from colorama import Fore, Style from autogpt.app import execute_command, get_command from autogpt.chat import chat_with_ai, create_chat_message from autogpt.config import Config from autogpt.json_utils.json_fix_llm import fix_json_using_multiple_techniques from autogpt.json_utils.utilities import validate_json from autogpt.logs import logger, print_assistant_thoughts from autogpt.speech import say_text from autogpt.spinner import Spinner from autogpt.utils import clean_input from autogpt.workspace import Workspace class Agent: """Agent class for interacting with Auto-GPT. Attributes: ai_name: The name of the agent. memory: The memory object to use. full_message_history: The full message history. next_action_count: The number of actions to execute. system_prompt: The system prompt is the initial prompt that defines everything the AI needs to know to achieve its task successfully. Currently, the dynamic and customizable information in the system prompt are ai_name, description and goals. triggering_prompt: The last sentence the AI will see before answering. For Auto-GPT, this prompt is: Determine which next command to use, and respond using the format specified above: The triggering prompt is not part of the system prompt because between the system prompt and the triggering prompt we have contextual information that can distract the AI and make it forget that its goal is to find the next task to achieve. SYSTEM PROMPT CONTEXTUAL INFORMATION (memory, previous conversations, anything relevant) TRIGGERING PROMPT The triggering prompt reminds the AI about its short term meta task (defining the next task) """ def __init__( self, ai_name, memory, full_message_history, next_action_count, command_registry, config, system_prompt, triggering_prompt, workspace_directory, ): self.cfg = Config() self.ai_name = ai_name self.memory = memory self.full_message_history = full_message_history self.next_action_count = next_action_count self.command_registry = command_registry self.config = config self.system_prompt = system_prompt self.triggering_prompt = triggering_prompt self.workspace = Workspace(workspace_directory, self.cfg.restrict_to_workspace) self.loop_count = 0 self.command_name = None self.sarguments = None self.user_input = "" self.cfg = Config() def start_interaction_loop(self): # Discontinue if continuous limit is reached self.loop_count += 1 if ( self.cfg.continuous_mode and self.cfg.continuous_limit > 0 and self.loop_count > self.cfg.continuous_limit ): logger.typewriter_log( "Continuous Limit Reached: ", Fore.YELLOW, f"{self.cfg.continuous_limit}" ) # break # Send message to AI, get response with Spinner("Thinking... "): self.assistant_reply = chat_with_ai( self, self.system_prompt, self.triggering_prompt, self.full_message_history, self.memory, self.cfg.fast_token_limit, ) # TODO: This hardcodes the model to use GPT3.5. Make this an argument self.assistant_reply_json = fix_json_using_multiple_techniques(self.assistant_reply) for plugin in self.cfg.plugins: if not plugin.can_handle_post_planning(): continue self.assistant_reply_json = plugin.post_planning(self, self.assistant_reply_json) # Print Assistant thoughts if self.assistant_reply_json != {}: validate_json(self.assistant_reply_json, "llm_response_format_1") # Get command name and self.arguments try: print_assistant_thoughts(self.ai_name, self.assistant_reply_json) self.command_name, self.arguments = get_command(self.assistant_reply_json) if self.cfg.speak_mode: say_text(f"I want to execute {self.command_name}") self.arguments = self._resolve_pathlike_command_args(self.arguments) except Exception as e: logger.error("Error: \n", str(e)) if not self.cfg.continuous_mode and self.next_action_count == 0: # ### GET USER AUTHORIZATION TO EXECUTE COMMAND ### # Get key press: Prompt the user to press enter to continue or escape # to exit logger.typewriter_log( "NEXT ACTION: ", Fore.CYAN, f"COMMAND = {self.command_name}" f"ARGUMENTS = {self.arguments}", ) logger.typewriter_log( "", "", "Enter 'y' to authorise command, 'y -N' to run N continuous " "commands, 'n' to exit program, or enter feedback for " f"{self.ai_name}...", ) def start_interaction_next(self, cookie, chatbot, history, msg, _input, obj): console_input = _input if console_input.lower().strip() == "y": self.user_input = "GENERATE NEXT COMMAND JSON" elif console_input.lower().strip() == "": print("Invalid input format.") return elif console_input.lower().startswith("y -"): try: self.next_action_count = abs( int(console_input.split(" ")[1]) ) self.user_input = "GENERATE NEXT COMMAND JSON" except ValueError: print( "Invalid input format. Please enter 'y -n' where n is" " the number of continuous tasks." ) return elif console_input.lower() == "n": self.user_input = "EXIT" return else: self.user_input = console_input self.command_name = "human_feedback" return if self.user_input == "GENERATE NEXT COMMAND JSON": logger.typewriter_log( "-=-=-=-=-=-=-= COMMAND AUTHORISED BY USER -=-=-=-=-=-=-=", Fore.MAGENTA, "", ) elif self.user_input == "EXIT": print("Exiting...", flush=True) # break 这里需要注意 else: # Print command logger.typewriter_log( "NEXT ACTION: ", Fore.CYAN, f"COMMAND = {Fore.CYAN}{self.command_name}{Style.RESET_ALL}" f" ARGUMENTS = {Fore.CYAN}{self.arguments}{Style.RESET_ALL}", ) # Execute command if self.command_name is not None and self.command_name.lower().startswith("error"): result = ( f"Command {self.command_name} threw the following error: {self.arguments}" ) elif self.command_name == "human_feedback": result = f"Human feedback: {self.user_input}" else: for plugin in self.cfg.plugins: if not plugin.can_handle_pre_command(): continue self.command_name, self.arguments = plugin.pre_command( self.command_name, self.arguments ) command_result = execute_command( self.command_registry, self.command_name, self.arguments, self.config.prompt_generator, ) result = f"Command {self.command_name} returned: " f"{command_result}" for plugin in self.cfg.plugins: if not plugin.can_handle_post_command(): continue result = plugin.post_command(self.command_name, result) if self.next_action_count > 0: self.next_action_count -= 1 if self.command_name != "do_nothing": memory_to_add = ( f"Assistant Reply: {self.assistant_reply} " f"\nResult: {result} " f"\nHuman Feedback: {self.user_input} " ) self.memory.add(memory_to_add) # Check if there's a result from the command append it to the message # history if result is not None: self.full_message_history.append( create_chat_message("system", result) ) logger.typewriter_log("SYSTEM: ", Fore.YELLOW, result) else: self.full_message_history.append( create_chat_message("system", "Unable to execute command") ) logger.typewriter_log( "SYSTEM: ", Fore.YELLOW, "Unable to execute command" ) def _resolve_pathlike_command_args(self, command_args): if "directory" in command_args and command_args["directory"] in {"", "/"}: command_args["directory"] = str(self.workspace.root) else: for pathlike in ["filename", "directory", "clone_path"]: if pathlike in command_args: command_args[pathlike] = str( self.workspace.get_path(command_args[pathlike]) ) return command_args