agent-workflow/dist/agent-workflow.umd.cjs.map

A powerful workflow engine supporting DAG (Directed Acyclic Graph) task scheduling, dynamic task generation, and intelligent strategy systems.

{"version":3,"file":"agent-workflow.umd.cjs","sources":["../src/workflow/ContextManager.ts","../src/workflow/WorkflowBuilder.ts","../src/workflow/TaskRegistry.ts"],"sourcesContent":["//上下文管理器\n// 上下文用于任务之间的数据共享，并动态更新\nimport type { TaskInput } from \"./Task\";\n\nexport class ContextManager {\n  private context: TaskInput = {};\n\n  // 获取上下文中的数据\n  // biome-ignore lint/suspicious/noExplicitAny: <explanation>\n  get(key: string): any {\n    return this.context[key];\n  }\n\n  // 设置上下文中的数据\n  // biome-ignore lint/suspicious/noExplicitAny: <explanation>\n  set(key: string, value: any): void {\n    this.context[key] = value;\n  }\n\n  // 获取完整上下文\n  getAll(): TaskInput {\n    return this.context;\n  }\n\n  // 清除上下文\n  clear(): void {\n    this.context = {};\n  }\n}\n","import { ContextManager } from './ContextManager';\nimport type { TaskInput } from './Task';\n\n// DAG任务抽象基类定义 - 确保依赖关系一致性\nexport abstract class DAGTask {\n  abstract name: string;\n  public dependsOn: DAGTask[] = [];\n\n  constructor(dependencies: DAGTask[] = []) {\n    this.dependsOn = dependencies;\n  }\n\n  abstract execute(input: TaskInput): Promise<Record<string, any>>;\n}\n\n// 🔄 流式DAG任务抽象类（扩展）\nexport abstract class StreamingDAGTask extends DAGTask {\n  executeStream?(\n    input: TaskInput\n  ): AsyncGenerator<StreamChunk, Record<string, any>, unknown>;\n  isStreaming?: boolean;\n}\n\n// 🌊 流式数据块\nexport interface StreamChunk {\n  type: 'progress' | 'data' | 'error' | 'complete';\n  taskName: string;\n  content?: any;\n  progress?: number;\n  timestamp: number;\n  metadata?: Record<string, any>;\n}\n\n// 🔄 流式工作流结果\nexport interface StreamingWorkflowResult {\n  stream: AsyncGenerator<StreamChunk, WorkflowResult, unknown>;\n  getResult(): Promise<WorkflowResult>;\n}\n\n// 核心配置接口\nexport interface WorkflowConfig {\n  enableStreaming?: boolean;\n  retryAttempts?: number;\n  timeoutMs?: number;\n  maxDynamicSteps?: number;\n}\n\n// 统一的工作流上下文\nexport interface WorkflowContext {\n  readonly data: Record<string, unknown>;\n  get<T>(key: string): T | undefined;\n  set<T>(key: string, value: T): void;\n  getAll(): Record<string, unknown>;\n  clear(): void;\n  getExecutionHistory(): TaskExecutionResult[];\n  getLastResult(): any;\n}\n\n// 任务执行结果\nexport interface TaskExecutionResult {\n  taskName: string;\n  status: 'completed' | 'failed' | 'skipped';\n  output?: any;\n  error?: string;\n  duration: number;\n  timestamp: number;\n}\n\n// 工作流执行结果\nexport interface WorkflowResult<T = any> {\n  success: boolean;\n  data?: T;\n  error?: Error;\n  executionTime: number;\n  taskResults: Map<string, TaskExecutionResult>;\n  dynamicTasksGenerated?: number;\n  totalSteps?: number;\n}\n\n// 动态任务生成策略\nexport interface DynamicStrategy {\n  name: string;\n  condition: (context: WorkflowContext, result?: any) => boolean;\n  generator: (context: WorkflowContext) => Promise<DAGTask[]>;\n  priority?: number;\n  once?: boolean;\n}\n\n// 🤖 AI SDK 兼容的流式任务抽象类\nexport abstract class AISDKStreamingTask extends DAGTask {\n  executeStreamAI?(input: TaskInput): Promise<{\n    textStream?: AsyncIterable<string>;\n    fullStream?: AsyncIterable<any>;\n    toDataStreamResponse?: () => Response;\n    toReadableStream?: () => ReadableStream;\n  }>;\n  isAISDKStreaming?: boolean;\n}\n\n// 🌊 AI SDK 流式工作流结果\nexport interface AISDKStreamingWorkflowResult {\n  textStream: AsyncIterable<string>;\n  fullStream: AsyncIterable<any>;\n  toDataStreamResponse(): Response;\n  toReadableStream(): ReadableStream;\n  getResult(): Promise<WorkflowResult>;\n}\n\n// 主要的工作流构建器\nexport class WorkflowBuilder {\n  private config: WorkflowConfig = {};\n  private staticTasks: DAGTask[] = [];\n\n  private dynamicStrategies: DynamicStrategy[] = [];\n\n  // 🔒 私有构造函数 - 防止直接实例化\n  private constructor() {}\n\n  // 🏭 工厂方法 - 唯一创建实例的方式\n  static create(): WorkflowBuilder {\n    return new WorkflowBuilder();\n  }\n\n  // 配置方法\n  withConfig(config: Partial<WorkflowConfig>): this {\n    this.config = { ...this.config, ...config };\n    return this;\n  }\n\n  withRetry(attempts: number): this {\n    this.config.retryAttempts = attempts;\n    return this;\n  }\n\n  withTimeout(timeoutMs: number): this {\n    this.config.timeoutMs = timeoutMs;\n    return this;\n  }\n\n  // 静态任务构建\n  addTask(task: DAGTask): this {\n    this.staticTasks.push(task);\n    return this;\n  }\n\n  addTasks(tasks: DAGTask[]): this {\n    this.staticTasks.push(...tasks);\n    return this;\n  }\n\n  // 添加动态策略\n  addDynamicStrategy(strategy: DynamicStrategy): this {\n    this.dynamicStrategies.push(strategy);\n    return this;\n  }\n\n  // 条件任务生成 - 语法糖\n  whenCondition(\n    condition: (context: WorkflowContext) => boolean,\n    taskGenerator: (context: WorkflowContext) => Promise<DAGTask[]>\n  ): this {\n    return this.addDynamicStrategy({\n      name: `condition-${this.dynamicStrategies.length}`,\n      condition: (context) => {\n        // Wait for all current tasks to complete before checking conditions\n        const history = context.getExecutionHistory();\n        const completedTasks = history.filter((h) => h.status === 'completed');\n\n        // If there are completed tasks, check the condition\n        if (completedTasks.length > 0) {\n          return condition(context);\n        }\n        return false;\n      },\n      generator: taskGenerator,\n      once: true,\n    });\n  }\n\n  // 基于结果的任务生成\n  onTaskComplete(\n    taskName: string,\n    resultProcessor: (\n      result: any,\n      context: