# aiso shell like bash for linux import asyncio import sys import os import logging import re import toml import shlex from logging.handlers import RotatingFileHandler from typing import Any, Optional, TypeVar, Tuple, Sequence import argparse from prompt_toolkit import HTML, PromptSession, prompt,print_formatted_text from prompt_toolkit.formatted_text import FormattedText from prompt_toolkit.selection import SelectionState from prompt_toolkit.history import FileHistory from prompt_toolkit.auto_suggest import AutoSuggestFromHistory from prompt_toolkit.completion import WordCompleter from prompt_toolkit.styles import Style directory = os.path.dirname(__file__) sys.path.append(directory + '/../../') import proxy from aios_kernel import * sys.path.append(directory + '/../../component/') from agent_manager import AgentManager from workflow_manager import WorkflowManager logger = logging.getLogger(__name__) shell_style = Style.from_dict({ 'title': '#87d7ff bold', #RGB 'content': '#007f00', # resp content 'prompt': '#00FF00', 'error': '#8F0000 bold' }) class AIOS_Shell: def __init__(self,username:str) -> None: self.username = username self.current_target = "_" self.current_topic = "default" self.is_working = True def declare_all_user_config(self): user_data_dir = AIStorage.get_instance().get_myai_dir() contact_config_path =os.path.abspath(f"{user_data_dir}/contacts.toml") cm = ContactManager.get_instance(contact_config_path) cm.load_data() user_config = AIStorage.get_instance().get_user_config() user_config.add_user_config("username","username is your full name when using AIOS",False,None) user_config.add_user_config("telegram","Your telgram username",False,None) user_config.add_user_config("email","Your email",False,None) user_config.add_user_config("feature.llama","enable Local-llama feature",True,"False") user_config.add_user_config("feature.aigc","enable AIGC feature",True,"False") openai_node = OpenAI_ComputeNode.get_instance() openai_node.declare_user_config() user_config.add_user_config("shell.current","last opened target and topic",True,"default@Jarvis") proxy.declare_user_config() google_text_to_speech = GoogleTextToSpeechNode.get_instance() google_text_to_speech.declare_user_config() Local_Stability_ComputeNode.declare_user_config() #Stability_ComputeNode.declare_user_config() async def _handle_no_target_msg(self,bus:AIBus,target_id:str) -> bool: agent : AIAgent = await AgentManager.get_instance().get(target_id) if agent is not None: bus.register_message_handler(target_id,agent._process_msg) return True a_workflow = await WorkflowManager.get_instance().get_workflow(target_id) if a_workflow is not None: bus.register_message_handler(target_id,a_workflow._process_msg) return True return False async def is_agent(self,target_id:str) -> bool: agent : AIAgent = await AgentManager.get_instance().get(target_id) if agent is not None: return True else: return False async def initial(self) -> bool: cm = ContactManager.get_instance() owenr = cm.find_contact_by_name(self.username) if owenr is None: owenr = Contact(self.username) owenr.added_by = self.username owenr.is_family_member = True owenr.email = AIStorage.get_instance().get_user_config().get_value("email") owenr.telegram = AIStorage.get_instance().get_user_config().get_value("telegram") cm.add_family_member(self.username,owenr) knowledge_env = KnowledgeEnvironment("knowledge") Environment.set_env_by_id("knowledge",knowledge_env) cal_env = CalenderEnvironment("calender") await cal_env.start() Environment.set_env_by_id("calender",cal_env) workspace_env = WorkspaceEnvironment("bash") Environment.set_env_by_id("bash",workspace_env) paint_env = PaintEnvironment("paint") Environment.set_env_by_id("paint",paint_env) if await AgentManager.get_instance().initial() is not True: logger.error("agent manager initial failed!") return False if await WorkflowManager.get_instance().initial() is not True: logger.error("workflow manager initial failed!") return False open_ai_node = OpenAI_ComputeNode.get_instance() if await open_ai_node.initial() is not True: logger.error("openai node initial failed!") return False ComputeKernel.get_instance().add_compute_node(open_ai_node) llama_nodes = ComputeNodeConfig.get_instance().initial() for llama_node in llama_nodes: llama_node.start() ComputeKernel.get_instance().add_compute_node(llama_node) if await AIStorage.get_instance().is_feature_enable("llama"): llama_ai_node = LocalLlama_ComputeNode() if await llama_ai_node.initial() is True: await llama_ai_node.start() ComputeKernel.get_instance().add_compute_node(llama_ai_node) else: logger.error("llama node initial failed!") await AIStorage.get_instance().set_feature_init_result("llama",False) if await AIStorage.get_instance().is_feature_enable("aigc"): try: google_text_to_speech_node = GoogleTextToSpeechNode.get_instance() google_text_to_speech_node.init() ComputeKernel.get_instance().add_compute_node(google_text_to_speech_node) except Exception as e: logger.error(f"google text to speech node initial failed! {e}") await AIStorage.get_instance.set_feature_init_result("aigc",False) # stability_api_node = Stability_ComputeNode() # if await stability_api_node.initial() is not True: # logger.error("stability api node initial failed!") # ComputeKernel.get_instance().add_compute_node(stability_api_node) local_st_text_compute_node = LocalSentenceTransformer_Text_ComputeNode() if local_st_text_compute_node.initial() is not True: logger.error("local sentence transformer text embedding node initial failed!") else: ComputeKernel.get_instance().add_compute_node(local_st_text_compute_node) local_st_image_compute_node = LocalSentenceTransformer_Image_ComputeNode() if local_st_image_compute_node.initial() is not True: logger.error("local sentence transformer image embedding node initial failed!") else: ComputeKernel.get_instance().add_compute_node(local_st_image_compute_node) await ComputeKernel.get_instance().start() AIBus().get_default_bus().register_unhandle_message_handler(self._handle_no_target_msg) AIBus().get_default_bus().register_message_handler(self.username,self._user_process_msg) KnowledgePipline.get_instance().initial() TelegramTunnel.register_to_loader() EmailTunnel.register_to_loader() user_data_dir = str(AIStorage.get_instance().get_myai_dir()) tunnels_config_path = os.path.abspath(f"{user_data_dir}/etc/tunnels.cfg.toml") tunnel_config = None try: tunnel_config = toml.load(tunnels_config_path) if tunnel_config is not None: await AgentTunnel.load_all_tunnels_from_config(tunnel_config) except Exception as e: logger.warning(f"load tunnels config from {tunnels_config_path} failed!") return True def get_version(self) -> str: return "0.5.1" async def send_msg(self,msg:str,target_id:str,topic:str,sender:str = None) -> str: agent_msg = AgentMsg() agent_msg.set(sender,target_id,msg) agent_msg.topic = topic resp = await AIBus.get_default_bus().send_message(agent_msg) if resp is not None: if resp.msg_type != AgentMsgType.TYPE_SYSTEM: return resp.body else: return f"Process Message Error: {resp.body} Please check logs/aios.log for more details!" else: return "System Error: Timeout, no resopnse! Please check logs/aios.log for more details!" async def _user_process_msg(self,msg:AgentMsg) -> AgentMsg: pass async def get_tunnel_config_from_input(self,tunnel_target,tunnel_type): tunnel_config = {} tunnel_config["tunnel_id"] = f"{tunnel_type}_2_{tunnel_target}" tunnel_config["target"] = tunnel_target input_table = {} tunnel_introduce : str = "" match tunnel_type: case "telegram": tunnel_config["type"] = "TelegramTunnel" input_table["token"] = UserConfigItem("telegram bot token") input_table["allow"] = UserConfigItem("allow group (default is member,you can choose contact or guest)") case "email": tunnel_config["type"] = "EmailTunnel" case _: error_text = FormattedText([("class:error", f"tunnel type {tunnel_type}not support!")]) print_formatted_text(error_text,style=shell_style) return None intro_text = FormattedText([("class:prompt", tunnel_introduce)]) print_formatted_text(intro_text,style=shell_style) for key,item in input_table.items(): user_input = await try_get_input(f"{key} : {item.desc}") if user_input is None: return None tunnel_config[key] = user_input return tunnel_config async def append_tunnel_config(self,tunnel_config): user_data_dir = AIStorage.get_instance().get_myai_dir() tunnels_config_path = os.path.abspath(f"{user_data_dir}/etc/tunnels.cfg.toml") all_tunnels = None try: all_tunnels = toml.load(tunnels_config_path) except Exception as e: logger.warning(f"load tunnels config for append