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from swarms import Agent
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from swarms.structs.matrix_swarm import MatrixSwarm
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from swarms.prompts.finance_agent_sys_prompt import FINANCIAL_AGENT_SYS_PROMPT
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def create_agent(name: str) -> Agent:
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"""Utility function to build a simple agent for the matrix."""
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return Agent(
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agent_name=name,
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system_prompt=FINANCIAL_AGENT_SYS_PROMPT,
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model_name="gpt-4o-mini",
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max_loops=1,
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streaming_on=False,
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verbose=True,
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)
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if __name__ == "__main__":
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# Initialize a 2x2 matrix of agents
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agents = [
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[create_agent(f"Agent-{i}-{j}") for j in range(2)]
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for i in range(2)
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]
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swarm = MatrixSwarm(agents)
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# Perform basic matrix operations
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transposed = swarm.transpose()
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added = swarm.add(transposed)
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# Show shapes after operations
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print("Original shape:", len(swarm.agents), len(swarm.agents[0]))
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print("Transposed shape:", len(transposed.agents), len(transposed.agents[0]))
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print("Added matrix shape:", len(added.agents), len(added.agents[0]))
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# Prepare queries for each row of the matrix
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queries = [
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"What are the benefits of index funds?",
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"How does compound interest work?",
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]
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# Run agents by multiplying the matrix with its transpose
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results = swarm.multiply(transposed, queries)
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# Display results
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for row in results:
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for output in row:
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print(f"{output.agent_name}: {output.output_result}")
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