WorkflowContext\n    ) => Promise<DAGTask[]>\n  ): this {\n    return this.addDynamicStrategy({\n      name: `on-complete-${taskName}`,\n      condition: (context) => {\n        const history = context.getExecutionHistory();\n        return history.some(\n          (h) => h.taskName === taskName && h.status === 'completed'\n        );\n      },\n      generator: async (context) => {\n        const history = context.getExecutionHistory();\n        const taskResult = history.find((h) => h.taskName === taskName);\n        return resultProcessor(taskResult?.output, context);\n      },\n      once: true,\n    });\n  }\n\n  // 基于上下文变化的任务生成\n  onContextChange(\n    contextKey: string,\n    taskGenerator: (value: any, context: WorkflowContext) => Promise<DAGTask[]>\n  ): this {\n    return this.addDynamicStrategy({\n      name: `on-context-${contextKey}`,\n      condition: (context) => {\n        // Check if there's a new context value that hasn't been triggered before\n        const value = context.get(contextKey);\n        return value !== undefined;\n      },\n      generator: async (context) => {\n        const value = context.get(contextKey);\n        return taskGenerator(value, context);\n      },\n      once: true,\n    });\n  }\n\n  // 构建工作流实例\n  build(): Workflow {\n    if (this.dynamicStrategies.length > 0) {\n      return new StrategyBasedWorkflow(\n        this.config,\n        this.staticTasks,\n        this.dynamicStrategies\n      );\n    }\n\n    return new StaticWorkflow(this.config, this.staticTasks);\n  }\n\n  // 🌊 构建流式工作流实例\n  buildStreaming(): StreamingWorkflow {\n    this.config.enableStreaming = true;\n\n    if (this.dynamicStrategies.length > 0) {\n      return new StreamingStrategyBasedWorkflow(\n        this.config,\n        this.staticTasks,\n        this.dynamicStrategies\n      );\n    }\n\n    return new StreamingStaticWorkflow(this.config, this.staticTasks);\n  }\n\n  // 🤖 构建AI SDK兼容的流式工作流\n  buildAISDKStreaming(): AISDKStreamingWorkflow {\n    this.config.enableStreaming = true;\n\n    if (this.dynamicStrategies.length > 0) {\n      return new AISDKStreamingStrategyWorkflow(\n        this.config,\n        this.staticTasks,\n        this.dynamicStrategies\n      );\n    }\n\n    return new AISDKStreamingStaticWorkflow(this.config, this.staticTasks);\n  }\n}\n\n// 工作流接口\nexport interface Workflow {\n  execute(input?: TaskInput): Promise<WorkflowResult>;\n  executeStream?(input?: TaskInput): StreamingWorkflowResult;\n  getContext(): WorkflowContext;\n  getResults(): Map<string, TaskExecutionResult>;\n}\n\n// 🌊 流式工作流接口\nexport interface StreamingWorkflow extends Workflow {\n  executeStream(input?: TaskInput): StreamingWorkflowResult;\n}\n\n// 🤖 AI SDK 兼容的流式工作流接口\nexport interface AISDKStreamingWorkflow extends Workflow {\n  executeStreamAISDK(input?: TaskInput): AISDKStreamingWorkflowResult;\n}\n\n// 增强的上下文实现\nclass EnhancedWorkflowContext implements WorkflowContext {\n  private internalContext: ContextManager;\n  private executionHistory: TaskExecutionResult[] = [];\n\n  constructor() {\n    this.internalContext = new ContextManager();\n  }\n\n  get data(): Record<string, unknown> {\n    return this.internalContext.getAll();\n  }\n\n  get<T>(key: string): T | undefined {\n    return this.internalContext.get(key);\n  }\n\n  set<T>(key: string, value: T): void {\n    this.internalContext.set(key, value);\n  }\n\n  getAll(): Record<string, unknown> {\n    return this.internalContext.getAll();\n  }\n\n  clear(): void {\n    this.internalContext.clear();\n    this.executionHistory = [];\n  }\n\n  getExecutionHistory(): TaskExecutionResult[] {\n    return [...this.executionHistory];\n  }\n\n  getLastResult(): any {\n    const lastExecution =\n      this.executionHistory[this.executionHistory.length - 1];\n    return lastExecution?.output;\n  }\n\n  addExecutionResult(result: TaskExecutionResult): void {\n    this.executionHistory.push(result);\n  }\n\n  // 内部方法，用于访问原始ContextManager\n  getInternalContext(): ContextManager {\n    return this.internalContext;\n  }\n}\n\n// 基础工作流类\nabstract class BaseWorkflow {\n  protected context: EnhancedWorkflowContext;\n  protected config: WorkflowConfig;\n  protected startTime = 0;\n  protected taskResults: Map<string, TaskExecutionResult> = new Map();\n\n  constructor(config: WorkflowConfig) {\n    this.config = config;\n    this.context = new EnhancedWorkflowContext();\n  }\n\n  abstract execute(input?: TaskInput): Promise<WorkflowResult>;\n\n  getContext(): WorkflowContext {\n    return this.context;\n  }\n\n  getResults(): Map<string, TaskExecutionResult> {\n    return new Map(this.taskResults);\n  }\n\n  protected async executeTask(task: DAGTask): Promise<void> {\n    const taskStartTime = Date.now();\n\n    try {\n      // 直接执行任务\n      const input = this.context.getAll();\n      const output = await task.execute(input);\n\n      // 将任务输出存储在任务名称下\n      const taskName = task.name || '';\n      this.context.set(taskName, output);\n\n      // 也将输出的各个字段直接存储到上下文（保持兼容性）\n      for (const [key, value] of Object.entries(output)) {\n        this.context.set(key, value);\n      }\n\n      // 生成唯一的任务键，处理重复名称\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'completed',\n        output: output,\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n    } catch (error) {\n      // 生成唯一的任务键，处理重复名称\n      const taskName = task.name || '';\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'failed',\n        error: error instanceof Error ? error.message : String(error),\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n      throw error;\n    }\n  }\n}\n\n// 静态工作流实现\nclass StaticWorkflow extends BaseWorkflow