from {tunnels_config_path} failed! {e}") if all_tunnels is None: all_tunnels = {} all_tunnels[tunnel_config["tunnel_id"]] = tunnel_config try: f = open(tunnels_config_path,"w") if f: toml.dump(all_tunnels,f) logger.info(f"append tunnel config to {tunnels_config_path} success!") else: logger.warning(f"append tunnel config to {tunnels_config_path} failed!") except Exception as e: logger.warning(f"append tunnels config from {tunnels_config_path} failed! {e}") async def handle_contact_commands(self,args): cm = ContactManager.get_instance() if len(args) < 1: return FormattedText([("class:error", f'/contact $contact_name, Like /contact "Jim Green"')]) contact_name = args[0] contact = cm.find_contact_by_name(contact_name) is_update = False if contact is not None: #show old info and ask user to update or remove is_update = True op_str = await try_get_input(f"Contact {contact_name} already exist, update or remove? (u/r)") if op_str is None: return None if op_str == "r": cm.remove_contact(contact_name) return FormattedText([("class:title", f"remove {contact_name} success!")]) else: print(f"old info: {contact}") else: contact = Contact(contact_name) contact.is_family_member = False is_family_member = await try_get_input(f"Is {contact_name} your family member? (y/n)") if is_family_member is not None: if is_family_member == "y" or is_family_member == "Y": contact.is_family_member = True else: return None contact_telegram = await try_get_input(f"Input {contact_name}'s telegram username:") if contact_telegram is None: return None contact.telegram = contact_telegram contact_email = await try_get_input(f"Input {contact_name}'s email:") if contact_email is None: return None contact.email = contact_email contact_phone = await try_get_input(f"Input {contact_name}'s phone (optional):") if contact_phone is not None: contact.phone = contact_phone contact_note = await try_get_input(f"Input {contact_name}'s note (optional):") if contact_note is not None: contact.note = contact_note contact.added_by = self.username if is_update: cm.set_contact(contact_name,contact) else: cm.add_contact(contact_name,contact) async def handle_knowledge_commands(self, args): show_text = FormattedText([("class:title", "sub command not support!\n" "/knowledge add email | dir\n" "/knowledge journal [$topn]\n" "/knowledge query $object_id\n")]) if len(args) < 1: return show_text sub_cmd = args[0] if sub_cmd == "add": if len(args) < 2: return show_text if args[1] == "email": config = dict() for key, item in KnowledgeEmailSource.user_config_items(): user_input = await try_get_input(f"{key} : {item}") if user_input is None: return show_text config[key] = user_input error = KnowledgePipline.get_instance().add_email_source(KnowledgeEmailSource(config)) if error is not None: return FormattedText([("class:title", f"/knowledge add email failed {error}\n")]) else: KnowledgePipline.get_instance().save_cosnfig() if args[1] == "dir": config = dict() for key, item in KnowledgeDirSource.user_config_items(): user_input = await try_get_input(f"{key} : {item}") if user_input is None: return show_text config[key] = user_input error = KnowledgePipline.get_instance().add_dir_source(KnowledgeDirSource(config)) if error is not None: return FormattedText([("class:title", f"/knowledge add dir failed {error}\n")]) else: KnowledgePipline.get_instance().save_config() else: return show_text if sub_cmd == "journal": topn = 10 if len(args) == 1 else int(args[1]) journals = [str(journal) for journal in KnowledgePipline.get_instance().get_latest_journals(topn)] print_formatted_text("\r\n".join(journals)) if sub_cmd == "query": if len(args) < 2: return show_text from knowledge import ObjectID, ObjectType object_id = ObjectID.from_base58(args[1]) if object_id.get_object_type() == ObjectType.Image: from PIL import Image import io image = KnowledgeBase().load_object(object_id) image_data = KnowledgeBase().bytes_from_object(image) image = Image.open(io.BytesIO(image_data)) image.show() async def handle_node_commands(self, args): show_text = FormattedText([("class:title", "sub command not support!