Task Management Example

This guide provides a professional, step-by-step walkthrough for creating, registering, and executing a custom task using the TaskManager and Task classes from the agenticaiframework package.
It is intended for developers who want to define reusable, modular units of work for their agents.

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Prerequisites & Configuration

• Installation: Ensure agenticaiframework is installed and accessible in your Python environment.
• No additional configuration is required for this example.
• Python Version: Compatible with Python 3.8+.

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Code

from agenticaiframework.tasks import TaskManager, Task

if __name__ == "__main__":
    task_manager = TaskManager()

    # Define a custom task
    class AdditionTask(Task):
        def run(self, a, b):
            result = a + b
            print(f"Task Result: {result}")
            return result

    # Create and register the task
    addition_task = AdditionTask(name="AdditionTask")
    task_manager.register_task(addition_task)

    # Execute the task
    addition_task.run(5, 7)

    # List registered tasks
    print("Registered Tasks:", [task.name for task in task_manager.tasks])

    # Retrieve a specific task
    retrieved_task = task_manager.get_task("AdditionTask")
    print("Retrieved Task:", retrieved_task.name)

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Step-by-Step Execution

1. Import Required Classes
   Import TaskManager and Task from agenticaiframework.tasks.

2. Instantiate the Task Manager
   Create an instance of TaskManager to handle task registration and execution.

3. Define a Custom Task
   Create a class inheriting from Task and implement the run method with the desired logic.

4. Create the Task Instance
   Instantiate your custom task with a unique name.

5. Register the Task
   Use register_task to add the task to the manager's registry.

6. Execute the Task
   Call the run method with the required arguments.

7. List Registered Tasks
   Access the tasks list to see all registered tasks.

8. Retrieve a Specific Task
   Use get_task to fetch a task by name.

Best Practice: Keep tasks focused on a single responsibility to make them easier to test and reuse.

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Expected Input

No user input is required; the script uses hardcoded values for demonstration purposes. In production, task parameters could be dynamically generated from user input, workflows, or other runtime data.

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Expected Output

[YYYY-MM-DD HH:MM:SS] [Task:AdditionTask] Running task 'AdditionTask'
[YYYY-MM-DD HH:MM:SS] [Task:AdditionTask] Task 'AdditionTask' completed successfully
Task Result: 12
[YYYY-MM-DD HH:MM:SS] [TaskManager] Registered task 'AdditionTask' with ID <UUID>
Registered Tasks: ['AdditionTask']
Retrieved Task: AdditionTask

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How to Run

Run the example from the project root:

python examples/tasks_example.py

If installed as a package, you can also run it from anywhere:

python -m examples.tasks_example

Tip: Combine TaskManager with AgentManager to assign and execute tasks dynamically within agents.