from .base_agent import BaseAgent from prompt.template import PROBLEM_MODELING_PROMPT, PROBLEM_MODELING_CRITIQUE_PROMPT, PROBLEM_MODELING_IMPROVEMENT_PROMPT # from prompt.constants import modeling_methods class ProblemModeling(BaseAgent): def __init__(self, llm): super().__init__(llm) def modeling_actor(self, modeling_problem: str, problem_analysis: str, modeling_methods: str, user_prompt: str=''): prompt = PROBLEM_MODELING_PROMPT.format(modeling_methods=modeling_methods, modeling_problem=modeling_problem, problem_analysis=problem_analysis, user_prompt=user_prompt).strip() return self.llm.generate(prompt) def modeling_critic(self, modeling_problem: str, problem_analysis: str, modeling_solution: str): prompt = PROBLEM_MODELING_CRITIQUE_PROMPT.format(modeling_problem=modeling_problem, problem_analysis=problem_analysis, modeling_solution=modeling_solution).strip() return self.llm.generate(prompt) def modeling_improvement(self, modeling_problem: str, problem_analysis: str, modeling_solution: str, modeling_solution_critique: str, user_prompt: str=''): prompt = PROBLEM_MODELING_IMPROVEMENT_PROMPT.format(modeling_problem=modeling_problem, problem_analysis=problem_analysis, modeling_solution=modeling_solution, modeling_solution_critique=modeling_solution_critique, user_prompt=user_prompt).strip() return self.llm.generate(prompt) def modeling(self, modeling_problem: str, problem_analysis: str, modeling_methods: str, round: int = 3, user_prompt: str = ''): modeling_solution = self.modeling_actor(modeling_problem, problem_analysis, modeling_methods, user_prompt) for i in range(round): print(f'Problem Modeling Round {i+1}') modeling_solution_critique = self.modeling_critic(modeling_problem, problem_analysis, modeling_solution) modeling_solution_improvement = self.modeling_improvement(modeling_problem, problem_analysis, modeling_solution, modeling_solution_critique, user_prompt) modeling_solution = modeling_solution_improvement return modeling_solution