Struct WorkflowNode 

pub struct WorkflowNode {
    pub config: NodeConfig,
    /* private fields */
}

工作流节点

Fields

config: NodeConfig

节点配置

Implementations

impl WorkflowNode

pub fn start(id: &str) -> WorkflowNode

创建开始节点

pub fn end(id: &str) -> WorkflowNode

创建结束节点

pub fn task<F, Fut>(id: &str, name: &str, executor: F) -> WorkflowNode

where F: Fn(WorkflowContext, WorkflowValue) -> Fut + Send + Sync + 'static, Fut: Future<Output = Result<WorkflowValue, String>> + Send + 'static,

创建任务节点

pub fn agent<F, Fut>(id: &str, name: &str, agent_executor: F) -> WorkflowNode

where F: Fn(WorkflowContext, WorkflowValue) -> Fut + Send + Sync + 'static, Fut: Future<Output = Result<WorkflowValue, String>> + Send + 'static,

创建智能体节点

pub fn condition<F, Fut>(id: &str, name: &str, condition_fn: F) -> WorkflowNode

where F: Fn(WorkflowContext, WorkflowValue) -> Fut + Send + Sync + 'static, Fut: Future<Output = bool> + Send + 'static,

创建条件节点

pub fn parallel(id: &str, name: &str, branches: Vec<&str>) -> WorkflowNode

创建并行节点

pub fn join(id: &str, name: &str, wait_for: Vec<&str>) -> WorkflowNode

创建聚合节点

pub fn join_with_transform<F, Fut>( id: &str, name: &str, wait_for: Vec<&str>, transform: F, ) -> WorkflowNode

where F: Fn(HashMap<String, WorkflowValue>) -> Fut + Send + Sync + 'static, Fut: Future<Output = WorkflowValue> + Send + 'static,

创建聚合节点（带转换函数）

pub fn loop_node<F, Fut, C, CFut>( id: &str, name: &str, body: F, condition: C, max_iterations: u32, ) -> WorkflowNode

where F: Fn(WorkflowContext, WorkflowValue) -> Fut + Send + Sync + 'static, Fut: Future<Output = Result<WorkflowValue, String>> + Send + 'static, C: Fn(WorkflowContext, WorkflowValue) -> CFut + Send + Sync + 'static, CFut: Future<Output = bool> + Send + 'static,

创建循环节点

pub fn sub_workflow(id: &str, name: &str, sub_workflow_id: &str) -> WorkflowNode

创建子工作流节点

pub fn wait(id: &str, name: &str, event_type: &str) -> WorkflowNode

创建等待节点

pub fn transform<F, Fut>(id: &str, name: &str, transform_fn: F) -> WorkflowNode

where F: Fn(HashMap<String, WorkflowValue>) -> Fut + Send + Sync + 'static, Fut: Future<Output = WorkflowValue> + Send + 'static,

创建数据转换节点

pub fn llm_agent(id: &str, name: &str, agent: Arc<LLMAgent>) -> WorkflowNode

创建 LLM 智能体节点（使用 LLMAgentBuilder）

这个方法接受 LLMAgentBuilder，构建 LLMAgent 并创建节点。 Agent 将被包装在闭包中以便在工作流中执行。

pub fn llm_agent_with_template( id: &str, name: &str, agent: Arc<LLMAgent>, prompt_template: String, ) -> WorkflowNode

创建 LLM 智能体节点（使用自定义 prompt 模板）

允许使用 Jinja-style 模板格式化输入，例如：

Process this data: {{ input }}

pub fn with_description(self, desc: &str) -> WorkflowNode

设置描述

pub fn with_retry(self, policy: RetryPolicy) -> WorkflowNode

设置重试策略

pub fn with_timeout(self, timeout_ms: u64) -> WorkflowNode

设置超时

pub fn with_branch( self, condition_name: &str, target_node_id: &str, ) -> WorkflowNode

添加条件分支

pub fn id(&self) -> &str

获取节点 ID

pub fn node_type(&self) -> &NodeType

获取节点类型

pub fn parallel_branches(&self) -> &[String]

获取并行分支

pub fn join_nodes(&self) -> &[String]

获取聚合等待节点

pub fn condition_branches(&self) -> &HashMap<String, String>

获取条件分支

pub fn sub_workflow_id(&self) -> Option<&str>

获取子工作流 ID

pub fn wait_event_type(&self) -> Option<&str>

获取等待事件类型

pub async fn execute( &self, ctx: &WorkflowContext, input: WorkflowValue, ) -> NodeResult

执行节点