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import argparse |
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from metagpt.ext.spo.components.optimizer import PromptOptimizer |
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from metagpt.ext.spo.utils.llm_client import SPO_LLM |
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def parse_args(): |
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parser = argparse.ArgumentParser(description="SPO PromptOptimizer CLI") |
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parser.add_argument("--opt-model", type=str, default="claude-3-5-sonnet-20240620", help="Model for optimization") |
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parser.add_argument("--opt-temp", type=float, default=0.7, help="Temperature for optimization") |
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parser.add_argument("--eval-model", type=str, default="gpt-4o-mini", help="Model for evaluation") |
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parser.add_argument("--eval-temp", type=float, default=0.3, help="Temperature for evaluation") |
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parser.add_argument("--exec-model", type=str, default="gpt-4o-mini", help="Model for execution") |
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parser.add_argument("--exec-temp", type=float, default=0, help="Temperature for execution") |
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parser.add_argument("--workspace", type=str, default="workspace", help="Path for optimized output") |
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parser.add_argument("--initial-round", type=int, default=1, help="Initial round number") |
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parser.add_argument("--max-rounds", type=int, default=10, help="Maximum number of rounds") |
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parser.add_argument("--template", type=str, default="Poem.yaml", help="Template file name") |
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parser.add_argument("--name", type=str, default="Poem", help="Project name") |
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return parser.parse_args() |
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def main(): |
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args = parse_args() |
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SPO_LLM.initialize( |
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optimize_kwargs={"model": args.opt_model, "temperature": args.opt_temp}, |
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evaluate_kwargs={"model": args.eval_model, "temperature": args.eval_temp}, |
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execute_kwargs={"model": args.exec_model, "temperature": args.exec_temp}, |
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) |
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optimizer = PromptOptimizer( |
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optimized_path=args.workspace, |
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initial_round=args.initial_round, |
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max_rounds=args.max_rounds, |
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template=args.template, |
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name=args.name, |
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) |
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optimizer.optimize() |
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if __name__ == "__main__": |
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main() |
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