Agent Management Example

This guide provides a professional, step-by-step walkthrough for creating, registering, and controlling an agent using the AgentManager and Agent classes from the agenticaiframework package.
It is intended for developers building intelligent systems that require autonomous or semi-autonomous 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.agents import AgentManager, Agent

if __name__ == "__main__":
    agent_manager = AgentManager()

    # Create and register an agent
    example_agent = Agent(name="ExampleAgent")
    agent_manager.register_agent(example_agent)

    # Control the agent
    example_agent.start()
    example_agent.pause()
    example_agent.resume()
    example_agent.stop()

    # List registered agents
    print("Registered Agents:", [agent.name for agent in agent_manager.agents])

    # Retrieve a specific agent
    retrieved_agent = agent_manager.get_agent("ExampleAgent")
    print("Retrieved Agent:", retrieved_agent.name)

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Step-by-Step Execution

1. Import Required Classes
   Import AgentManager and Agent from agenticaiframework.agents.

2. Instantiate the Agent Manager
   Create an instance of AgentManager to handle agent registration and lifecycle management.

3. Create an Agent
   Instantiate an Agent with a unique name.

4. Register the Agent
   Use register_agent to add the agent to the manager's registry.

5. Control the Agent
   Use start, pause, resume, and stop to manage the agent's lifecycle.

6. List Registered Agents
   Access the agents list to see all registered agents.

7. Retrieve a Specific Agent
   Use get_agent to fetch an agent by name.

Best Practice: Assign meaningful names to agents to make debugging and monitoring easier.

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Expected Input

No user input is required; the script uses hardcoded values for demonstration purposes. In production, agent names and behaviors could be dynamically configured based on application needs.

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Expected Output

[YYYY-MM-DD HH:MM:SS] [Agent:ExampleAgent] Agent ExampleAgent started.
[YYYY-MM-DD HH:MM:SS] [Agent:ExampleAgent] Agent ExampleAgent paused.
[YYYY-MM-DD HH:MM:SS] [Agent:ExampleAgent] Agent ExampleAgent resumed.
[YYYY-MM-DD HH:MM:SS] [Agent:ExampleAgent] Agent ExampleAgent stopped.
Registered Agents: ['ExampleAgent']
Retrieved Agent: ExampleAgent

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How to Run

Run the example from the project root:

python examples/agents_example.py

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

python -m examples.agents_example

Tip: Integrate AgentManager with monitoring and task management systems for full lifecycle control of agents in production environments.