Nicolas Nahas
9 months ago
parent
0e7dc3557a
commit
b2f8721f85
@ -1,26 +1,91 @@
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from swarms import Agent, OpenAIChat
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"""
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* WORKING
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What this script does:
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Simple agent run to test AgentOps (https://www.agentops.ai/)
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Requirements:
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1. Create an account on https://www.agentops.ai/ and run pip install agentops
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2. Add the folowing API key(s) in your .env file:
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- OPENAI_API_KEY
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- AGENTOPS_API_KEY
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3. Go to your agentops dashboard to observe your activity
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"""
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################ Adding project root to PYTHONPATH ################################
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# If you are running playground examples in the project files directly, use this:
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import sys
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import os
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sys.path.insert(0, os.getcwd())
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################ Adding project root to PYTHONPATH ################################
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from swarms import Agent, OpenAIChat, AgentRearrange
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import agentops
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# Initialize agentops
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agentops.start_session()
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# Initialize the agent
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agent = Agent(
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agent_name="Accounting Agent",
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system_prompt="Generate a financial report for the company's quarterly earnings.",
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agent_name="Treasurer",
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system_prompt="Give your opinion on the cash management.",
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agent_description=(
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"Generate a financial report for the company's quarterly earnings."
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"responsible for managing an organization's financial assets and liquidity. They oversee cash management, "
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"investment strategies, and financial risk. Key duties include monitoring cash flow, managing bank relationships, "
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"ensuring sufficient funds for operations, and optimizing returns on short-term investments. Treasurers also often "
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"handle debt management and may be involved in capital raising activities."
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),
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llm=OpenAIChat(),
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max_loops=1,
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autosave=True,
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dashboard=False,
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streaming_on=True,
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verbose=True,
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stopping_token="<DONE>",
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interactive=False,
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state_save_file_type="json",
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saved_state_path="accounting_agent.json",
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agent_ops_on=True,
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)
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# Run the Agent on a task
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agent.run(
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"Generate a financial report for the company's quarterly earnings!"
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agent2 = Agent(
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agent_name="CFO",
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system_prompt="Give your opinion on the financial performance of the company.",
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agent_description=(
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"the top financial executive in an organization, overseeing all financial operations and strategy. Their role is broader than a treasurer's and includes:\n"
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"Financial planning and analysis\n"
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"Accounting and financial reporting\n"
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"Budgeting and forecasting\n"
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"Strategic financial decision-making\n"
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"Compliance and risk management\n"
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"Investor relations (in public companies)\n"
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"Overseeing the finance and accounting departments"
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),
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llm=OpenAIChat(),
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max_loops=1,
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streaming_on=True,
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verbose=True,
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)
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swarm = AgentRearrange(
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agents=[agent, agent2],
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flow="Treasurer -> CFO",
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)
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results = swarm.run("Date,Revenue,Expenses,Profit,Cash_Flow,Inventory,Customer_Acquisition_Cost,Customer_Retention_Rate,Marketing_Spend,R&D_Spend,Debt,Assets\n"
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"2023-01-01,1000000,800000,200000,150000,500000,100,0.85,50000,100000,2000000,5000000\n"
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"2023-02-01,1050000,820000,230000,180000,520000,95,0.87,55000,110000,1950000,5100000\n"
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"2023-03-01,1100000,850000,250000,200000,530000,90,0.88,60000,120000,1900000,5200000\n"
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"2023-04-01,1200000,900000,300000,250000,550000,85,0.90,70000,130000,1850000,5400000\n"
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"2023-05-01,1300000,950000,350000,300000,580000,80,0.92,80000,140000,1800000,5600000\n"
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"2023-06-01,1400000,1000000,400000,350000,600000,75,0.93,90000,150000,1750000,5800000\n"
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"2023-07-01,1450000,1050000,400000,320000,620000,78,0.91,95000,160000,1700000,5900000\n"
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"2023-08-01,1500000,1100000,400000,300000,650000,80,0.90,100000,170000,1650000,6000000\n"
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"2023-09-01,1550000,1150000,400000,280000,680000,82,0.89,105000,180000,1600000,6100000\n"
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"2023-10-01,1600000,1200000,400000,260000,700000,85,0.88,110000,190000,1550000,6200000\n"
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"2023-11-01,1650000,1250000,400000,240000,720000,88,0.87,115000,200000,1500000,6300000\n"
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"2023-12-01,1700000,1300000,400000,220000,750000,90,0.86,120000,210000,1450000,6400000\n"
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"2024-01-01,1500000,1200000,300000,180000,780000,95,0.84,100000,180000,1500000,6300000\n"
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"2024-02-01,1550000,1220000,330000,200000,760000,92,0.85,105000,185000,1480000,6350000\n"
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"2024-03-01,1600000,1240000,360000,220000,740000,89,0.86,110000,190000,1460000,6400000\n"
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"2024-04-01,1650000,1260000,390000,240000,720000,86,0.87,115000,195000,1440000,6450000\n"
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"2024-05-01,1700000,1280000,420000,260000,700000,83,0.88,120000,200000,1420000,6500000\n"
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"2024-06-01,1750000,1300000,450000,280000,680000,80,0.89,125000,205000,1400000,6550000"
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)
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@ -1,28 +0,0 @@
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from swarms.utils.loguru_logger import logger
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import os
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from dotenv import load_dotenv
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def try_import_agentops(*args, **kwargs):
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try:
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load_dotenv()
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logger.info("Trying to import agentops")
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import agentops
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agentops.init(os.getenv("AGENTOPS_API_KEY"), *args, **kwargs)
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return "agentops imported successfully."
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except ImportError:
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logger.error("Could not import agentops")
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def end_session_agentops():
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try:
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logger.info("Trying to end session")
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import agentops
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agentops.end_session("Success")
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return "Session ended successfully."
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except ImportError:
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logger.error("Could not import agentops")
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return "Could not end session."
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