gyt/opendan
1
0
Fork 0
Code Issues Pull Requests Actions Packages Projects Releases Wiki Activity

Merge pull request #62 from wugren/MVP

Browse Source 
Add story maker
This commit is contained in:
Liu Zhicong
2023-09-22 00:48:15 -07:00
committed by GitHub
parent 0d556003c5 3061e00800
commit add4357c24
15 changed files with 521 additions and 227 deletions
Download Patch File Download Diff File Expand all files Collapse all files
rootfs/agents/fairy_tale_writer/agent.toml
+8
View File
@@ -0,0 +1,8 @@
instance_id = "fairy_tale_writer"
fullname = "tracy wang"
llm_model_name = "gpt-3.5-turbo-16k-0613"
enable_function = []
[[prompt]]
role = "system"
content = "你是一个童话做作家，能够写出各种有趣的童话。"
rootfs/agents/manager/agent.toml
+2
View File
@@ -1,5 +1,7 @@
instance_id = "agent:xxxxxxabcde"
fullname = "musk"
enable_function = []
[[prompt]]
role = "system"
content = "你有丰富的管理技能，擅长将复杂工作拆解成简单的任务，让团队成员高效协作。"
rootfs/agents/speecher/agent.toml
+8
View File
@@ -0,0 +1,8 @@
instance_id = "speecher"
fullname = "tracy wang"
llm_model_name = "gpt-3.5-turbo-16k-0613"
enable_function = ["text_to_speech"]
[[prompt]]
role = "system"
content = "你是一个故事播音员，可以将故事演播成音频，演播前需要将故事改编成播音剧本，提取旁白和角色台词，以及每个角色需要有性别、年龄、以及每句台词的语气等。如果生成了音频文件则告知你的用户。"
rootfs/workflows/story_maker/workflow.toml
+42
View File
@@ -0,0 +1,42 @@
name = "story_maker"
[filter]
"*" = "manager"
[roles.manager]
name = "manager"
fullname = "总导演"
agent="manager"
enable_function = []
[[roles.manager.prompt]]
role="system"
content="""
你是一个语音故事制作总导演,与客户对接并向团队下达指令。你的团队分为下面几个成员:writer,speecher。一个故事制作分成两个阶段：让writer写出故事，再交由speecher演播故事生成音频文件。你的基本工作模式是：
1. 收到客户的明确的指令后,让writer写出故事
2. 将writer写出的故事交给speecher演播
3. 获得音频文件之后，将音频文件的存放路径交给客户
4. 当你决定要和成员通信时，请使用下面形式输出需要通信的消息
```
##/send_msg 成员名称
内容
```
"""
[roles.writer]
name = "writer"
agent = "fairy_tale_writer"
fullname = "作家"
enable_function = []
[[roles.writer.prompt]]
role="system"
content=""
[roles.speecher]
name = "speecher"
agent = "speecher"
enable_function = ["text_to_speech"]
[[roles.speecher.prompt]]
role="system"
content=""
src/aios_kernel/__init__.py
+1
View File
@@ -19,6 +19,7 @@ from .tg_tunnel import TelegramTunnel
from .email_tunnel import EmailTunnel
from .storage import ResourceLocation,AIStorage,UserConfig,UserConfigItem
from .contact_manager import ContactManager,Contact,FamilyMember
from .text_to_speech_function import TextToSpeechFunction
from .workspace_env import WorkspaceEnvironment
AIOS_Version = "0.5.1, build 2023-9-17"
src/aios_kernel/agent.py
+40 -38
View File
@@ -26,7 +26,7 @@ class AgentPrompt:
self.system_message = None
def as_str(self)->str:
result_str = ""
result_str = ""
if self.system_message:
result_str += self.system_message.get("role") + ":" + self.system_message.get("content") + "\n"
if self.messages:
@@ -34,18 +34,18 @@ class AgentPrompt:
result_str += msg.get("role") + ":" + msg.get("content") + "\n"
return result_str
def to_message_list(self):
result = []
if self.system_message:
result.append(self.system_message)
result.extend(self.messages)
return result
def append(self,prompt):
if prompt is None:
return
if prompt.system_message is not None:
if self.system_message is None:
self.system_message = prompt.system_message
@@ -99,9 +99,9 @@ class AIAgentTemplete:
logger.error("load prompt from config failed!")
return False
return True
class AIAgent:
def __init__(self) -> None:
@@ -111,7 +111,7 @@ class AIAgent:
self.agent_id:str = None
self.template_id:str = None
self.fullname:str = None
self.powerby = None
self.powerby = None
self.enable = True
self.enable_kb = False
self.enable_timestamp = False
@@ -124,7 +124,7 @@ class AIAgent:
self.owner_env : Environment = None
self.owenr_bus = None
self.enable_function_list = []
@classmethod
def create_from_templete(cls,templete:AIAgentTemplete, fullname:str):
# Agent just inherit from templete on craete,if template changed,agent will not change
@@ -137,7 +137,7 @@ class AIAgent:
result_agent.powerby = templete.author
result_agent.prompt = templete.prompt
return result_agent
def load_from_config(self,config:dict) -> bool:
if config.get("instance_id") is None:
logger.error("agent instance_id is None!")