implements Workflow {\n  protected tasks: DAGTask[];\n\n  constructor(config: WorkflowConfig, tasks: DAGTask[]) {\n    super(config);\n    this.tasks = tasks;\n  }\n\n  async execute(input: TaskInput = {}): Promise<WorkflowResult> {\n    this.startTime = Date.now();\n\n    try {\n      // Set initial input\n      Object.entries(input).forEach(([key, value]) => {\n        this.context.set(key, value);\n      });\n\n      // Execute DAG tasks\n      await this.executeDAG();\n\n      return {\n        success: true,\n        data: this.context.getAll(),\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n      };\n    } catch (error) {\n      return {\n        success: false,\n        error: error as Error,\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n      };\n    }\n  }\n\n  private async executeDAG(): Promise<void> {\n    const levels = this.computeExecutionLevels();\n    let hasError = false;\n    let lastError: Error | undefined;\n\n    for (const level of levels) {\n      // Execute all tasks at the current level, don't stop due to individual task failures\n      const results = await Promise.allSettled(\n        level.map((task) => this.executeTask(task))\n      );\n\n      // Check for failed tasks\n      for (const result of results) {\n        if (result.status === 'rejected') {\n          hasError = true;\n          lastError = result.reason;\n        }\n      }\n    }\n\n    // If any tasks failed, throw the last error\n    if (hasError && lastError) {\n      throw lastError;\n    }\n  }\n\n  protected computeExecutionLevels(): DAGTask[][] {\n    // Efficient topological sorting implementation\n    const graph = new Map<DAGTask, DAGTask[]>();\n    const inDegree = new Map<DAGTask, number>();\n\n    // Initialize\n    for (const task of this.tasks) {\n      graph.set(task, []);\n      inDegree.set(task, 0);\n    }\n\n    // Build dependency graph\n    for (const task of this.tasks) {\n      if (task.dependsOn) {\n        for (const dep of task.dependsOn) {\n          graph.get(dep)?.push(task);\n          inDegree.set(task, (inDegree.get(task) || 0) + 1);\n        }\n      }\n    }\n\n    // Layered execution\n    const levels: DAGTask[][] = [];\n    const queue = this.tasks.filter((task) => inDegree.get(task) === 0);\n    let processedCount = 0;\n\n    while (queue.length > 0) {\n      const currentLevel = [...queue];\n      levels.push(currentLevel);\n      processedCount += currentLevel.length;\n      queue.length = 0;\n\n      for (const task of currentLevel) {\n        for (const next of graph.get(task) || []) {\n          const newDegree = (inDegree.get(next) || 0) - 1;\n          inDegree.set(next, newDegree);\n          if (newDegree === 0) {\n            queue.push(next);\n          }\n        }\n      }\n    }\n\n    // Detect circular dependencies\n    if (processedCount < this.tasks.length) {\n      throw new Error(\n        'Circular dependency detected, unable to execute workflow'\n      );\n    }\n\n    return levels;\n  }\n}\n\n// 策略驱动的动态工作流\nclass StrategyBasedWorkflow extends BaseWorkflow implements Workflow {\n  protected tasks: DAGTask[];\n  protected strategies: DynamicStrategy[];\n  protected dynamicTasksGenerated = 0;\n  protected currentStep = 0;\n  protected usedStrategies: Set<string> = new Set();\n\n  constructor(\n    config: WorkflowConfig,\n    tasks: DAGTask[],\n    strategies: DynamicStrategy[]\n  ) {\n    super(config);\n    this.tasks = [...tasks];\n    this.strategies = strategies;\n  }\n\n  async execute(input: TaskInput = {}): Promise<WorkflowResult> {\n    this.startTime = Date.now();\n    this.dynamicTasksGenerated = 0;\n    this.currentStep = 0;\n    this.usedStrategies.clear();\n\n    try {\n      // Set initial input\n      Object.entries(input).forEach(([key, value]) => {\n        this.context.set(key, value);\n      });\n\n      // Dynamic execution loop\n      while (this.hasTasksToExecute() && this.shouldContinue()) {\n        this.currentStep++;\n\n        // Execute current batch of tasks\n        await this.executeCurrentBatch();\n\n        // Evaluate strategies and generate new tasks\n        await this.evaluateStrategiesAndGenerateTasks();\n      }\n\n      // Check if unable to continue due to circular dependencies\n      if (!this.hasTasksToExecute() && this.shouldContinue()) {\n        const processedTaskNames = new Set(\n          this.context\n            .getExecutionHistory()\n            .filter(\n              (h) =>\n                h.status === 'completed' ||\n                h.status === 'failed' ||\n                h.status === 'skipped'\n            )\n            .map((h) => h.taskName)\n        );\n\n        const unprocessedTasks = this.tasks.filter(\n          (task) => !processedTaskNames.has(task.name || '')\n        );\n\n        if (unprocessedTasks.length > 0) {\n          throw new Error(\n            'Circular dependency detected, unable to execute workflow'\n          );\n        }\n      }\n\n      return {\n        success: true,\n        data: this.context.getAll(),\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n        dynamicTasksGenerated: this.dynamicTasksGenerated,\n        totalSteps: this.currentStep,\n      };\n    } catch (error) {\n      return {\n        success: false,\n        error: error as Error,\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n        dynamicTasksGenerated: this.dynamicTasksGenerated,\n        totalSteps: this.currentStep,\n      };\n    }\n  }\n\n  protected hasTasksToExecute(): boolean {\n    const readyTasks = this.getReadyTasks();\n    return readyTasks.length > 0;\n  }\n\n  protected shouldContinue(): boolean {\n    const maxSteps = this.config.maxDynamicSteps || 50;\n    return this.currentStep < maxSteps;\n  }\n\n  private async executeCurrentBatch(): Promise<void> {\n    const readyTasks = this.getReadyTasks();\n\n    if (readyTasks.length === 0) return;\n\n    // Execute ready tasks in parallel, don't stop due to individual task failures\n    const results = await Promise.allSettled(\n      readyTasks.map((task) => this.executeTask(task))\n    );\n\n    // Log failed tasks but continue execution\n    for (const result of results) {\n      if (result.status === 'rejected') {\n        console.warn('Task execution failed:', result.reason);\n      }\n    }\n  }\n\n  protected getReadyTasks(): DAGTask[] {\n    const processedTaskNames = new Set(\n      this.context\n        .getExecutionHistory()\n        .filter(\n          (h) =>\n            h.status === 'completed' ||\n            h.status === 'failed' ||\n            h.status === 'skipped'\n        )\n        .map((h) => h.taskName)\n    );\n\n    return this.tasks.filter((task) => {\n      // Check if already processed (completed, failed, or skipped)\n      if (processedTaskNames.has(task.name || '')) {\n        return false;\n      }\n\n      // Check if dependencies are satisfied (as long as dependency tasks have been processed, regardless of success/failure)\n      if (task.dependsOn) {\n        return task.dependsOn.every((dep) =>\n          processedTaskNames.has(dep.name || '')\n        );\n      }\n\n      return true;\n    });\n  }\n\n  protected async evaluateStrategiesAndGenerateTasks(): Promise<void> {\n    // Sort strategies by priority\n    const sortedStrategies = [...this.strategies].sort(\n      (a, b) => (b.priority || 0) - (a.priority || 0)\n    );\n\n    for (const strategy of sortedStrategies) {\n      // Skip already used one-time strategies\n      if (strategy.once && this.usedStrategies.has(strategy.name)) {\n        continue;\n      }\n\n      try {\n        const lastResult = this.context.getLastResult();\n\n        if (strategy.condition(this.context, lastResult)) {\n          const newTasks = await strategy.generator(this.context);\n\n          if (newTasks.length > 0) {\n            this.tasks.push(...newTasks);\n            this.dynamicTasksGenerated += newTasks.length;\n\n            if (strategy.once) {\n              this.usedStrategies.add(strategy.name);\n            }\n\n            console.log(\n              `🎯 Strategy \"${strategy.name}\" generated ${newTasks.length} new tasks`\n            );\n          }\n        }\n      } catch (error) {\n        console.error(`Strategy \"${strategy.name}\" execution failed:`, error);\n      }\n    }\n  }\n}\n\n// 🌊 流式静态工作流实现\nclass StreamingStaticWorkflow\n  extends StaticWorkflow\n  implements StreamingWorkflow\n{\n  private streamResult: WorkflowResult | undefined;\n\n  executeStream(input: TaskInput = {}): StreamingWorkflowResult {\n    this.streamResult = undefined; // Reset\n    const stream = this.createExecutionStream(input);\n\n    const resultPromise = (async (): Promise<WorkflowResult> => {\n      // Consume stream until completion, generator will set streamResult\n      for await (const chunk of stream) {\n        // Stream processing\n      }\n\n      // Return streaming execution result\n      return (\n        this.streamResult || {\n          success: false,\n          error: new Error('Streaming execution not completed'),\n          executionTime: 0,\n          taskResults: new Map(),\n        }\n      );\n    })();\n\n    return {\n      stream: this.createExecutionStream(input),\n      getResult: () => resultPromise,\n    };\n  }\n\n  private async *createExecutionStream(\n    input: TaskInput\n  ): AsyncGenerator<StreamChunk, WorkflowResult, unknown> {\n    this.startTime = Date.now();\n\n    try {\n      // Set initial input\n      Object.entries(input).forEach(([key, value]) => {\n        this.context.set(key, value);\n      });\n\n      yield {\n        type: 'progress',\n        taskName: 'workflow',\n        content: 'Workflow execution started',\n        progress: 0,\n        timestamp: Date.now(),\n      };\n\n      // Execute DAG tasks with streaming output\n      yield* this.executeDAGStream();\n\n      const result: WorkflowResult = {\n        success: true,\n        data: this.context.getAll(),\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n      };\n\n      // Save result for getResult usage\n      this.streamResult = result;\n\n      yield {\n        type: 'complete',\n        taskName: 'workflow',\n        content: 'Workflow execution completed',\n        progress: 100,\n        timestamp: Date.now(),\n      };\n\n      return result;\n    } catch (error) {\n      const errorResult: WorkflowResult = {\n        success: false,\n        error: error as Error,\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n      };\n\n      // Save error result\n      this.streamResult = errorResult;\n\n      yield {\n        type: 'error',\n        taskName: 'workflow',\n        content: error instanceof Error ? error.message : String(error),\n        timestamp: Date.now(),\n      };\n\n      return errorResult;\n    }\n  }\n\n  private async *executeDAGStream(): AsyncGenerator<\n    StreamChunk,\n    void,\n    unknown\n  > {\n    const levels = this.computeExecutionLevels();\n    const totalTasks = this.tasks.length;\n    let completedTasks = 0;\n\n    for (const level of levels) {\n      // Execute all tasks at the current level\n      const taskPromises = level.map((task) => this.executeTaskStream(task));\n\n      for await (const taskStream of taskPromises) {\n        for await (const chunk of