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swarms/playground/structs/multi_agent_collaboration/agent_rearrange.py

73 lines
1.6 KiB

from swarms import Agent, AgentRearrange, OpenAIChat
# Initialize the director agent
director = Agent(
agent_name="Director",
system_prompt="Directs the tasks for the workers",
llm=OpenAIChat(),
max_loops=1,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
state_save_file_type="json",
saved_state_path="director.json",
)
# Initialize worker 1
worker1 = Agent(
agent_name="Worker1",
system_prompt="Generates a transcript for a youtube video on what swarms are",
llm=OpenAIChat(),
max_loops=1,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
state_save_file_type="json",
saved_state_path="worker1.json",
)
# Initialize worker 2
worker2 = Agent(
agent_name="Worker2",
system_prompt="Summarizes the transcript generated by Worker1",
llm=OpenAIChat(),
max_loops=1,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
state_save_file_type="json",
saved_state_path="worker2.json",
)
# Create a list of agents
agents = [director, worker1, worker2]
# Define the flow pattern
flow = "Director -> Worker1 -> Worker2"
# Using AgentRearrange class
agent_system = AgentRearrange(agents=agents, flow=flow)
output = agent_system.run(
"Create a format to express and communicate swarms of llms in a structured manner for youtube"
)
print(output)
# # Using rearrange function
# output = rearrange(
# agents,
# flow,
# "Create a format to express and communicate swarms of llms in a structured manner for youtube",
# )
# print(output)