@@ -190,7 +190,7 @@ class AIAgent:
if llm_result_str == "ignore":
r.state = "ignore"
return r
lines = llm_result_str.splitlines()
is_need_wait = False
@@ -207,7 +207,7 @@ class AIAgent:
r.send_msgs.append(new_msg)
is_need_wait = True
case "post_msg":# postmsg($target_id,$msg_content)
if len(func_args) != 1:
logger.error(f"parse postmsg failed! {func_call}")
@@ -217,22 +217,22 @@ class AIAgent:
msg_content = func_item.body
new_msg.set(self.agent_id,target_id,msg_content)
r.post_msgs.append(new_msg)
case "call":# call($func_name,$args_str)
r.calls.append(func_item)
is_need_wait = True
return True
case "post_call": # post_call($func_name,$args_str)
r.post_calls.append(func_item)
return True
return True
current_func : FunctionItem = None
for line in lines:
if line.startswith("##/"):
if current_func:
if check_args(current_func) is False:
r.resp += current_func.dumps()
func_name,func_args = AgentMsg.parse_function_call(line[3:])
current_func = FunctionItem(func_name,func_args)
else:
@@ -240,11 +240,11 @@ class AIAgent:
current_func.append_body(line + "\n")
else:
r.resp += line + "\n"
if current_func:
if check_args(current_func) is False:
r.resp += current_func.dumps()
if len(r.send_msgs) > 0 or len(r.calls) > 0:
r.state = "waiting"
else:
@@ -281,21 +281,22 @@ class AIAgent:
def _get_inner_functions(self) -> dict:
if self.owner_env is None:
return None
all_inner_function = self.owner_env.get_all_ai_functions()
if all_inner_function is None:
return None
result_func = []
result_len = 0
for inner_func in all_inner_function:
func_name = inner_func.get_name()
if self.enable_function_list:
if self.enable_function_list is not None:
if len(self.enable_function_list) > 0:
if func_name not in self.enable_function_list:
logger.debug(f"ageint {self.agent_id} ignore inner func:{func_name}")
continue
else:
continue
this_func = {}
this_func["name"] = func_name
this_func["description"] = inner_func.get_description()
@@ -315,28 +316,29 @@ class AIAgent:
func_node : AIFunction = self.owner_env.get_ai_function(func_name)
if func_node is None:
return "execute failed,function not found"
ineternal_call_record = AgentMsg.create_internal_call_msg(func_name,arguments,org_msg.get_msg_id(),org_msg.target)
try:
result_str:str = await func_node.execute(**arguments)
except Exception as e:
result_str = "call error:" + str(e)
result_str = "call error:" + str(e)
logger.error(f"llm execute inner func:{func_name} error:{e}")
logger.info("llm execute inner func result:" + result_str)
inner_functions,inner_function_len = self._get_inner_functions()
prompt.messages.append({"role":"function","content":result_str,"name":func_name})
task_result:ComputeTaskResult = await ComputeKernel.get_instance().do_llm_completion(prompt,self.llm_model_name,self.max_token_size,inner_functions)
ineternal_call_record.result_str = task_result.result_str
ineternal_call_record.done_time = time.time()
org_msg.inner_call_chain.append(ineternal_call_record)
if stack_limit > 0:
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
return await self._execute_func(inner_func_call_node,prompt,org_msg,stack_limit-1)
return await self._execute_func(inner_func_call_node,prompt,org_msg,stack_limit-1)
else:
return task_result.result_str
@@ -346,7 +348,7 @@ class AIAgent:
def _format_msg_by_env_value(self,prompt:AgentPrompt):
if self.owner_env is None:
return
for msg in prompt.messages:
old_content = msg.get("content")
msg["content"] = old_content.format_map(self.owner_env)
@@ -382,7 +384,7 @@ class AIAgent:
system_prompt_len = prompt.get_prompt_token_len()
input_len = len(msg.body)
history_prmpt,history_token_len = await self._get_prompt_from_session(chatsession,system_prompt_len + function_token_len,input_len)
prompt.append(history_prmpt) # chat context
@@ -399,7 +401,7 @@ class AIAgent:
if inner_func_call_node:
#TODO to save more token ,can i use msg_prompt?
final_result = await self._execute_func(inner_func_call_node,prompt,msg)
llm_result : LLMResult = self._get_llm_result_type(final_result)
is_ignore = False
result_prompt_str = ""
@@ -417,21 +419,21 @@ class AIAgent:
agent_sesion = AIChatSession.get_session(self.agent_id,f"{sendmsg.target}#{sendmsg.topic}",self.chat_db)
agent_sesion.append(sendmsg)
agent_sesion.append(send_resp)
final_result = llm_result.resp + result_prompt_str
if is_ignore is not True:
resp_msg = msg.create_resp_msg(final_result)
chatsession.append(msg)
chatsession.append(resp_msg)
return resp_msg
return None
def get_id(self) -> str:
return self.agent_id
def get_fullname(self) -> str:
return self.fullname
@@ -440,14 +442,14 @@ class AIAgent:
def get_llm_model_name(self) -> str:
return self.llm_model_name
def get_max_token_size(self) -> int:
return self.max_token_size
async def _get_prompt_from_session(self,chatsession:AIChatSession,system_token_len,input_token_len,is_groupchat=False) -> AgentPrompt:
# TODO: get prompt from group chat is different from single chat
history_len = (self.max_token_size * 0.7) - system_token_len - input_token_len
messages = chatsession.read_history() # read
messages = chatsession.read_history() # read
result_token_len = 0
result_prompt = AgentPrompt()
read_history_msg = 0
src/aios_kernel/bus.py
+23 -21
View File
@@ -19,14 +19,14 @@ class AIBusHandler:
async def handle_message(self,msg:AgentMsg) -> Any:
if self.handler is None:
return None
resp_msg = await self.handler(msg)
if self.enable_defualt_proc:
if resp_msg is not None:
await self.owner_bus.post_message(resp_msg,False)
return resp_msg
class AIBus:
_instance = None
@classmethod
@@ -48,16 +48,16 @@ class AIBus:
if msg.rely_msg_id is not None:
handler.results[msg.rely_msg_id] = msg
return None
handler.queue.put_nowait(msg)
self.start_process(target_id)
return True
if use_unhandle:
if self.unhandle_handler is not None:
if await self.unhandle_handler(self,msg):
return await self.post_message(msg,False)
logger.warn(f"post message to {msg.target} failed!,target not found")
return False
@@ -71,7 +71,7 @@ class AIBus:
if sender_handler is None:
logger.warn(f"sender {sender_id} not register on AI_BUS!")
