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66 lines
2.0 KiB
66 lines
2.0 KiB
from typing import List, Callable
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from swarms import Worker
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class MultiAgentDebate:
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def __init__(
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self,
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agents: List[Worker],
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selection_func: Callable[[int, List[Worker]], int]
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):
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self.agents = agents
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self.selection_func = selection_func
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def reset_agents(self):
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for agent in self.agents:
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agent.reset()
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def inject_agent(self, agent: Worker):
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self.agents.append(agent)
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def run(self, task: str, max_iters: int = None):
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self.reset_agents()
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results = []
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for i in range(max_iters or len(self.agents)):
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speaker_idx = self.selection_func(i, self.agents)
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speaker = self.agents[speaker_idx]
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response = speaker.run(task)
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results.append({
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'agent': speaker.ai_name,
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'response': response
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})
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return results
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def update_task(self, task: str):
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self.task = task
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def format_results(self, results):
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formatted_results = "\n".join([f"Agent {result['agent']} responded: {result['response']}" for result in results])
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return formatted_results
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# Define a selection function
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def select_speaker(step: int, agents: List[Worker]) -> int:
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# This function selects the speaker in a round-robin fashion
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return step % len(agents)
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# Initialize agents
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worker1 = Worker(openai_api_key="", ai_name="Optimus Prime")
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worker2 = Worker(openai_api_key="", ai_name="Bumblebee")
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worker3 = Worker(openai_api_key="", ai_name="Megatron")
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agents = [
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worker1,
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worker2,
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worker3
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]
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# Initialize multi-agent debate with the selection function
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debate = MultiAgentDebate(agents, select_speaker)
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# Run task
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task = "What were the winning boston marathon times for the past 5 years (ending in 2022)? Generate a table of the year, name, country of origin, and times."
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results = debate.run(task, max_iters=4)
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# Print results
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for result in results:
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print(f"Agent {result['agent']} responded: {result['response']}") |