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from swarmai.agents.AgentBase import AgentBase
from swarmai.utils.ai_engines.GPTConversEngine import GPTConversEngine
from swarmai.utils.task_queue.Task import Task
from swarmai.utils.PromptFactory import PromptFactory
class GeneralPurposeAgent(AgentBase):
"""Manager agent class that is responsible for breaking down the tasks into subtasks and assigning them into the task queue.
"""
def __init__(self, agent_id, agent_type, swarm, logger):
super().__init__(agent_id, agent_type, swarm, logger)
self.engine = GPTConversEngine("gpt-3.5-turbo", 0.5, 1000)
self.TASK_METHODS = {}
for method in self.swarm.TASK_TYPES:
if method != "breakdown_to_subtasks":
self.TASK_METHODS[method] = self._think
def perform_task(self):
self.step = "perform_task"
try:
# self.task is already taken in the beginning of the cycle in AgentBase
if not isinstance(self.task, Task):
raise Exception(f"Task is not of type Task, but {type(self.task)}")
task_type = self.task.task_type
if task_type not in self.TASK_METHODS:
raise Exception(f"Task type {task_type} is not supported by the agent {self.agent_id} of type {self.agent_type}")
self.result = self.TASK_METHODS[task_type](self.task.task_description)
return True
except Exception as e:
self.log(f"Agent {self.agent_id} of type {self.agent_type} failed to perform the task {self.task.task_description} with error {e}", level = "error")
return False
def share(self):
pass
def _think(self, task_description):
self.step = "think"
prompt = (
"Act as an analyst and worker."
f"You need to perform a task: {task_description}. The type of the task is {self.task.task_type}."
"If you don't have capabilities to perform the task (for example no google access), return empty string (or just a space)"
"Make sure to actually solve the task and provide a valid solution; avoid describing how you would do it."
)
# generate a conversation
conversation = [
{"role": "user", "content": prompt}
]
result = self.engine.call_model(conversation)
# add to shared memory
self._send_data_to_swarm(result)
self.log(f"Agent {self.agent_id} of type {self.agent_type} thought about the task:\n{task_description}\n\nand shared the following result:\n{result}", level = "info")
return result
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