return None
post_result = await self.post_message(msg)
if post_result is False:
return None
@@ -84,37 +84,39 @@ class AIBus:
msg.status = AgentMsgStatus.RESPONSED
del sender_handler.results[msg.msg_id]
return resp
await asyncio.sleep(0.2)
retry_times += 1
if retry_times > 5*120: # default timeout is 120 sec
if retry_times > 5*240: # default timeout is 240 sec
msg.status = AgentMsgStatus.ERROR
return None
return None
def register_unhandle_message_handler(self,handler:Any) -> Queue:
self.unhandle_handler = handler
# means sub
def register_message_handler(self,handler_name:str,handler:Any) -> Queue:
handler_node = AIBusHandler(handler,self)
def register_message_handler(self,handler_name:str,handler:Any) -> Queue:
handler_node = AIBusHandler(handler,self)
self.handlers[handler_name] = handler_node
return handler_node.queue
async def process_queue(self, handler:AIBusHandler):
while True:
# Wait for a message
message = await handler.queue.get()
#try:
try:
# Try to handle the message
await handler.handle_message(message)
#except Exception as e:
await handler.handle_message(message)
except Exception as e:
# If an error occurs, put the message back into the queue
# logger.error(f"handle message {message.msg_id} failed! {e}")
logger.error(f"handle message {message.msg_id} failed! {e}")
logger.exception(e)
raise e
#self.queues[name].put_nowait(message)
return
def start_process(self,target_name):
@@ -122,12 +124,12 @@ class AIBus:
if handler is None:
logger.error(f"handler {target_name} not found!")
return
if handler.handler is None:
return
if handler.working_task is not None:
logger.warn(f"handler {target_name} is already working!")
return
handler.working_task = asyncio.create_task(self.process_queue(handler))
handler.working_task = asyncio.create_task(self.process_queue(handler))
src/aios_kernel/chatsession.py
+14 -13
View File
@@ -35,10 +35,10 @@ class ChatSessionDB:
self._create_table(conn)
return conn
def close(self):
if not hasattr(self.local, 'conn'):
return
return
self.local.conn.close()
def _create_table(self, conn):
@@ -56,7 +56,7 @@ class ChatSessionDB:
# create messages table
# reciver_id could be None
conn.execute("""
CREATE TABLE IF NOT EXISTS Messages (
MessageID TEXT PRIMARY KEY,
@@ -142,7 +142,7 @@ class ChatSessionDB:
except Error as e:
logging.error("Error occurred while inserting message: %s", e)
return -1 # return -1 if an error occurs
def get_chatsession_by_id(self, session_id):
"""Get a message by its ID"""
conn = self._get_conn()
@@ -150,7 +150,7 @@ class ChatSessionDB:
c.execute("SELECT * FROM ChatSessions WHERE SessionID = ?", (session_id,))
chatsession = c.fetchone()
return chatsession
def get_chatsession_by_owner_topic(self, owner_id, topic):
"""Get a chatsession by its owner and topic"""
conn = self._get_conn()
@@ -175,7 +175,7 @@ class ChatSessionDB:
except Error as e:
logging.error("Error occurred while getting sessions: %s", e)
return -1, None # return -1 and None if an error occurs
def get_message_by_id(self, message_id):
"""Get a message by its ID"""
conn =self._get_conn()
@@ -216,7 +216,7 @@ class ChatSessionDB:
except Error as e:
logging.error("Error occurred while updating message status: %s", e)
return -1 # return -1 if an error occurs
# chat session store the chat history between owner and agent
# chat session might be large, so can read / write at stream mode.
@@ -230,7 +230,7 @@ class AIChatSession:
# cls._dbs[db_path] = db
# db.get_chatsession_by_id(session_id)
# #result = AIChatSession()
@classmethod
def get_session(cls,owner_id:str,session_topic:str,db_path:str,auto_create = True) -> str:
db = cls._dbs.get(db_path)
@@ -249,21 +249,22 @@ class AIChatSession:
result = AIChatSession(owner_id,session[0],db)
result.topic = session_topic
return result
return result
def __init__(self,owner_id:str, session_id:str, db:ChatSessionDB) -> None:
self.owner_id :str = owner_id
self.session_id : str = session_id
self.db : ChatSessionDB = db
self.topic : str = None
self.start_time : str = None
def get_owner_id(self) -> str:
return self.owner_id
def read_history(self, number:int=10,offset=0) -> [AgentMsg]:
return []
msgs = self.db.get_messages(self.session_id, number, offset)
result = []
for msg in msgs:
@@ -298,4 +299,4 @@ class AIChatSession:
# """chat session changed event handler"""
# pass
#TODO : add iterator interface for read chat history
#TODO : add iterator interface for read chat history
src/aios_kernel/compute_kernel.py
+44 -10
View File
@@ -7,7 +7,7 @@ from asyncio import Queue
from .agent import AgentPrompt
from .compute_node import ComputeNode
from .compute_task import ComputeTask, ComputeTaskState, ComputeTaskResult
from .compute_task import ComputeTask, ComputeTaskState, ComputeTaskResult, ComputeTaskType
logger = logging.getLogger(__name__)
@@ -23,7 +23,7 @@ class ComputeKernel:
if cls._instance is None:
cls._instance = ComputeKernel()
return cls._instance
def __init__(self) -> None:
self.is_start = False
self.task_queue = Queue()
@@ -73,7 +73,7 @@ class ComputeKernel:
hit_pos = random.randint(0, total_weights - 1)
for i in range(min(len(support_nodes) - 1, hit_pos), -1, -1):
if support_nodes[i]["pos"] <= hit_pos:
return node
return support_nodes[i]["node"]
logger.warning(
f"task {task.display()} is not support by any compute node")
@@ -118,7 +118,7 @@ class ComputeKernel:
if task_req.state == ComputeTaskState.ERROR:
break
if check_times >= 20:
if check_times >= 120:
task_req.state = ComputeTaskState.ERROR
break
@@ -129,7 +129,7 @@ class ComputeKernel:
if task_req.state == ComputeTaskState.DONE:
return task_req.result
return "error!"
