@@ -178,12 +178,12 @@ class EndNode(BaseNode):
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upstream_ref_index = i
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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}")
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break
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if upstream_ref_index is None:
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# 没有引用直接上游节点，输出完整模板内容
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output = self._render_template(output_template, state)
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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]}...'")
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# 通过 writer 发送完整内容（作为一个 message chunk）
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from langgraph.config import get_stream_writer
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writer = get_stream_writer()
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@@ -196,14 +196,14 @@ class EndNode(BaseNode):
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"is_suffix": False
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})
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logger.info(f"节点 {self.node_id} 已通过 writer 发送完整内容")
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# yield 完成标记
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yield {"__final__": True, "result": output}
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return
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# 有引用直接上游节点，只输出该引用之后的部分（后缀）
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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）")
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# 收集后缀部分
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suffix_parts = []
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logger.info(f"[后缀调试] 开始收集后缀，从索引 {upstream_ref_index + 1} 到 {len(parts) - 1}")
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@@ -214,7 +214,7 @@ class EndNode(BaseNode):
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# 静态文本
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logger.info(f"[后缀调试] 添加静态文本: '{part['content']}'")
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suffix_parts.append(part["content"])
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elif part["type"] == "dynamic":
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# Other dynamic references (if there are multiple references)
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node_id = part["node_id"]
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@@ -229,21 +229,21 @@ class EndNode(BaseNode):
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except Exception as e:
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logger.warning(f"[后缀调试] 获取变量 {node_id}.{field} 失败: {e}")
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content = ""
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# Convert to string if not None
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suffix_parts.append(str(content) if content is not None else "")
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# 拼接后缀
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suffix = "".join(suffix_parts)
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# 构建完整输出（用于返回，包含前缀 + 动态内容 + 后缀）
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full_output = self._render_template(output_template, state)
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logger.info(f"[后缀调试] 节点 {self.node_id} 后缀部分数量: {len(suffix_parts)}")
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logger.info(f"[后缀调试] 后缀内容: '{suffix}'")
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logger.info(f"[后缀调试] 后缀长度: {len(suffix)}")
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logger.info(f"[后缀调试] 后缀是否为空: {not suffix}")
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if suffix:
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logger.info(f"节点 {self.node_id} 输出后缀: '{suffix}...' (长度: {len(suffix)})")
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# 一次性输出后缀（作为单个 chunk）
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@@ -266,8 +266,8 @@ class EndNode(BaseNode):
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# 统计信息
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node_outputs = state.get("node_outputs", {})
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total_nodes = len(node_outputs)
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logger.info(f"节点 {self.node_id} (End) 执行完成（流式），共执行了 {total_nodes} 个节点")
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# yield 完成标记（包含完整输出）
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yield {"__final__": True, "result": full_output}
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@@ -1,5 +1,14 @@
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from enum import StrEnum
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from app.core.workflow.nodes.operators import (
|
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StringOperator,
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NumberOperator,
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AssignmentOperatorType,
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BooleanOperator,
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ArrayOperator,
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ObjectOperator
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)
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class NodeType(StrEnum):
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START = "start"
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@@ -14,6 +23,7 @@ class NodeType(StrEnum):
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HTTP_REQUEST = "http-request"
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TOOL = "tool"
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AGENT = "agent"
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ASSIGNER = "assigner"
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class ComparisonOperator(StrEnum):
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@@ -34,3 +44,32 @@ class ComparisonOperator(StrEnum):
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class LogicOperator(StrEnum):
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AND = "and"
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OR = "or"
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class AssignmentOperator(StrEnum):
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ASSIGN = "assign"
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CLEAR = "clear"
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ADD = "add" # +=
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SUBTRACT = "subtract" # -=
