Dependent Tasks

In this example, we’ll explore how ControlFlow enables the creation of complex, hierarchical workflows using dependent tasks. We’ve chosen a text analysis scenario to demonstrate several powerful features of ControlFlow:

• Organizing tasks in a logical, nested structure
• Simplifying data flow through automatic context sharing
• Ensuring correct task execution order with dependencies
• Maintaining a shared context across all tasks in a workflow

As you examine the code, pay attention to how these concepts are implemented and how they contribute to creating a clear, efficient workflow structure.

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Code

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Key points

1. Task hierarchy: The parent task encompasses the entire analysis process, with child tasks handling specific aspects. This structure allows for logical organization of complex workflows.
2. Automatic context sharing: Child tasks have access to their parent’s context without explicit passing, streamlining data flow within the workflow.
3. Dependencies: The depends_on parameter ensures tasks are executed in the correct order, as demonstrated by the summary task depending on the key terms task.
4. Flow context: By wrapping tasks in a flow, ControlFlow maintains a shared context across all tasks, including visibility into prior executions and conversation history.
5. Unified execution: Running the parent task automatically executes all child tasks in the correct order, simplifying workflow management.

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Further reading

• For more details on creating tasks and context sharing, see the task documentation.
• To learn more about defining dependencies between tasks, check out the dependencies guide.
• For information on how ControlFlow manages task execution and context, refer to the running tasks guide.

By leveraging these features, you can create complex workflows that maintain a clear structure and ensure efficient information flow between tasks. This approach helps in building more maintainable and scalable AI-powered applications with minimal boilerplate code.