raise Exception("error!")
def text_embedding(self,input:str,model_name:Optional[str] = None):
@@ -137,7 +137,7 @@ class ComputeKernel:
task_req.set_text_embedding_params(input,model_name)
self.run(task_req)
return task_req
async def do_text_embedding(self,input:str,model_name:Optional[str] = None) -> [float]:
task_req = self.text_embedding(input,model_name)
async def check_timer():
@@ -155,11 +155,45 @@ class ComputeKernel:
await asyncio.sleep(0.5)
check_times += 1
await asyncio.create_task(check_timer())
if task_req.state == ComputeTaskState.DONE:
return task_req.result.result
return "error!"
return "error!"
async def do_text_to_speech(self,
input:str,
language_code:Optional[str] = None,
gender: Optional[str] = None,
age: Optional[str] = None,
voice_name: Optional[str] = None,
tone: Optional[str] = None):
task_req = ComputeTask()
task_req.params["text"] = input
task_req.params["language_code"] = language_code
task_req.params["gender"] = gender
task_req.params["age"] = age
task_req.params["voice_name"] = voice_name
task_req.params["tone"] = tone
task_req.task_type = ComputeTaskType.TEXT_2_VOICE
self.run(task_req)
check_times = 0
while True:
if task_req.state == ComputeTaskState.DONE:
break
if task_req.state == ComputeTaskState.ERROR:
break
if check_times >= 60:
task_req.state = ComputeTaskState.ERROR
break
await asyncio.sleep(0.5)
check_times += 1
if task_req.state == ComputeTaskState.DONE:
return task_req.result.result
else:
raise Exception("do_text_to_speech failed!")
src/aios_kernel/google_text_to_speech_node.py
+89 -13
View File
@@ -3,9 +3,11 @@ import os
import asyncio
from asyncio import Queue
import logging
from typing import Optional
from google.cloud import texttospeech
from .storage import AIStorage
from .compute_task import ComputeTask, ComputeTaskResult, ComputeTaskState, ComputeTaskType
from .compute_node import ComputeNode
@@ -21,26 +23,78 @@ see:https://cloud.google.com/text-to-speech/docs/before-you-begin
class GoogleTextToSpeechNode(ComputeNode):
_instance = None
def __new__(cls, *args, **kwargs):
@classmethod
def get_instance(cls):
if cls._instance is None:
cls._instance = super(GoogleTextToSpeechNode, cls).__new__(cls)
cls._instance.is_start = False
cls._instance = cls()
return cls._instance
def __init__(self):
super().__init__()
if self.is_start is True:
logger.warn("GoogleTextToSpeechNode is already start")
return
self.is_start = True
self.node_id = "google_text_to_speech_node"
self.task_queue = Queue()
self.client: Optional[texttospeech.TextToSpeechClient] = None
self.client = texttospeech.TextToSpeechClient()
self.language_list = {
"cnm-CN": {
"female": ["cmn-CN-Standard-A",
"cmn-CN-Standard-D",
"cmn-CN-Wavenet-A",
"cmn-CN-Wavenet-D",
"cmn-TW-Standard-A",
"cmn-TW-Wavenet-A"],
"man": ["cmn-CN-Standard-B",
"cmn-CN-Standard-C",
"cmn-CN-Wavenet-B",
"cmn-CN-Wavenet-C",
"cmn-TW-Standard-B",
"cmn-TW-Standard-C",
"cmn-TW-Wavenet-B",
"cmn-TW-Wavenet-C"]
},
"en-US": {
"female": ["en-US-Neural2-C",
"en-US-Neural2-E",
"en-US-Neural2-F",
"en-US-Neural2-G",
"en-US-Neural2-H",
"en-US-News-K",
"en-US-News-L",
"en-US-Standard-C",
"en-US-Standard-E",
"en-US-Standard-F",
"en-US-Standard-G",
"en-US-Standard-H",
"en-US-Studio-O",
"en-US-Wavenet-C",
"en-US-Wavenet-E",
"en-US-Wavenet-F",
"en-US-Wavenet-G",
"en-US-Wavenet-H"],
"man": ["en-US-Polyglot-1",
"en-US-Standard-A",
"en-US-Standard-B",
"en-US-Standard-D",
"en-US-Standard-I",
"en-US-Standard-J",
"en-US-Studio-M",
"en-US-Wavenet-A",
"en-US-Wavenet-B",
"en-US-Wavenet-D",
"en-US-Wavenet-I",
"en-US-Wavenet-J"]
}
}
self.start()
def init(self):
user_config = AIStorage.get_instance().get_user_config()
google_application_credentials = user_config.get_value("google_application_credentials")
if google_application_credentials is None:
raise Exception("google_application_credentials is None!")