taskStream) {\n          yield chunk;\n          if (chunk.type === 'complete') {\n            completedTasks++;\n            yield {\n              type: 'progress',\n              taskName: 'workflow',\n              content: `Completed ${completedTasks}/${totalTasks} tasks`,\n              progress: Math.round((completedTasks / totalTasks) * 100),\n              timestamp: Date.now(),\n            };\n          }\n        }\n      }\n    }\n  }\n\n  private async *executeTaskStream(\n    task: StreamingDAGTask\n  ): AsyncGenerator<StreamChunk, void, unknown> {\n    const taskStartTime = Date.now();\n\n    try {\n      yield {\n        type: 'progress',\n        taskName: task.name,\n        content: `Starting task execution: ${task.name}`,\n        progress: 0,\n        timestamp: Date.now(),\n      };\n\n      const input = this.context.getAll();\n      let output: Record<string, any>;\n\n      // Check if it's a streaming task\n      if (task.isStreaming && task.executeStream) {\n        const generator = task.executeStream(input);\n        let finalResult: Record<string, any> = {};\n\n        try {\n          // Iterate generator and yield all intermediate results\n          while (true) {\n            const { value, done } = await generator.next();\n            if (done) {\n              finalResult = value || {};\n              break;\n            }\n            // Yield streaming data\n            yield value;\n          }\n        } catch (error) {\n          // Error during streaming task execution\n          throw error;\n        }\n\n        output = finalResult;\n      } else {\n        // Regular task execution\n        output = await task.execute(input);\n      }\n\n      // Store results\n      const taskName = task.name || '';\n      this.context.set(taskName, output);\n\n      for (const [key, value] of Object.entries(output)) {\n        this.context.set(key, value);\n      }\n\n      // Generate unique task key\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'completed',\n        output: output,\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n\n      yield {\n        type: 'complete',\n        taskName: task.name,\n        content: `Task completed: ${task.name}`,\n        progress: 100,\n        timestamp: Date.now(),\n        metadata: { duration: result.duration },\n      };\n    } catch (error) {\n      const taskName = task.name || '';\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'failed',\n        error: error instanceof Error ? error.message : String(error),\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n\n      yield {\n        type: 'error',\n        taskName: task.name,\n        content: error instanceof Error ? error.message : String(error),\n        timestamp: Date.now(),\n      };\n    }\n  }\n}\n\n// 🌊 流式策略工作流实现\nclass StreamingStrategyBasedWorkflow\n  extends StrategyBasedWorkflow\n  implements StreamingWorkflow\n{\n  private streamResult: WorkflowResult | undefined;\n\n  executeStream(input: TaskInput = {}): StreamingWorkflowResult {\n    this.streamResult = undefined; // Reset\n    const stream = this.createDynamicExecutionStream(input);\n\n    const resultPromise = (async (): Promise<WorkflowResult> => {\n      // Consume stream until completion, generator will set streamResult\n      for await (const chunk of stream) {\n        // Stream processing\n      }\n\n      // Return streaming execution result\n      return (\n        this.streamResult || {\n          success: false,\n          error: new Error('Streaming execution not completed'),\n          executionTime: 0,\n          taskResults: new Map(),\n        }\n      );\n    })();\n\n    return {\n      stream: this.createDynamicExecutionStream(input),\n      getResult: () => resultPromise,\n    };\n  }\n\n  private async *createDynamicExecutionStream(\n    input: TaskInput\n  ): AsyncGenerator<StreamChunk, WorkflowResult, unknown> {\n    this.startTime = Date.now();\n    this.dynamicTasksGenerated = 0;\n    this.currentStep = 0;\n    this.usedStrategies.clear();\n\n    try {\n      Object.entries(input).forEach(([key, value]) => {\n        this.context.set(key, value);\n      });\n\n      yield {\n        type: 'progress',\n        taskName: 'workflow',\n        content: 'Dynamic workflow execution started',\n        progress: 0,\n        timestamp: Date.now(),\n      };\n\n      // Dynamic execution loop\n      while (this.hasTasksToExecute() && this.shouldContinue()) {\n        this.currentStep++;\n\n        yield {\n          type: 'progress',\n          taskName: 'workflow',\n          content: `Executing step ${this.currentStep}`,\n          progress: Math.min(\n            (this.currentStep / (this.config.maxDynamicSteps || 50)) * 100,\n            90\n          ),\n          timestamp: Date.now(),\n        };\n\n        // Execute current batch of tasks\n        const readyTasks = this.getReadyTasks();\n        for (const task of readyTasks) {\n          yield* this.executeTaskStreamForStrategy(task as StreamingDAGTask);\n        }\n\n        // Evaluate strategies and generate new tasks\n        await this.evaluateStrategiesAndGenerateTasks();\n\n        if (this.dynamicTasksGenerated > 0) {\n          yield {\n            type: 'data',\n            taskName: 'strategy',\n            content: `Dynamically generated ${this.dynamicTasksGenerated} new tasks`,\n            timestamp: Date.now(),\n          };\n        }\n      }\n\n      const result: WorkflowResult = {\n        success: true,\n        data: this.context.getAll(),\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n        dynamicTasksGenerated: this.dynamicTasksGenerated,\n        