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from prompts import(
select_prompt,
reasoning_modules,
adapt_prompt,
implement_prompt
)
from llm import LLM
from task_example import task1
import logging
def setup_logging():
logger = logging.getLogger("__name__")
logger.setLevel(logging.INFO)
handler = logging.FileHandler("prompt_log.txt")
handler.setLevel(logging.INFO)
formatter = logging.Formatter('%(levelname)s - %(message)s')
handler.setFormatter(formatter)
logger.addHandler(handler)
return logger
logger = setup_logging()
class SelfDiscover:
def __init__(self, task) -> None:
self.llm = LLM(model_name="OpenAI")
self.actions = ["SELECT", "ADAPT", "IMPLEMENT"]
self.task = task
def __call__(self):
for action in self.actions:
print(action)
if action == "SELECT":
prompt = select_prompt.replace("{Task}",self.task)
prompt = prompt.replace("{resonining_modules}", reasoning_modules)
logger.info("SELECT PROMPT :" + prompt)
self.selected_modules = self.llm(prompt)
print(self.selected_modules)
elif action == "ADAPT":
prompt = adapt_prompt.replace("{Task}",self.task)
prompt = prompt.replace("{selected_modules}",self.selected_modules)
logger.info("ADAPT PROMPT :" + prompt)
self.adapted_modules = self.llm(prompt)
elif action == "IMPLEMENT":
prompt = implement_prompt.replace("{Task}",self.task)
prompt = prompt.replace("{adapted_modules}", self.adapted_modules)
logger.info("IMPLEMENT PROMPT:" + prompt)
self.reasoning_structure = self.llm(prompt)
if __name__=="__main__":
result = SelfDiscover(task=task1)
result()
logger.info(f"SELECTED_MODULES : {result.selected_modules}")
logger.info(f"ADAPTED_MODULES : {result.adapted_modules}")
logger.info(f"REASONING_STRUCTURE : {result.reasoning_structure}") |