problem_prompt.py

def generate_prompt_for_dict(problem_dict):
    prompt = ''
    prompt += 'Given an ' + str(problem_dict['dim']) + ' dimensional optimization problem with ' + problem_dict['obj_language'] + ' formulation:\n\n'
    if problem_dict['obj_language'] == 'Latex' or problem_dict['obj_language'] == 'latex':
        formula_latex = 'Minimize: '
        formula_latex += problem_dict['formula']
        if problem_dict['constraints'] != 'None':
            constraint = problem_dict["constraints"]
            constraint_formula = "\n" + r'\\\text{Subject to: }\\'
            if 'g' in constraint.keys():
                num_of_g_constraints = len(constraint['g'])
                for i in range(num_of_g_constraints):
                    constraint_formula += r'g_' + str(i) + r'(x) = '
                    constraint_formula += constraint['g'][i]
                    constraint_formula += r'\leq 0\\'
            if 'h' in constraint.keys():
                num_of_h_constraints = len(constraint['h'])
                for i in range(num_of_h_constraints):
                    constraint_formula += r'h_' + str(i) + r'(x) = '
                    constraint_formula += constraint['h'][i]
                    constraint_formula += r'= 0\\'
            formula_latex += constraint_formula
        prompt += formula_latex
    else:
        prompt += problem_dict['formula']

    # search_range = [-problem['search_range'], problem['search_range']]
    prompt += '\n\nGenerate a solver for it.\n'
    prompt += f'Note that the feasible domain is:{problem_dict["search_range"]}.\n\n'
    prompt += f'The problem should be solved within {problem_dict["FEs"]} function evaluations.\n'
    if  problem_dict['obj_language'] == 'Latex' or problem_dict['obj_language'] == 'latex':
        pass
    else:
        if problem_dict['constraints'] != 'None':
            prompt += 'The constraints for solutions:\n'
            prompt += f'{problem_dict["constraints"]}'
    return prompt