\n" "/node add llama $model_name $url\n" "/node rm llama $model_name $url\n" "/node list\n")]) if len(args) < 1: return show_text sub_cmd = args[0] if sub_cmd == "add": if len(args) < 2: return show_text if args[1] == "llama": if len(args) < 4: return show_text model_name = args[2] url = args[3] ComputeNodeConfig.get_instance().add_node("llama", url, model_name) ComputeNodeConfig.get_instance().save() node = LocalLlama_ComputeNode(url, model_name) node.start() ComputeKernel.get_instance().add_compute_node(node) else: return show_text elif sub_cmd == "rm": if len(args) < 2: return show_text if args[1] == "llama": if len(args) < 4: return show_text model_name = args[3] url = args[4] ComputeNodeConfig.get_instance().remove_node("llama", url, model_name) ComputeNodeConfig.get_instance().save() else: return show_text elif sub_cmd == "list": print_formatted_text(ComputeNodeConfig.get_instance().list()) async def call_func(self,func_name, args): match func_name: case 'send': show_text = FormattedText([("class:error", f'send args error,/send Tracy "Hello! It is a good day!" default')]) if len(args) == 3: target_id = args[0] msg_content = args[1] topic = args[2] resp = await self.send_msg(msg_content,target_id,topic,self.username) show_text = FormattedText([("class:title", f"{self.current_topic}@{self.current_target} >>> "), ("class:content", resp)]) return show_text case 'set_config': show_text = FormattedText([("class:error", f"set config args error,/set_config $config_item! ")]) if len(args) == 1: key = args[0] config_item = AIStorage.get_instance().get_user_config().get_config_item(key) old_value = AIStorage.get_instance().get_user_config().get_value(key) if config_item is not None: value = await session.prompt_async(f"{key} : {config_item.desc} \nCurrent : {old_value}\nPlease input new value:",style=shell_style) AIStorage.get_instance().get_user_config().set_value(key,value) await AIStorage.get_instance().get_user_config().save_to_user_config() show_text = FormattedText([("class:title", f"set {key} to {value} success!")]) else: show_text = FormattedText([("class:error", f"set config failed! config item {key} not found!")]) return show_text case 'connect': show_text = FormattedText([("class:error", "args error, /connect $target")]) if len(args) < 1: return show_text tunnel_target = args[0] if len(args) < 2: tunnel_type = "telegram" else: tunnel_type = args[1] tunnel_config = await self.get_tunnel_config_from_input(tunnel_target,tunnel_type) if tunnel_config: if await AgentTunnel.load_tunnel_from_config(tunnel_config): # append await self.append_tunnel_config(tunnel_config) show_text = FormattedText([("class:title", f"connect to {tunnel_target} success!")]) return show_text case 'knowledge': return await self.handle_knowledge_commands(args) case 'contact': return await self.handle_contact_commands(args) case 'open': if len(args) >= 1: target_id = args[0] else: show_text = FormattedText([("class:error", "/open Need Target Agent/Workflow ID! like /open Jarvis default")]) return show_text if len(args) >= 2: topic = args[1] else: topic = "default" self.current_target = target_id self.current_topic = topic show_text = FormattedText([("class:title", f"current session switch to {topic}@{target_id}")]) AIStorage.get_instance().get_user_config().set_value("shell.current",f"{self.current_topic}@{self.current_target}") await AIStorage.get_instance().get_user_config().save_to_user_config() return show_text case 'enable': if len(args) >= 1: feature = args[0] else: show_text = FormattedText([("class:error", "/enable Need Feature Name! like /enable llama")]) return show_text if await AIStorage.get_instance().is_feature_enable(feature): show_text = FormattedText([("class:title", f"Feature {feature} already enabled!")]) return show_text await AIStorage.get_instance().enable_feature(feature) show_text = FormattedText([("class:title", f"Feature {feature} enabled!")]) return show_text case 'disable': if len(args) >= 1: feature = args[0] else: show_text = FormattedText([("class:error", "/disable Need Feature Name! like /disable llama")]) return show_text if not await AIStorage.get_instance().is_feature_enable(feature): show_text = FormattedText([("class:title", f"Feature {feature} already disabled!")]) return show_text await AIStorage.get_instance().disable_feature(feature) show_text = FormattedText([("class:title", f"Feature {feature} disabled!")]) return show_text #case 'login': # if len(args) >= 1: # self.username = args[0] # AIBus().get_default_bus().register_message_handler(self.username,self._user_process_msg) # return self.username + " login success!" case 'history': num = 10 offset = 0 if args is not None: if len(args) >= 1: num = args[0] if len(args) >= 2: offset = args[1] db_path = "" if await self.is_agent(self.current_target): db_path = AgentManager.get_instance().db_path else: db_path = WorkflowManager.get_instance().db_file chatsession:AIChatSession = AIChatSession.get_session(self.current_target,f"{self.username}#{self.current_topic}",db_path,False) if chatsession is not None: msgs = chatsession.read_history(num,offset) format_texts = [] for msg in msgs: format_texts.append(("class:content",f"{msg.sender} >>> {msg.body}")) format_texts.append(("",f"\n-------------------\n")) return FormattedText(format_texts) return FormattedText([("class:title", f"chatsession not found")]) case 'node': return await self.handle_node_commands(args) case 'exit': os._exit(0) case 'help': return FormattedText([("class:title", f"GO to https://github.com/fiatrete/OpenDAN-Personal-AI-OS/issues ^_^")]) ########################################################################################################################## history = FileHistory('aios_shell_history.txt') session = PromptSession(history=history) def parse_function_call(func_string): if len(func_string) > 2: if func_string[0] == '/' and func_string[1] != '/': str_list = shlex.split(func_string[1:]) func_name = str_list[0] params = str_list[1:] return func_name, params else: return None async def try_get_input(desc:str,mutil_line:bool = False,check_func:callable = None) -> str: user_input = await session.prompt_async(f"{desc} \nType /exit to abort. \nPlease input:",style=shell_style) err_str = "" if check_func is None: if len(user_input) > 0: if user_input != "/exit": if mutil_line is False: user_input = user_input.strip() return user_input else: return None else: is_ok,err_str = check_func(user_input) if is_ok: return user_input error_text = FormattedText([("class:error", err_str)]) print_formatted_text(error_text,style=shell_style) return await try_get_input(desc,check_func) async def get_user_config_from_input(check_result:dict) -> bool: for key,item in check_result.items(): user_input = await try_get_input(f"System config {key} ({item.desc}) not define!") if user_input is None: if item.is_optional: continue else: True if len(user_input) > 0: AIStorage.get_instance().get_user_config().set_value(key,user_input) await AIStorage.get_instance().get_user_config().save_to_user_config() return True async def main_daemon_loop(shell:AIOS_Shell): while shell.is_working: await asyncio.sleep(1) return 0 def print_welcome_screen(): print("\033[1;31m") logo = """ \t _______ ____________________ __ \t __ __ \______________________ __ \__ |__ | / / \t _ / / /__ __ \ _ \_ __ \_ / / /_ /| |_ |/ / \t / /_/ /__ /_/ / __/ / / / /_/ /_ ___ | /| / \t \____/ _ .___/\___//_/ /_//_____/ /_/ |_/_/ |_/ \t /_/ """ print(logo) print("\033[0m") print("\033[1;32m \t\tWelcome to OpenDAN - Your Personal AI OS\033[0m\n") introduce = """ \tOpenDAN (Open and Do Anything Now with AI) is revolutionizing the \tAI landscape with its Personal AI Operating System. Designed for \tseamless integration of diverse AI modules, it ensures unmatched \tinteroperability. OpenDAN empowers users to craft powerful AI agents: \tfrom butlers and assistants to personal tutors and digital companions. \tAll while retaining control. These agents can team up to tackle complex \tchallenges, integrate with existing services, and command IoT devices. \t \tWith OpenDAN, we're putting AI in your hands, making life simpler and smarter. \t \t================ AIOS Shell Handbook ================ \033[1;94m\tUnderstand the Shell Prompt :\033[0m [current_username]<->[current_topic]@[current_target]$ \033[1;94m\tTalk with Agent/Workflow :\033[0m Directly input and wait. \033[1;94m\tTalk with another Agent/Workflow :\033[0m /open $target_name [$topic_name] \033[1;94m\tInstall new Agent/Workflow :\033[0m /install $agent_name (Not support at 0.5.1) \t\t(For Developer) Download and unzip Agent to ~/myai/agents or ~/myai/workflows \033[1;94m\tView chat History :\033[0m /history \033[1;94m\tChange AIOS Owner's telegram username :\033[0m /set_config telegram \033[1;94m\tChange OpenAI API Token :\033[0m /set_config $openai_api_key \033[1;94m\tGive your Agent a Telegram account :\033[0m /connect $agent_name \033[1;94m\tAdd personal files to the AI Knowledge Base. \033[0m \t\t1) Copy your file to ~/myai/data \t\t2) /knowlege add dir \033[1;94m\tSearch your knowledge base :\033[0m /open Mia \033[1;94m\tCheck the progress of AI reading personal data :\033[0m /knowledge journal \033[1;94m\tQuery object with ID in knowledge base :\033[0m /knowledge query $object_id \033[1;94m\tOpen AI Bash (For Developer Only):\033[0m /open ai_bash \033[1;94m\tEnable AIGC Feature :\033[0m /enable aigc \033[1;94m\tEnable llama (Local LLM Kernel) :\033[0m /enable llama """ print(introduce) print(f"\033[1;34m \t\tVersion: {AIOS_Version}\n\033") print("\033[1;33m \tOpenDAN is an open-source project, let's define the future of Humans and AI together.\033[0m") print("\033[1;33m \tGithub\t: https://github.com/fiatrete/OpenDAN-Personal-AI-OS\033[0m") print("\033[1;33m \tWebsite\t: https://www.opendan.ai\033[0m") print("\n\n") async def main(): print_welcome_screen() print("Booting...") if os.path.isdir(f"{directory}/../../../rootfs"): AIStorage.get_instance().is_dev_mode = True else: AIStorage.get_instance().is_dev_mode = False if AIStorage.get_instance().is_dev_mode: logging.basicConfig(filename="aios_shell.log",filemode="w",encoding='utf-8',force=True, level=logging.INFO, format='[%(asctime)s]%(name)s[%(levelname)s]: %(message)s') else: dir_path = f"{AIStorage.get_instance().get_myai_dir()}/logs" if not os.path.exists(dir_path): os.makedirs(dir_path) log_file = f"{AIStorage.get_instance().get_myai_dir()}/logs/aios.log" handler = RotatingFileHandler(log_file, maxBytes=50*1024*1024, backupCount=100) logging.basicConfig(handlers=[handler], level=logging.INFO, format='%(asctime)s - %(name)s - %(levelname)s - %(message)s') is_daemon = False logger.info(f"Check Host OS :{os.name}") if os.name != 'nt': is_daemon = os.fstat(0) != os.fstat(1) or os.fstat(0) != os.fstat(2) shell = AIOS_Shell("user") shell.declare_all_user_config() await AIStorage.get_instance().initial() check_result = AIStorage.get_instance().get_user_config().check_config() if check_result is not None: if is_daemon: logger.error(check_result) return 1 else: #Remind users to enter necessary configurations. if await get_user_config_from_input(check_result) is False: return 1 shell.username = AIStorage.get_instance().get_user_config().get_value("username") init_result = await shell.initial() proxy.apply_storage() if init_result is False: if is_daemon: logger.error("aios shell initial failed!") return 1 else: print("aios shell initial failed!") return 1 print(f"aios shell {shell.get_version()} ready. Daemon:{is_daemon}") logger.info(f"aios shell {shell.get_version()} ready. Daemon:{is_daemon}") if is_daemon: return await main_daemon_loop(shell) completer = WordCompleter(['/send $target $msg $topic', '/open $target $topic', '/history $num $offset', '/connect $target', '/contact $name', '/knowledge add email | dir', '/knowledge journal [$topn]', '/knowledge query $object_id', '/set_config $key', '/enable $feature', '/disable $feature', '/node add llama $model_name $url', '/node rm llama $model_name $url', '/show', '/exit', '/help'], ignore_case=True) current = AIStorage.get_instance().get_user_config().get_value("shell.current") current = current.split("@") shell.current_target = current[1] shell.current_topic = current[0] await asyncio.sleep(0.2) while True: user_input = await session.prompt_async(f"{shell.username}<->{shell.current_topic}@{shell.current_target}$ ",completer=completer,style=shell_style) if len(user_input) <= 1: continue func_call = parse_function_call(user_input) show_text = None if func_call: show_text = await shell.call_func(func_call[0], func_call[1]) else: resp = await shell.send_msg(user_input,shell.current_target,shell.current_topic,shell.username) show_text = FormattedText([ ("class:title", f"{shell.current_topic}@{shell.current_target} >>> "), ("class:content", resp) ]) print_formatted_text(show_text,style=shell_style) #print_formatted_text(f"{shell.username}<->{shell.current_topic}@{shell.current_target} >>> {resp}",style=shell_style) if __name__ == "__main__": asyncio.run(main())