os.environ["GOOGLE_APPLICATION_CREDENTIALS"] = google_application_credentials
self.client = texttospeech.TextToSpeechClient()
def start(self):
async def _run_task_loop():
while True:
@@ -64,10 +118,24 @@ class GoogleTextToSpeechNode(ComputeNode):
task.state = ComputeTaskState.RUNNING
language_code = task.params["language_code"]
text = task.params["text"]
voice_name = task.params["voice_name"]
gender = task.params["gender"]
age = task.params["age"]
if language_code == "zh":
language_code = "cnm-CN"
elif language_code == "en":
language_code = "en-US"
else:
raise Exception(f"language_code {language_code} not support")
lang_list = self.language_list[language_code][gender]
voice = lang_list[hash(voice_name) % len(lang_list)]
synthesis_input = texttospeech.SynthesisInput(text=text)
voice = texttospeech.VoiceSelectionParams(language_code=language_code,
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL)
ssml_gender=texttospeech.SsmlVoiceGender.NEUTRAL,
name=voice)
audio_config = texttospeech.AudioConfig(audio_encoding=texttospeech.AudioEncoding.MP3)
@@ -95,10 +163,18 @@ class GoogleTextToSpeechNode(ComputeNode):
def get_capacity(self):
return 0
def is_support(self, task_type: ComputeTaskType) -> bool:
if task_type == ComputeTaskType.TEXT_2_VOICE:
def is_support(self, task: ComputeTask) -> bool:
if task.task_type == ComputeTaskType.TEXT_2_VOICE:
return True
return False
def is_local(self) -> bool:
return False
def declare_user_config(self):
if os.getenv("GOOGLE_APPLICATION_CREDENTIALS") is None:
user_config = AIStorage.get_instance().get_user_config()
user_config.add_user_config("google_application_credentials",
"google application credentials, please visit:https://cloud.google.com/text-to-speech/docs/before-you-begin",
False,
None)
src/aios_kernel/open_ai_node.py
+12 -11
View File
@@ -20,7 +20,7 @@ class OpenAI_ComputeNode(ComputeNode):
if cls._instance is None:
cls._instance = OpenAI_ComputeNode()
return cls._instance
@classmethod
def declare_user_config(cls):
if os.getenv("OPENAI_API_KEY_") is None:
@@ -46,7 +46,7 @@ class OpenAI_ComputeNode(ComputeNode):
if self.openai_api_key is None:
logger.error("openai_api_key is None!")
return False
openai.api_key = self.openai_api_key
self.start()
return True
@@ -68,7 +68,7 @@ class OpenAI_ComputeNode(ComputeNode):
resp = openai.Embedding.create(model=model_name,
input=input)
# resp = {
# "object": "list",
# "data": [
@@ -86,7 +86,7 @@ class OpenAI_ComputeNode(ComputeNode):
logger.info(f"openai response: {resp}")
result = ComputeTaskResult()
result = ComputeTaskResult()
result.set_from_task(task)
result.worker_id = self.node_id
result.result = resp["data"][0]["embedding"]
@@ -100,23 +100,23 @@ class OpenAI_ComputeNode(ComputeNode):
if max_token_size is None:
max_token_size = 4000
result_token = int(max_token_size * 0.4)
logger.info(f"call openai {mode_name} prompts: {prompts}")
result_token = max_token_size
if llm_inner_functions is None:
logger.info(f"call openai {mode_name} prompts: {prompts}")
resp = openai.ChatCompletion.create(model=mode_name,
messages=prompts,
max_tokens=result_token,
temperature=0.7)
else:
logger.info(f"call openai {mode_name} prompts: {prompts} functions: {json.dumps(llm_inner_functions)}")
resp = openai.ChatCompletion.create(model=mode_name,
messages=prompts,
functions=llm_inner_functions,
max_tokens=result_token,
temperature=0.7) # TODO: add temperature to task params?
