import asyncio from swarms import Agent from swarms.prompts.finance_agent_sys_prompt import ( FINANCIAL_AGENT_SYS_PROMPT, ) from swarms.utils.visualizer import ( SwarmVisualizationRich, SwarmMetadata, ) # Replace with your actual module name # Create two example agents agent1 = Agent( agent_name="Financial-Analysis-Agent", system_prompt=FINANCIAL_AGENT_SYS_PROMPT, model_name="gpt-4o-mini", max_loops=1, autosave=True, dashboard=False, verbose=True, dynamic_temperature_enabled=True, saved_state_path="finance_agent.json", user_name="swarms_corp", retry_attempts=1, context_length=200000, return_step_meta=False, output_type="string", streaming_on=False, ) # Create a second dummy agent for demonstration agent2 = Agent( agent_name="Stock-Advisor-Agent", system_prompt="Provide stock market insights and investment advice.", model_name="gpt-4o-mini", max_loops=1, autosave=True, dashboard=False, verbose=True, dynamic_temperature_enabled=True, saved_state_path="stock_agent.json", user_name="swarms_corp", retry_attempts=1, context_length=200000, return_step_meta=False, output_type="string", streaming_on=False, ) # Create swarm metadata metadata = SwarmMetadata( name="Financial Swarm", description="A swarm of agents focused on financial analysis and stock market advice.", version="1.0", author="Your Name", primary_objective="Provide comprehensive financial and investment analysis.", ) # Instantiate the visualizer with a list of agents visualizer = SwarmVisualizationRich( swarm_metadata=metadata, agents=[agent1, agent2], update_resources=True, refresh_rate=0.1, ) # Start the visualization asyncio.run(visualizer.start())