""" Example demonstrating running agents with different tasks using uvloop. This example shows how to use run_agents_with_tasks_uvloop to execute different tasks across multiple agents concurrently. """ import os from swarms.structs.agent import Agent from swarms.structs.multi_agent_exec import ( run_agents_with_tasks_uvloop, ) def create_example_agents(num_agents: int = 3): """ Create example agents for demonstration. Args: num_agents: Number of agents to create Returns: List of Agent instances """ agents = [] for i in range(num_agents): agent = Agent( agent_name=f"Agent_{i+1}", system_prompt=f"You are Agent {i+1}, a helpful AI assistant.", model_name="gpt-4o-mini", # Using a lightweight model for examples max_loops=1, autosave=False, verbose=False, ) agents.append(agent) return agents def run_different_tasks_example(): """ Run agents with different tasks using uvloop. Returns: List of results from each agent """ # Check if API key is available if not os.getenv("OPENAI_API_KEY"): raise ValueError( "OPENAI_API_KEY environment variable must be set" ) agents = create_example_agents(3) tasks = [ "Explain what machine learning is in simple terms.", "Describe the benefits of cloud computing.", "What are the main challenges in natural language processing?", ] results = run_agents_with_tasks_uvloop(agents, tasks) return results if __name__ == "__main__": results = run_different_tasks_example() # Results can be processed further as needed