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@ -3,24 +3,27 @@ from swarms.prompts.finance_agent_sys_prompt import (
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FINANCIAL_AGENT_SYS_PROMPT,
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)
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# Initialize the agent
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# Initialize the financial analysis agent with a system prompt and configuration.
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agent = Agent(
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agent_name="Financial-Analysis-Agent",
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agent_description="Personal finance advisor agent",
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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agent_name="Financial-Analysis-Agent", # Name of the agent
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agent_description="Personal finance advisor agent", # Description of the agent's role
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT, # System prompt for financial tasks
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max_loops=1,
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mcp_urls=[
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"http://0.0.0.0:8001/mcp",
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"http://0.0.0.0:8000/mcp",
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"http://0.0.0.0:8001/mcp", # URL for the OKX crypto price MCP server
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"http://0.0.0.0:8000/mcp", # URL for the agent creation MCP server
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],
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model_name="gpt-4o-mini",
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output_type="all",
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)
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# Create a markdown file with initial content
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# Run the agent with a specific instruction to use the create_agent tool.
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# The agent is asked to create a new agent specialized for accounting rules in crypto.
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out = agent.run(
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# Example alternative prompt:
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# "Use the get_okx_crypto_price to get the price of solana just put the name of the coin",
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"Use the create_agent tool that is specialized in creating agents"
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"Use the create_agent tool that is specialized in creating agents and create an agent speecialized for accounting rules in crypto"
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)
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# Print the output from the agent's run method.
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print(out)
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