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swarms/agent_with_new_agents.py

53 lines
1.8 KiB

from swarms import Agent
from swarm_models import OpenAIChat
from swarms_memory import ChromaDB
import os
# Initialize memory for agents
memory_risk = ChromaDB(metric="cosine", output_dir="risk_analysis_results")
memory_sustainability = ChromaDB(metric="cosine", output_dir="sustainability_results")
# Initialize model
model = OpenAIChat(api_key=os.getenv("OPENAI_API_KEY"), model_name="gpt-4o-mini", temperature=0.1)
# Initialize Risk Analysis Agent
risk_analysis_agent = Agent(
agent_name="Delaware-C-Corp-Risk-Analysis-Agent",
system_prompt="You are a specialized risk analysis agent focused on assessing risks.",
agent_description="Performs risk analysis for Delaware C Corps.",
llm=model,
max_loops=3,
autosave=True,
dashboard=False,
verbose=True,
dynamic_temperature_enabled=True,
saved_state_path="delaware_c_corp_risk_analysis_agent.json",
user_name="risk_analyst_user",
retry_attempts=2,
context_length=200000,
long_term_memory=memory_risk,
)
# Initialize Sustainability Agent
sustainability_agent = Agent(
agent_name="Delaware-C-Corp-Sustainability-Agent",
system_prompt="You are a sustainability analysis agent focused on ESG factors.",
agent_description="Analyzes sustainability practices for Delaware C Corps.",
llm=model,
max_loops=2,
autosave=True,
dashboard=False,
verbose=True,
dynamic_temperature_enabled=False,
saved_state_path="delaware_c_corp_sustainability_agent.json",
user_name="sustainability_specialist",
retry_attempts=3,
context_length=180000,
long_term_memory=memory_sustainability,
)
# Run the agents
risk_analysis_agent.run("What are the top financial and operational risks for a Delaware C Corp in healthcare?")
sustainability_agent.run("How can a Delaware C Corp in manufacturing improve its sustainability practices?")