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47 lines
1.4 KiB
47 lines
1.4 KiB
from swarms import Agent
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from swarms.structs.spreadsheet_swarm import SpreadSheetSwarm
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# Example 1: Using pre-configured agents
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agents = [
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Agent(
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agent_name="Research-Agent",
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agent_description="Specialized in market research and analysis",
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model_name="claude-sonnet-4-20250514",
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dynamic_temperature_enabled=True,
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max_loops=1,
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streaming_on=False,
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),
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Agent(
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agent_name="Technical-Agent",
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agent_description="Expert in technical analysis and trading strategies",
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model_name="claude-sonnet-4-20250514",
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dynamic_temperature_enabled=True,
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max_loops=1,
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streaming_on=False,
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),
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Agent(
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agent_name="Risk-Agent",
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agent_description="Focused on risk assessment and portfolio management",
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model_name="claude-sonnet-4-20250514",
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dynamic_temperature_enabled=True,
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max_loops=1,
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streaming_on=False,
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),
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]
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# Initialize the SpreadSheetSwarm with agents
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swarm = SpreadSheetSwarm(
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name="Financial-Analysis-Swarm",
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description="A swarm of specialized financial analysis agents",
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agents=agents,
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max_loops=1,
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autosave=False,
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workspace_dir="./swarm_outputs",
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)
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# Run all agents with the same task
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task = "What are the top 3 energy stocks to invest in for 2024? Provide detailed analysis."
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result = swarm.run(task=task)
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print(result)
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