from colorama import Fore from autogpt.api_manager import ApiManager from autogpt.config.ai_config import AIConfig from autogpt.config.config import Config from autogpt.logs import logger from autogpt.prompts.generator import PromptGenerator from autogpt.setup import prompt_user from autogpt.utils import clean_input CFG = Config() def build_default_prompt_generator() -> PromptGenerator: """ This function generates a prompt string that includes various constraints, commands, resources, and performance evaluations. Returns: str: The generated prompt string. """ # Initialize the PromptGenerator object prompt_generator = PromptGenerator() # Add constraints to the PromptGenerator object prompt_generator.add_constraint( "~4000 word limit for short term memory. Your short term memory is short, so" " immediately save important information to files." ) prompt_generator.add_constraint( "If you are unsure how you previously did something or want to recall past" " events, thinking about similar events will help you remember." ) prompt_generator.add_constraint("No user assistance") prompt_generator.add_constraint( 'Exclusively use the commands listed in double quotes e.g. "command name"' ) # Define the command list commands = [ ("Task Complete (Shutdown)", "task_complete", {"reason": ""}), ] # Add commands to the PromptGenerator object for command_label, command_name, args in commands: prompt_generator.add_command(command_label, command_name, args) # Add resources to the PromptGenerator object prompt_generator.add_resource( "Internet access for searches and information gathering." ) prompt_generator.add_resource("Long Term memory management.") prompt_generator.add_resource( "GPT-3.5 powered Agents for delegation of simple tasks." ) prompt_generator.add_resource("File output.") # Add performance evaluations to the PromptGenerator object prompt_generator.add_performance_evaluation( "Continuously review and analyze your actions to ensure you are performing to" " the best of your abilities." ) prompt_generator.add_performance_evaluation( "Constructively self-criticize your big-picture behavior constantly." ) prompt_generator.add_performance_evaluation( "Reflect on past decisions and strategies to refine your approach." ) prompt_generator.add_performance_evaluation( "Every command has a cost, so be smart and efficient. Aim to complete tasks in" " the least number of steps." ) prompt_generator.add_performance_evaluation( "If you cannot think of a valid command to perform start or message an agent to determine the next command." ) prompt_generator.add_performance_evaluation("Write all code to a file.") return prompt_generator def construct_main_ai_config() -> AIConfig: """Construct the prompt for the AI to respond to Returns: str: The prompt string """ config = AIConfig.load(CFG.ai_settings_file) if CFG.skip_reprompt and config.ai_name: logger.typewriter_log("Name :", Fore.GREEN, config.ai_name) logger.typewriter_log("Role :", Fore.GREEN, config.ai_role) logger.typewriter_log("Goals:", Fore.GREEN, f"{config.ai_goals}") logger.typewriter_log( "API Budget:", Fore.GREEN, "infinite" if config.api_budget <= 0 else f"${config.api_budget}", ) elif config.ai_name: logger.typewriter_log( "Welcome back! ", Fore.GREEN, f"Would you like me to return to being {config.ai_name}?", speak_text=True, ) should_continue = clean_input( f"""Continue with the last settings? Name: {config.ai_name} Role: {config.ai_role} Goals: {config.ai_goals} API Budget: {"infinite" if config.api_budget <= 0 else f"${config.api_budget}"} Continue (y/n): """ ) if should_continue.lower() == "n": config = AIConfig() if not config.ai_name: config = prompt_user() config.save(CFG.ai_settings_file) # set the total api budget api_manager = ApiManager() api_manager.set_total_budget(config.api_budget) # Agent Created, print message logger.typewriter_log( config.ai_name, Fore.LIGHTBLUE_EX, "has been created with the following details:", speak_text=True, ) # Print the ai config details # Name logger.typewriter_log("Name:", Fore.GREEN, config.ai_name, speak_text=False) # Role logger.typewriter_log("Role:", Fore.GREEN, config.ai_role, speak_text=False) # Goals logger.typewriter_log("Goals:", Fore.GREEN, "", speak_text=False) for goal in config.ai_goals: logger.typewriter_log("-", Fore.GREEN, goal, speak_text=False) return config