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45 lines
1.3 KiB
45 lines
1.3 KiB
from swarms import Agent
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from swarms.prompts.finance_agent_sys_prompt import (
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FINANCIAL_AGENT_SYS_PROMPT,
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)
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from swarm_models import OpenAIChat
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model = OpenAIChat(model_name="gpt-4o")
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# Initialize the agent
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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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+ "Output the <DONE> token when you're done creating a portfolio of etfs, index, funds, and more for AI",
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max_loops=1,
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llm=model,
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dynamic_temperature_enabled=True,
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user_name="Kye",
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retry_attempts=3,
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# streaming_on=True,
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context_length=8192,
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return_step_meta=False,
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output_type="str", # "json", "dict", "csv" OR "string" "yaml" and
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auto_generate_prompt=False, # Auto generate prompt for the agent based on name, description, and system prompt, task
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max_tokens=4000, # max output tokens
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# interactive=True,
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stopping_token="<DONE>",
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saved_state_path="agent_00.json",
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interactive=False,
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)
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async def run_agent():
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await agent.arun(
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"Create a table of super high growth opportunities for AI. I have $40k to invest in ETFs, index funds, and more. Please create a table in markdown.",
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all_cores=True,
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)
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if __name__ == "__main__":
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import asyncio
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asyncio.run(run_agent())
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