import json class PromptGenerator: def __init__(self): self.constraints = [] self.commands = [] self.resources = [] self.performance_evaluation = [] self.response_format = { "thoughts": { "text": "thought", "reasoning": "reasoning", "plan": "- short bulleted\n- list that conveys\n- long-term plan", "criticism": "constructive self-criticism", "speak": "thoughts summary to say to user" }, "command": { "name": "command name", "args": { "arg name": "value" } } } def add_constraint(self, constraint): self.constraints.append(constraint) # {CommandLabel}: "{CommandName}", args: "{arg#Name}": "{arg#Prompt}" def add_command(self, command_label, command_name, args=None): if args is None: args = {} command_args = {arg_key: arg_value for arg_key, arg_value in args.items()} command = { "label": command_label, "name": command_name, "args": command_args, } self.commands.append(command) def _generate_command_string(self, command): args_string = ', '.join(f'"{key}": "{value}"' for key, value in command['args'].items()) return f'{command["label"]}: "{command["name"]}", args: {args_string}' def add_resource(self, resource): self.resources.append(resource) def add_performance_evaluation(self, evaluation): self.performance_evaluation.append(evaluation) def _generate_numbered_list(self, items, item_type='list'): if item_type == 'command': return "\n".join(f"{i+1}. {self._generate_command_string(item)}" for i, item in enumerate(items)) else: return "\n".join(f"{i+1}. {item}" for i, item in enumerate(items)) def generate_prompt_string(self): formatted_response_format = json.dumps(self.response_format, indent=4) prompt_string = ( f"Constraints:\n{self._generate_numbered_list(self.constraints)}\n\n" f"Commands:\n{self._generate_numbered_list(self.commands, item_type='command')}\n\n" f"Resources:\n{self._generate_numbered_list(self.resources)}\n\n" f"Performance Evaluation:\n{self._generate_numbered_list(self.performance_evaluation)}\n\n" f"You should only respond in JSON format as described below \nResponse Format: \n{formatted_response_format} \nEnsure the response can be parsed by Python json.loads" ) return prompt_string