logger.info(f"openai response: {json.dumps(resp, indent=4)}")
result = ComputeTaskResult()
@@ -139,6 +139,7 @@ class OpenAI_ComputeNode(ComputeNode):
result.result_message = resp["choices"][0]["message"]
if token_usage:
result.result_refers["token_usage"] = token_usage
logger.info(f"openai success response: {result.result_str}")
return result
case _:
task.state = ComputeTaskState.ERROR
@@ -148,7 +149,7 @@ class OpenAI_ComputeNode(ComputeNode):
if self.is_start is True:
return
self.is_start = True
async def _run_task_loop():
while True:
task = await self.task_queue.get()
@@ -171,13 +172,13 @@ class OpenAI_ComputeNode(ComputeNode):
def is_support(self, task: ComputeTask) -> bool:
if task.task_type == ComputeTaskType.LLM_COMPLETION:
if task.task_type == ComputeTaskType.LLM_COMPLETION:
if not task.params["model_name"]:
return True
model_name : str = task.params["model_name"]
if model_name.startswith("gpt-"):
return True
if task.task_type == ComputeTaskType.TEXT_EMBEDDING:
if task.params["model_name"] == "text-embedding-ada-002":
return True
src/aios_kernel/text_to_speech_function.py
+101
View File
@@ -0,0 +1,101 @@
import io
import logging
import os
import random
from typing import Dict
from aios_kernel import ComputeKernel
from aios_kernel.ai_function import AIFunction
from pydub import AudioSegment
logger = logging.getLogger(__name__)
class TextToSpeechFunction(AIFunction):
def __init__(self):
self.func_id = "text_to_speech"
self.description = "根据输入的剧本生成音频文件，成功时会返回音频文件路径"
def get_name(self) -> str:
return self.func_id
def get_description(self) -> str:
return self.description
def get_parameters(self) -> Dict:
return {
"type": "object",
"properties": {
"language": {"type": "string", "description": "演播语言", "enum": ["zh", "en"]},
"roles": {"type": "array", "items": {
"type": "object",
"properties": {
"name": {"type": "string", "description": "角色名字"},
"gender": {"type": "string", "description": "角色性别", "enum": ["man", "female"]},
"age": {"type": "string", "description": "年龄", "enum": ["child", "adult"]},
}}},
"lines": {"type": "array", "items": {
"type": "object",
"properties": {
"name": {"type": "string", "description": "角色名字"},
"tone": {"type": "string", "description": "演播情感",
"enum": ["happy", "sad", "angry", "fear", "disgust", "surprise", "neutral"]},
"text": {"type": "string", "description": "台词"},
}
}}
}
}
async def execute(self, **kwargs) -> str:
logger.info(f"execute text_to_speech function: {kwargs}")
language = kwargs.get("language")
if language is None:
language = "zh"
roles = kwargs.get("roles")
lines = kwargs.get("lines")
audio = None
for line in lines:
name = line.get("name")
tone = line.get("tone")
text = line.get("text")
gender = None
age = None
for role in roles:
role_name = role.get("name")
if role_name == name:
gender = role.get("gender")
age = role.get("age")
break
i = 0
while i < 3:
try:
data = await ComputeKernel.get_instance().do_text_to_speech(text, language, gender, age, name, tone)
if audio is None:
audio = AudioSegment.from_mp3(io.BytesIO(data))
else:
audio = audio + AudioSegment.from_mp3(io.BytesIO(data))
break
except Exception as e:
logger.error(f"do_text_to_speech failed: {e}")
i += 1
continue
if audio is not None:
path = os.path.join(os.path.realpath(os.curdir), "{}.mp3".format(''.join(random.sample('zyxwvutsrqponmlkjihgfedcba', 10))))
audio.export(path, format="mp3")
return "exec text_to_speech OK，speech file store at {}".format(path)
else:
return "exec text_to_speech failed"
def is_local(self) -> bool:
return True
def is_in_zone(self) -> bool:
return True
def is_ready_only(self) -> bool:
return False
src/aios_kernel/workflow.py
+58 -56
View File
@@ -2,7 +2,7 @@ import logging
import asyncio
import json
import os
import time
import time
from asyncio import Queue
from typing import Optional,Tuple,List
from abc import ABC, abstractmethod
@@ -32,7 +32,7 @@ class MessageFilter:
# TODO: add more filter
return None
def load_from_config(self,config:dict) -> bool:
self.filters = config
return True
@@ -68,8 +68,8 @@ class Workflow:
def load_from_config(self,config:dict) -> bool:
if config is None:
return False
if config.get("name") is None:
if config.get("name") is None:
logger.error("workflow config must have name")
return False
self.workflow_name = config.get("name")
@@ -84,7 +84,7 @@ class Workflow:
if self.rule_prompt.load_from_config(config.get("prompt")) is False:
logger.error("Workflow load prompt failed")
return False
if config.get("roles") is None:
logger.error("workflow config must have roles")
return False
@@ -106,13 +106,13 @@ class Workflow:
self.env_db_file = self.owner_workflow.env_db_file
self.workflow_env = WorkflowEnvironment(self.workflow_id,self.env_db_file)
env_ndoe = config.get("enviroment")
env_ndoe = config.get("enviroment")
if env_ndoe is not None:
if self._load_env_from_config(env_ndoe) is False:
logger.error("Workflow load env failed")
return False
connected_env_ndoe = config.get("connected_env")
connected_env_ndoe = config.get("connected_env")
if connected_env_ndoe is not None:
for _node in connected_env_ndoe:
env_id = _node.get("env_id")
@@ -124,13 +124,13 @@ class Workflow:
logger.error(f"Workflow load connected_env failed, env {env_id} not found!")
return False
self.connect_to_environment(remote_env,_node.get("event2msg"))
sub_workflows = config.get("sub_workflows")
if sub_workflows is not None:
if self._load_sub_workflows(sub_workflows) is False:
logger.error("Workflow load sub workflows failed")
return False
return True
def _load_env_from_config(self,config:dict) -> bool:
@@ -147,7 +147,7 @@ class Workflow:
return False
self.sub_workflows[k] = sub_workflow
return True
def _parse_msg_target(self,s:str)->list[str]:
return s.split(".")