totalSteps: this.currentStep,\n      };\n\n      // Save result for getResult usage\n      this.streamResult = result;\n\n      yield {\n        type: 'complete',\n        taskName: 'workflow',\n        content: 'Dynamic workflow execution completed',\n        progress: 100,\n        timestamp: Date.now(),\n      };\n\n      return result;\n    } catch (error) {\n      const errorResult: WorkflowResult = {\n        success: false,\n        error: error as Error,\n        executionTime: Date.now() - this.startTime,\n        taskResults: this.taskResults,\n        dynamicTasksGenerated: this.dynamicTasksGenerated,\n        totalSteps: this.currentStep,\n      };\n\n      // Save error result\n      this.streamResult = errorResult;\n\n      yield {\n        type: 'error',\n        taskName: 'workflow',\n        content: error instanceof Error ? error.message : String(error),\n        timestamp: Date.now(),\n      };\n\n      return errorResult;\n    }\n  }\n\n  private async *executeTaskStreamForStrategy(\n    task: StreamingDAGTask\n  ): AsyncGenerator<StreamChunk, void, unknown> {\n    const taskStartTime = Date.now();\n\n    try {\n      yield {\n        type: 'progress',\n        taskName: task.name,\n        content: `Starting dynamic task execution: ${task.name}`,\n        progress: 0,\n        timestamp: Date.now(),\n      };\n\n      const input = this.context.getAll();\n      let output: Record<string, any>;\n\n      // Check if it's a streaming task\n      if (task.isStreaming && task.executeStream) {\n        const generator = task.executeStream(input);\n        let finalResult: Record<string, any> = {};\n\n        try {\n          // Iterate generator and yield all intermediate results\n          while (true) {\n            const { value, done } = await generator.next();\n            if (done) {\n              finalResult = value || {};\n              break;\n            }\n            // Yield streaming data\n            yield value;\n          }\n        } catch (error) {\n          // Error during streaming task execution\n          throw error;\n        }\n\n        output = finalResult;\n      } else {\n        // Regular task execution\n        output = await task.execute(input);\n      }\n\n      // Store results (same logic as base class)\n      const taskName = task.name || '';\n      this.context.set(taskName, output);\n\n      for (const [key, value] of Object.entries(output)) {\n        this.context.set(key, value);\n      }\n\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'completed',\n        output: output,\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n\n      yield {\n        type: 'complete',\n        taskName: task.name,\n        content: `Dynamic task completed: ${task.name}`,\n        progress: 100,\n        timestamp: Date.now(),\n        metadata: { duration: result.duration },\n      };\n    } catch (error) {\n      console.warn('Dynamic task execution failed:', error);\n\n      const taskName = task.name || '';\n      let uniqueKey = taskName;\n      let counter = 1;\n      while (this.taskResults.has(uniqueKey)) {\n        uniqueKey = `${taskName}_${counter}`;\n        counter++;\n      }\n\n      const result: TaskExecutionResult = {\n        taskName: taskName,\n        status: 'failed',\n        error: error instanceof Error ? error.message : String(error),\n        duration: Date.now() - taskStartTime,\n        timestamp: Date.now(),\n      };\n\n      this.taskResults.set(uniqueKey, result);\n      this.context.addExecutionResult(result);\n\n      yield {\n        type: 'error',\n        taskName: task.name,\n        content: error instanceof Error ? error.message : String(error),\n        timestamp: Date.now(),\n      };\n    }\n  }\n}\n\n// 🤖 AI SDK 兼容的静态流式工作流\nclass AISDKStreamingStaticWorkflow\n  extends StaticWorkflow\n  implements AISDKStreamingWorkflow\n{\n  executeStreamAISDK(input: TaskInput = {}): AISDKStreamingWorkflowResult {\n    const resultPromise = this.execute(input);\n\n    // 创建组合的流\n    const combinedStreams = this.createCombinedAISDKStreams(input);\n\n    return {\n      textStream: combinedStreams.textStream,\n      fullStream: combinedStreams.fullStream,\n      toDataStreamResponse: () => combinedStreams.toDataStreamResponse(),\n      toReadableStream: () => combinedStreams.toReadableStream(),\n      getResult: () => resultPromise,\n    };\n  }\n\n  private createCombinedAISDKStreams(input: TaskInput) {\n    const textChunks: string[] = [];\n    const dataChunks: any[] = [];\n\n    const self = this;\n\n    // 创建异步生成器函数\n    const textStreamGenerator = async function* (): AsyncGenerator<\n      string,\n      void,\n      unknown\n    > {\n      try {\n        Object.entries(input).forEach(([key, value]) => {\n          self.context.set(key, value);\n        });\n\n        const levels = self.computeExecutionLevels();\n\n        for (const level of levels) {\n          for (const task of level) {\n            const aiTask = task as AISDKStreamingTask;\n\n            if (aiTask.isAISDKStreaming && aiTask.executeStreamAI) {\n              const streamResult = await aiTask.executeStreamAI(\n                self.context.getAll()\n              );\n\n              if (streamResult.textStream) {\n                for await (const chunk of streamResult.textStream) {\n                  textChunks.push(chunk);\n                  yield chunk;\n                }\n              }\n            } else {\n              // 普通任务，生成状态文本\n              const statusText = `[${task.name}] Task completed\\n`;\n              textChunks.push(statusText);\n              yield statusText;\n\n              // 执行任务\n              await self.executeTask(task);\n            }\n          }\n        }\n      } catch (error) {\n        const errorText = `Error: ${\n          error instanceof Error ? error.message : String(error)\n        }\\n`;\n        textChunks.push(errorText);\n        yield errorText;\n      }\n    };\n\n    const fullStreamGenerator = async function* (): AsyncGenerator<\n      any,\n      void,\n      unknown\n    > {\n      try {\n        Object.entries(input).forEach(([key, value]) => {\n          self.context.set(key, value);\n        });\n\n        yield { type: 'workflow-start', data: { status: 'starting' } };\n\n        const levels = self.computeExecutionLevels();\n\n        for (const level of levels) {\n          for (const task of level) {\n            const aiTask = task as AISDKStreamingTask;\n\n            yield { type: 'task-start', data: { taskName: task.name } };\n\n            if (aiTask.isAISDKStreaming && aiTask.executeStreamAI) {\n              const streamResult = await aiTask.executeStreamAI(\n                self.context.getAll()\n              );\n\n              if (streamResult.fullStream) {\n                for await (const chunk of streamResult.fullStream) {\n                  dataChunks.push(chunk);\n                  yield { type: 'ai-chunk', data: chunk };\n                }\n              }\n            } else {\n              // 执行普通任务\n              await self.executeTask(task);\n              yield {\n                type: 'task-complete',\n                data: {\n                  taskName: task.name,\n                  result: self.context.get(task.name),\n                },\n              };\n            }\n          }\n        }\n\n        yield {\n          type: 'workflow-complete',\n          data: {\n            status: 'completed',\n            finalResult: self.context.getAll(),\n          },\n        };\n      } catch (error) {\n        yield {\n          type: 'workflow-error',\n          data: {\n            error: error instanceof Error ? error.message : String(error),\n          },\n        };\n      }\n    };\n\n    return {\n      get textStream() {\n        return textStreamGenerator();\n      },\n      get fullStream() {\n        return fullStreamGenerator();\n      },\n\n      toDataStreamResponse(): Response {\n        const encoder = new TextEncoder();\n\n        const stream = new ReadableStream({\n          async start(controller) {\n            try {\n              for await (const chunk of fullStreamGenerator()) {\n                const data = `data: ${JSON.stringify(chunk)}\\n\\n`;\n                controller.enqueue(encoder.encode(data));\n              }\n              controller.close();\n            } catch (error) {\n              controller.error(error);\n            }\n          },\n        });\n\n        return new Response(stream, {\n          headers: {\n            'Content-Type': 'text/event-stream',\n            'Cache-Control': 'no-cache',\n            Connection: 'keep-alive',\n          },\n        });\n      },\n\n      toReadableStream(): ReadableStream {\n        const encoder = new TextEncoder();\n\n        return new ReadableStream({\n          async start(controller) {\n            try {\n              for await (const textChunk of textStreamGenerator()) {\n                controller.enqueue(encoder.encode(textChunk));\n              }\n              controller.close();\n            } catch (error) {\n              controller.error(error);\n            }\n          },\n        });\n      },\n    };\n  }\n}\n\n// 🤖 AI SDK 兼容的策略流式工作流\nclass AISDKStreamingStrategyWorkflow\n  extends StrategyBasedWorkflow\n  implements AISDKStreamingWorkflow\n{\n  executeStreamAISDK(input: TaskInput = {}): AISDKStreamingWorkflowResult {\n    const resultPromise = this.execute(input);\n\n    // 创建组合的流（动态版本）\n    const combinedStreams = this.createDynamicCombinedAISDKStreams(input);\n\n    return {\n      textStream: combinedStreams.textStream,\n      fullStream: combinedStreams.fullStream,\n      toDataStreamResponse: () => combinedStreams.toDataStreamResponse(),\n      toReadableStream: () => combinedStreams.toReadableStream(),\n      getResult: () => resultPromise,\n    };\n  }\n\n  private createDynamicCombinedAISDKStreams(input: TaskInput) {\n    const textChunks: string[] = [];\n    const dataChunks: any[] = [];\n\n    const self = this;\n\n    const textStreamGenerator = async function* (): AsyncGenerator<\n      string,\n      void,\n      unknown\n    > {\n      try {\n        Object.entries(input).forEach(([key, value]) => {\n          self.context.set(key, value);\n        });\n\n        self.currentStep = 0;\n        self.dynamicTasksGenerated = 0;\n        self.usedStrategies.clear();\n\n        while (self.hasTasksToExecute() && self.shouldContinue()) {\n          self.currentStep++;\n\n          const readyTasks = self.getReadyTasks();\n\n          for (const task of readyTasks) {\n            const aiTask = task as AISDKStreamingTask;\n\n            if (aiTask.isAISDKStreaming && aiTask.executeStreamAI) {\n              const streamResult = await aiTask.executeStreamAI(\n                self.context.getAll()\n              );\n\n              if (streamResult.textStream) {\n                for await (const chunk of streamResult.textStream) {\n                  textChunks.push(chunk);\n                  yield chunk;\n                }\n              }\n            } else {\n              const statusText = `[${task.name}] Task completed\\n`;\n              textChunks.push(statusText);\n              yield statusText;\n\n              await self.executeTask(task);\n            }\n          }\n\n          // 评估动态策略\n          await self.evaluateStrategiesAndGenerateTasks();\n        }\n      } catch (error) {\n        const errorText = `Error: ${\n          error instanceof Error ? error.message : String(error)\n        }\\n`;\n        textChunks.push(errorText);\n        yield errorText;\n      }\n    };\n\n    const fullStreamGenerator = async function* (): AsyncGenerator<\n      any,\n      void,\n      unknown\n    > {\n      try {\n        Object.entries(input).forEach(([key, value]) => {\n          self.context.set(key, value);\n        });\n\n        yield { type: 'dynamic-workflow-start', data: { status: 'starting' } };\n\n        self.currentStep = 0;\n        self.dynamicTasksGenerated = 0;\n        self.usedStrategies.clear();\n\n        while (self.hasTasksToExecute() && self.shouldContinue()) {\n          self.currentStep++;\n\n          yield {\n            type: 'dynamic-step',\n            data: {\n              step: self.currentStep,\n              maxSteps: self.config.maxDynamicSteps || 50,\n            },\n          };\n\n          const readyTasks = self.getReadyTasks();\n\n          for (const task of readyTasks) {\n            const aiTask = task as AISDKStreamingTask;\n\n            yield { type: 'task-start', data: { taskName: task.name } };\n\n            if (aiTask.isAISDKStreaming && aiTask.executeStreamAI) {\n              const streamResult = await aiTask.executeStreamAI(\n                self.context.getAll()\n              );\n\n              if (streamResult.fullStream) {\n                for await (const chunk of streamResult.fullStream) {\n                  dataChunks.push(chunk);\n                  yield { type: 'ai-chunk', data: chunk };\n                }\n              }\n            } else {\n              await self.executeTask(task);\n              yield {\n                type: 'task-complete',\n                data: {\n                  taskName: task.name,\n                  result: self.context.get(task.name),\n                },\n              };\n            }\n          }\n\n          // 评估动态策略\n          const beforeCount = self.tasks.length;\n          await self.evaluateStrategiesAndGenerateTasks();\n          const afterCount = self.tasks.length;\n\n          if (afterCount > beforeCount) {\n            yield {\n              type: 'dynamic-tasks-generated',\n              data: {\n                newTasks: afterCount - beforeCount,\n                totalGenerated: self.dynamicTasksGenerated,\n              },\n            };\n          }\n        }\n\n        yield {\n          type: 'dynamic-workflow-complete',\n          data: {\n            status: 'completed',\n            totalSteps: self.currentStep,\n            dynamicTasksGenerated: self.dynamicTasksGenerated,\n            finalResult: self.context.getAll(),\n          },\n        };\n      } catch (error) {\n        yield {\n          type: 'dynamic-workflow-error',\n          data: {\n            error: error instanceof Error ? error.message : String(error),\n          },\n        };\n      }\n    };\n\n    return {\n      get textStream() {\n        return textStreamGenerator();\n      },\n      get fullStream() {\n        return fullStreamGenerator();\n      },\n\n      toDataStreamResponse(): Response {\n        const encoder = new TextEncoder();\n\n        const stream = new ReadableStream({\n          async start(controller) {\n            try {\n              for await (const chunk of fullStreamGenerator()) {\n                const data = `data: ${JSON.stringify(chunk)}\\n\\n`;\n                controller.enqueue(encoder.encode(data));\n              }\n              controller.close();\n            } catch (error) {\n              controller.error(error);\n            }\n          },\n        });\n\n        return new Response(stream, {\n          headers: {\n            'Content-Type': 'text/event-stream',\n            'Cache-Control': 'no-cache',\n            Connection: 'keep-alive',\n          },\n        });\n      },\n\n      toReadableStream(): ReadableStream {\n        const encoder = new TextEncoder();\n\n        return new ReadableStream({\n          async start(controller) {\n            try {\n              for await (const textChunk of textStreamGenerator()) {\n                controller.enqueue(encoder.encode(textChunk));\n              }\n              controller.close();\n            } catch (error) {\n              controller.error(error);\n            }\n          },\n        });\n      },\n    };\n  }\n}\n","import type { DAGTask } from \"./WorkflowBuilder\";\n\nexport interface TaskDefinition {\n  name: string;\n  description: string;\n  capabilities: string[];\n  createTask: () => DAGTask;\n}\n\nexport class TaskRegistry {\n  private static instance: TaskRegistry;\n  private tasks: Map<string, TaskDefinition> = new Map();\n\n  private constructor() {}\n\n  static getInstance(): TaskRegistry {\n    if (!TaskRegistry.instance) {\n      TaskRegistry.instance = new TaskRegistry();\n    }\n    return TaskRegistry.instance;\n  }\n\n  registerTask(definition: TaskDefinition): void {\n    this.tasks.set(definition.name, definition);\n  }\n\n  getTask(name: string): TaskDefinition | undefined {\n    return this.tasks.get(name);\n  }\n\n  getAllTasks(): TaskDefinition[] {\n    return Array.from(this.tasks.values());\n  }\n\n  getTasksByCapability(capability: string): TaskDefinition[] {\n    return this.getAllTasks().filter((task) =>\n      task.capabilities.includes(capability),\n    );\n  }\n\n  clear(): void {\n    this.tasks.clear();\n  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