AI Planning

The plan function in ControlFlow extends the capabilities of AI workflows by allowing dynamic generation of tasks. This feature allows you to leverage AI for creating structured, goal-oriented task sequences programmatically.

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Purpose of AI planning

While ControlFlow allows manual creation of tasks for AI workflows, there are scenarios where automatically generating tasks can be beneficial:

1. Dynamic Task Generation: When the specific steps to achieve a goal aren’t known in advance.
2. Complex Problem Decomposition: For objectives that require breaking down into subtasks based on context or intermediate results.
3. Adaptive Workflows: In processes that need to adjust based on changing conditions or new information.

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The plan function

The plan function takes a high-level objective and generates a structured sequence of tasks to achieve that goal. Here’s a basic example:

import controlflow as cf

tasks = cf.plan(
    objective="Analyze customer feedback data",
    n_tasks=3  # Optionally specify the number of tasks
)

# Execute the generated plan
cf.run_tasks(tasks)

In this example, plan will generate a list of 3 tasks that, when completed, should result in an analysis of customer feedback data. These tasks might include steps like “Load data”, “Preprocess text”, “Perform sentiment analysis”, etc.

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Dependencies

If appropriate, plan can generate tasks that depend on each other or have parent/child relationships. You can influence this behavior by providing instructions.

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Agents and tools

You can pass a list of agents or tools to the plan function. It will take these into account when generating tasks and assign agents or tools to tasks as needed.