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swarms/round_robin_example.py

59 lines
1.4 KiB

from swarms import Agent, Anthropic
from swarms.structs.round_robin import RoundRobinSwarm
# Initialize the director agent
director = Agent(
agent_name="Director",
system_prompt="Directs the tasks for the workers",
llm=Anthropic(),
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=Anthropic(),
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=Anthropic(),
max_loops=1,
dashboard=False,
streaming_on=True,
verbose=True,
stopping_token="<DONE>",
state_save_file_type="json",
saved_state_path="worker2.json",
)
# Round Robin
round_table = RoundRobinSwarm(
agents=[director, worker1, worker2],
verbose=True,
max_loops=1,
callback=None,
)
# Run the task and get the results
task = "Create a format to express and communicate swarms of llms in a structured manner for youtube"
results = round_table.run(task)
print("Round Robin Results:", results)