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MULTIPLY = "multiply" # *=
|
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DIVIDE = "divide" # /=
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|
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APPEND = "append"
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REMOVE_LAST = "remove_last"
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REMOVE_FIRST = "remove_first"
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@classmethod
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def get_operator(cls, obj) -> AssignmentOperatorType:
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if isinstance(obj, str):
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return StringOperator
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elif isinstance(obj, bool):
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return BooleanOperator
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elif isinstance(obj, (int, float)):
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return NumberOperator
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elif isinstance(obj, list):
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return ArrayOperator
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elif isinstance(obj, dict):
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return ObjectOperator
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|
||||
raise TypeError(f"Unsupported variable type ({type(obj)})")
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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}")
|
||||
|
||||
@@ -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:
|
||||
|
||||
146
api/app/core/workflow/nodes/operators.py
Normal file
146
api/app/core/workflow/nodes/operators.py
Normal file
@@ -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]
|
||||
@@ -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:
|
||||
|
||||
@@ -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"""
|
||||
|
||||
@@ -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
|
||||
|
||||
@@ -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 = [
|
||||
|
||||
@@ -39,14 +39,14 @@ class WorkflowService:
|
||||
# ==================== 配置管理 ====================
|
||||
|
||||
def create_workflow_config(
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
nodes: list[dict[str, Any]],
|
||||
edges: list[dict[str, Any]],
|
||||
variables: list[dict[str, Any]] | None = None,
|
||||
execution_config: dict[str, Any] | None = None,
|
||||
triggers: list[dict[str, Any]] | None = None,
|
||||
validate: bool = True
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
nodes: list[dict[str, Any]],
|
||||
edges: list[dict[str, Any]],
|
||||
variables: list[dict[str, Any]] | None = None,
|
||||
execution_config: dict[str, Any] | None = None,
|
||||
triggers: list[dict[str, Any]] | None = None,
|
||||
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,
|
||||
app_id: uuid.UUID,
|
||||
nodes: list[dict[str, Any]] | None = None,
|
||||
edges: list[dict[str, Any]] | None = None,
|
||||
variables: list[dict[str, Any]] | None = None,
|
||||
execution_config: dict[str, Any] | None = None,
|
||||
triggers: list[dict[str, Any]] | None = None,
|
||||
validate: bool = True
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
nodes: list[dict[str, Any]] | None = None,
|
||||
edges: list[dict[str, Any]] | None = None,
|
||||
variables: list[dict[str, Any]] | None = None,
|
||||
execution_config: dict[str, Any] | None = None,
|
||||
triggers: list[dict[str, Any]] | None = None,
|
||||
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,
|
||||
app_id: uuid.UUID
|
||||
self,
|
||||
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,
|
||||
workflow_config_id: uuid.UUID,
|
||||
app_id: uuid.UUID,
|
||||
trigger_type: str,
|
||||
triggered_by: uuid.UUID | None = None,
|
||||
conversation_id: uuid.UUID | None = None,
|
||||
input_data: dict[str, Any] | None = None
|
||||
self,
|
||||
workflow_config_id: uuid.UUID,
|
||||
app_id: uuid.UUID,
|
||||
trigger_type: str,
|
||||
triggered_by: uuid.UUID | None = None,
|
||||
conversation_id: uuid.UUID | 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,
|
||||
app_id: uuid.UUID,
|
||||
limit: int = 50,
|
||||
offset: int = 0
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
limit: int = 50,
|
||||
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,
|
||||
execution_id: str,
|
||||
status: str,
|
||||
output_data: dict[str, Any] | None = None,
|
||||
error_message: str | None = None,
|
||||
error_node_id: str | None = None
|
||||
self,
|
||||
execution_id: str,
|
||||
status: str,
|
||||
output_data: dict[str, Any] | None = None,
|
||||
error_message: 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,
|
||||
app_id: uuid.UUID,
|
||||
payload: DraftRunRequest,
|
||||
config: WorkflowConfig
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
payload: DraftRunRequest,
|
||||
config: WorkflowConfig
|
||||
):
|
||||
"""运行工作流
|
||||
|
||||
@@ -527,10 +527,10 @@ class WorkflowService:
|
||||
)
|
||||
|
||||
async def run_stream(
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
payload: DraftRunRequest,
|
||||
config: WorkflowConfig
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
payload: DraftRunRequest,
|
||||
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,
|
||||
input_data=input_data,
|
||||
execution_id=execution.execution_id,
|
||||
workspace_id="",
|
||||
user_id=payload.user_id
|
||||
workflow_config=workflow_config_dict,
|
||||
input_data=input_data,
|
||||
execution_id=execution.execution_id,
|
||||
workspace_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,
|
||||
app_id: uuid.UUID,
|
||||
input_data: dict[str, Any],
|
||||
triggered_by: uuid.UUID,
|
||||
conversation_id: uuid.UUID | None = None,
|
||||
stream: bool = False
|
||||
self,
|
||||
app_id: uuid.UUID,
|
||||
input_data: dict[str, Any],
|
||||
triggered_by: uuid.UUID,
|
||||
conversation_id: uuid.UUID | None = None,
|
||||
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,
|
||||
workflow_config: dict[str, Any],
|
||||
input_data: dict[str, Any],
|
||||
execution_id: str,
|
||||
workspace_id: str,
|
||||
user_id: str):
|
||||
self,
|
||||
workflow_config: dict[str, Any],
|
||||
input_data: dict[str, Any],
|
||||
execution_id: str,
|
||||
workspace_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,
|
||||
input_data=input_data,
|
||||
execution_id=execution_id,
|
||||
workspace_id=workspace_id,
|
||||
user_id=user_id
|
||||
workflow_config=workflow_config,
|
||||
input_data=input_data,
|
||||
execution_id=execution_id,
|
||||
workspace_id=workspace_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)
|
||||
|
||||
Reference in New Issue
Block a user