Spaces:
Runtime error
Runtime error
File size: 2,964 Bytes
b3509ba |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 |
from swarmai.agents.AgentBase import AgentBase
from swarmai.utils.ai_engines import LanchainGoogleEngine, GPTConversEngine
from swarmai.utils.task_queue.Task import Task
from swarmai.utils.PromptFactory import PromptFactory
class GooglerAgent(AgentBase):
"""Googler agent that can google things.
"""
def __init__(self, agent_id, agent_type, swarm, logger):
super().__init__(agent_id, agent_type, swarm, logger)
self.search_engine = LanchainGoogleEngine("gpt-3.5-turbo", 0.5, 1000)
self.thinking_engine = GPTConversEngine("gpt-3.5-turbo", 0.5, 1000)
self.TASK_METHODS = {
Task.TaskTypes.google_search: self.google,
}
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(message = 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 google(self, task_description):
self.step = "google"
# just googling
system_prompt = PromptFactory.StandardPrompts.google_search_config_prompt
conversation = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": task_description},
]
result = self.search_engine.call_model(conversation)
# summarize and pretify the result
summarisation_prompt =(
f"After googling the topic {task_description}, you found the results listed below."
"Summarize the facts as brief as possible"
"You MUST provide the links as sources for each fact."
"Add tags in brackets to the facts to make them more searchable. For example: (Company X market trends), (Company X competitors), etc."
)
conversation = [
{"role": "system", "content": system_prompt},
{"role": "user", "content": summarisation_prompt + f"Search Results:\n{result}"},
]
result = self.thinking_engine.call_model(conversation)
self.log(message = f"Agent {self.agent_id} of type {self.agent_type} googled:\n{task_description}\n\nand got:\n{result}", level = "info")
# saving to the shared memory
self._send_data_to_swarm(result)
return result
|