You can not select more than 25 topics
Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
49 lines
1.8 KiB
49 lines
1.8 KiB
from swarms import Agent
|
|
from swarms.structs.hiearchical_swarm import HierarchicalSwarm
|
|
|
|
|
|
# Initialize agents for a $50B portfolio analysis
|
|
agents = [
|
|
Agent(
|
|
agent_name="Sector-Financial-Analyst",
|
|
agent_description="Senior financial analyst at BlackRock.",
|
|
system_prompt="You are a financial analyst tasked with optimizing asset allocations for a $50B portfolio. Provide clear, quantitative recommendations for each sector.",
|
|
max_loops=1,
|
|
model_name="groq/deepseek-r1-distill-qwen-32b",
|
|
max_tokens=3000,
|
|
),
|
|
Agent(
|
|
agent_name="Sector-Risk-Analyst",
|
|
agent_description="Expert risk management analyst.",
|
|
system_prompt="You are a risk analyst responsible for advising on risk allocation within a $50B portfolio. Provide detailed insights on risk exposures for each sector.",
|
|
max_loops=1,
|
|
model_name="groq/deepseek-r1-distill-qwen-32b",
|
|
max_tokens=3000,
|
|
),
|
|
Agent(
|
|
agent_name="Tech-Sector-Analyst",
|
|
agent_description="Technology sector analyst.",
|
|
system_prompt="You are a tech sector analyst focused on capital and risk allocations. Provide data-backed insights for the tech sector.",
|
|
max_loops=1,
|
|
model_name="groq/deepseek-r1-distill-qwen-32b",
|
|
max_tokens=3000,
|
|
),
|
|
]
|
|
|
|
# Create hierarchical swarm system
|
|
majority_voting = HierarchicalSwarm(
|
|
name="Sector-Investment-Advisory-System",
|
|
description="System for sector analysis and optimal allocations.",
|
|
agents=agents,
|
|
# director=director_agent,
|
|
max_loops=1,
|
|
output_type="dict",
|
|
)
|
|
|
|
# Run the analysis
|
|
result = majority_voting.run(
|
|
task="Evaluate market sectors and determine optimal allocation for a $50B portfolio. Include a detailed table of allocations, risk assessments, and a consolidated strategy."
|
|
)
|
|
|
|
print(result)
|