@@ -170,12 +170,12 @@ class Workflow:
if current_workflow is None:
logger.error(f"sub workflow {inner_obj_id[i]} not found!")
return None
i += 1
logger.error(f"{msg.target} not found! forword message failed!")
return None
def get_workflow_id_from_target(self,target:str) -> str:
target_list = target.split(".")
if len(target_list) == 0:
@@ -203,11 +203,11 @@ class Workflow:
#1. workflow start process message
final_result = None
# this is workflow's group_chat session
session_topic = msg.sender + "#" + msg.topic
chatsesssion = AIChatSession.get_session(self.workflow_id,session_topic,self.db_file)
#2. find role by msg.mentions or workflow's selector logic
if msg.mentions is not None:
if not self.workflow_id in msg.mentions:
@@ -219,20 +219,20 @@ class Workflow:
this_role = self.role_group.get(mention)
if this_role is not None:
return await self.role_process_msg(msg,this_role,chatsesssion)
if self.input_filter is not None:
select_role_id = self.input_filter.select(msg)
if select_role_id is not None:
if select_role_id is not None:
select_role = self.role_group.get(select_role_id)
if select_role is None:
logger.error(f"input_filter return invalid role id:{select_role_id}, role not found in role_group")
return None
return await self.role_process_msg(msg,select_role,chatsesssion)
else:
logger.error(f"input_filter return None for :{msg.body}")
return None
logger.error(f"{self.workflow_id}:no role can process this msg:{msg.body}")
return final_result
@@ -245,7 +245,7 @@ class Workflow:
if llm_result_str == "ignore":
r.state = "ignore"
return r
lines = llm_result_str.splitlines()
is_need_wait = False
@@ -262,7 +262,7 @@ class Workflow:
r.send_msgs.append(new_msg)
is_need_wait = True
case "post_msg":# postmsg($target_id,$msg_content)
if len(func_args) != 1:
logger.error(f"parse postmsg failed! {func_call}")
@@ -272,22 +272,22 @@ class Workflow:
msg_content = func_item.body
new_msg.set("_",target_id,msg_content)
r.post_msgs.append(new_msg)
case "call":# call($func_name,$args_str)
r.calls.append(func_item)
is_need_wait = True
return True
case "post_call": # post_call($func_name,$args_str)
r.post_calls.append(func_item)
return True
return True
current_func : FunctionItem = None
for line in lines:
if line.startswith("##/"):
if current_func:
if check_args(current_func) is False:
r.resp += current_func.dumps()
func_name,func_args = AgentMsg.parse_function_call(line[3:])
current_func = FunctionItem(func_name,func_args)
else:
@@ -295,7 +295,7 @@ class Workflow:
current_func.append_body(line + "\n")
else:
r.resp += line + "\n"
if current_func:
if check_args(current_func) is False:
r.resp += current_func.dumps()
@@ -309,14 +309,14 @@ class Workflow:
async def role_post_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
msg.sender = the_role.get_role_id()
target_role = self.role_group.get(msg.target)
if target_role:
msg.target = target_role.get_role_id()
logger.info(f"{msg.sender} post message {msg.msg_id} to inner role: {msg.target}")
asyncio.create_task(self.role_process_msg(msg,target_role,workflow_chat_session))
return
target_workflow = self.sub_workflows.get(msg.target)
if target_workflow:
msg.target = target_workflow.workflow_id
@@ -341,7 +341,7 @@ class Workflow:
# msg.target = target_workflow.workflow_id
logger.info(f"{msg.sender} send message {msg.msg_id} to sub workflow: {msg.target}")
return await target_workflow._process_msg(msg)
logger.info(f"{msg.sender} post message {msg.msg_id} to AIBus: {msg.target}")
return await self.get_bus().send_message(msg)
@@ -352,8 +352,8 @@ class Workflow:
func_node : AIFunction = self.workflow_env.get_ai_function(func_item.name)
if func_node is None:
return "execute failed,function not found"
result_str:str = await func_node.execute(**arguments)
result_str:str = await func_node.execute(**arguments)
return result_str
async def role_post_call(self,func_item:FunctionItem,the_role:AIRole):
@@ -363,7 +363,7 @@ class Workflow:
def _format_msg_by_env_value(self,prompt:AgentPrompt):
if self.workflow_env is None:
return
for msg in prompt.messages:
old_content = msg.get("content")
msg["content"] = old_content.format_map(self.workflow_env)
@@ -372,15 +372,17 @@ class Workflow:
all_inner_function = self.workflow_env.get_all_ai_functions()
if all_inner_function is None:
return None
result_func = []
for inner_func in all_inner_function:
func_name = inner_func.get_name()
if the_role.enable_function_list:
if the_role.enable_function_list is not None:
if len(the_role.enable_function_list) > 0:
if func_name not in the_role.enable_function_list:
logger.debug(f"ageint {self.agent_id} ignore inner func:{func_name}")
logger.debug(f"agent {self.agent_id} ignore inner func:{func_name}")
continue
else:
continue
this_func = {}
this_func["name"] = func_name
this_func["description"] = inner_func.get_description()
@@ -399,17 +401,17 @@ class Workflow:
func_node : AIFunction = self.workflow_env.get_ai_function(func_name)
if func_node is None:
return "execute failed,function not found"
ineternal_call_record = AgentMsg.create_internal_call_msg(func_name,arguments,org_msg.get_msg_id(),org_msg.target)
result_str:str = await func_node.execute(**arguments)
inner_functions = self._get_inner_functions()
inner_functions = self._get_inner_functions(the_role)
prompt.messages.append({"role":"function","content":result_str,"name":func_name})
task_result:ComputeTaskResult = await ComputeKernel.get_instance().do_llm_completion(prompt,
the_role.agent.llm_model_name,the_role.agent.max_token_size,
inner_functions)
ineternal_call_record.result_str = task_result.result_str
ineternal_call_record.done_time = time.time()
org_msg.inner_call_chain.append(ineternal_call_record)
@@ -419,13 +421,13 @@ class Workflow:
return await self._role_execute_func(the_role,inner_func_call_node,prompt,org_msg,stack_limit-1)
else:
return task_result.result_str
def _is_in_same_workflow(self,msg) -> bool:
pass
async def role_process_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
async def role_process_msg(self,msg:AgentMsg,the_role:AIRole,workflow_chat_session:AIChatSession):
msg.target = the_role.get_role_id()
prompt = AgentPrompt()
prompt.append(the_role.agent.prompt)
@@ -433,7 +435,7 @@ class Workflow:
prompt.append(the_role.get_prompt())
# prompt.append(self._get_function_prompt(the_role.get_name()))
# prompt.append(self._get_knowlege_prompt(the_role.get_name()))
#support group chat, user content include sender name!
