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())