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import os
from agents.reflexion_oneshot import Reflexion_Oneshot
from models.OpenAI import OpenAIModel
from dataloaders.TritonBench import TritonBench
from args_config import load_config
def main():
args = load_config("configs/tritonbench_oneshot_config.yaml")
# setup LLM model
model = OpenAIModel(api_key=args.api_key, model_id=args.model_id)
# setup dataset
result_path = None
dataset = TritonBench(statis_path=args.statis_path,
py_folder=args.py_folder,
instruction_path=args.instruction_path,
py_interpreter=args.py_interpreter,
golden_metrics=args.golden_metrics,
perf_ref_folder=args.perf_ref_folder,
perf_G_path=args.perf_G_path,
result_path=result_path)
# setup agent
agent = Reflexion_Oneshot(model=model, dataset=dataset, corpus_path=args.corpus_path)
# run the agent
agent.run(output_path=args.output_path, multi_thread=args.multi_thread, iteration_num=args.max_iteration, temperature=args.temperature, datalen=None)
if __name__ == "__main__":
main() |