prompt.append(await self._get_prompt_from_session(workflow_chat_session))
@@ -443,15 +445,15 @@ class Workflow:
self._format_msg_by_env_value(prompt)
inner_functions = self._get_inner_functions(the_role)
async def _do_process_msg():
#TODO: send msg to agent might be better?
task_result:ComputeTaskResult = await ComputeKernel.get_instance().do_llm_completion(prompt,the_role.agent.get_llm_model_name(),the_role.agent.get_max_token_size(),inner_functions)
result_str = task_result.result_str
logger.info(f"{the_role.role_id} process {msg.sender}:{msg.body},llm str is :{result_str}")
inner_func_call_node = task_result.result_message.get("function_call")
if inner_func_call_node:
#TODO to save more token ,can i use msg_prompt?
result_str = await self._role_execute_func(the_role,inner_func_call_node,prompt,msg)
@@ -461,7 +463,7 @@ class Workflow:
postmsg.prev_msg_id = msg.get_msg_id()
# might be craete a new msg.topic for this postmsg
postmsg.topic = msg.topic
await self.role_post_msg(postmsg,the_role,workflow_chat_session)
if not self._is_in_same_workflow(postmsg):
role_sesion = AIChatSession.get_session(the_role.get_role_id(),f"{postmsg.target}#{msg.topic}",self.db_file)
@@ -469,14 +471,14 @@ class Workflow:
else:
# message will be saved in role.process_message
pass
for post_call in result.post_calls:
action_msg = msg.create_action_msg(post_call[0],post_call[1],the_role.get_role_id())
workflow_chat_session.append(action_msg)
await self.role_post_call(post_call,the_role)
#save post_call
result_prompt_str = ""
match result.state:
case "ignore":
@@ -506,11 +508,11 @@ class Workflow:
else:
# message will be saved in role.process_message
pass
for call in result.calls:
action_msg = msg.create_action_msg(call[0],call[1],call_result,the_role.get_role_id)
call_result = await self.role_call(call,the_role)
if call_result is not None:
result_prompt_str += f"\ncall {call[0]} result is :{call_result}"
#save action
@@ -522,7 +524,7 @@ class Workflow:
prompt.append(result_prompt)
r = await _do_process_msg()
return r
return await _do_process_msg()
async def _get_prompt_from_session(self,chatsession:AIChatSession) -> AgentPrompt:
@@ -533,9 +535,9 @@ class Workflow:
result_prompt.messages.append({"role":"assistant","content":msg.body})
else:
result_prompt.messages.append({"role":"user","content":f"{msg.body}"})
return result_prompt
def _get_knowlege_prompt(self,role_name:str) -> AgentPrompt:
pass
@@ -557,7 +559,7 @@ class Workflow:
# if k == "role":
# continue
# else:
#
#
# def _env_msg_handler(env_event:EnvironmentEvent) -> None:
# the_msg:AgentMsg= self._env_event_to_msg(env_event)
# self.role_post_msg
src/aios_kernel/workflow_env.py
+24 -21
View File
@@ -7,6 +7,8 @@ from sqlite3 import Error
import threading
import logging
from typing import Optional
from .text_to_speech_function import TextToSpeechFunction
from .environment import Environment,EnvironmentEvent
from .ai_function import SimpleAIFunction
from .storage import AIStorage
@@ -23,8 +25,8 @@ class CalenderEvent(EnvironmentEvent):
self.data = data
def display(self) -> str:
return f"#event timer:{self.data}"
return f"#event timer:{self.data}"
# AI Calender GOAL: Let user use "create notify after 2 days" to create a timer event
class CalenderEnvironment(Environment):
def __init__(self, env_id: str) -> None:
@@ -39,7 +41,7 @@ class CalenderEnvironment(Environment):
#self.add_ai_function(SimpleAIFunction("serach_events",
# "search events in calender",
# self._search_events))
get_param = {
"start_time": "start time (UTC) of event",
"end_time": "end time (UTC) of event"
@@ -59,14 +61,14 @@ class CalenderEnvironment(Environment):
self.add_ai_function(SimpleAIFunction("add_event",
"add event to calender",
self._add_event,add_param))
delete_param = {
"event_id": "id of event"
}
self.add_ai_function(SimpleAIFunction("delete_event",
"delete event from calender",
self._delete_event,delete_param))
update_param = {
"event_id": "id of event",
"new_title": "new title of event",
@@ -79,7 +81,7 @@ class CalenderEnvironment(Environment):
self.add_ai_function(SimpleAIFunction("update_event",
"update event in calender",
self._update_event,update_param))
#self.add_ai_function(SimpleAIFunction("user_confirm",
# "user confirm",
# self._user_confirm))
@@ -98,7 +100,7 @@ class CalenderEnvironment(Environment):
);
""")
await db.commit()
async def _add_event(self,title, start_time, end_time, participants=None, location=None, details=None):
async with aiosqlite.connect(self.db_file) as db:
await db.execute("""
@@ -127,7 +129,7 @@ class CalenderEnvironment(Environment):
_event["details"] = row[6]
result[row[0]] = _event
return json.dumps(result, indent=4, sort_keys=True)
async def _get_events_by_time_range(self,start_time, end_time):
async with aiosqlite.connect(self.db_file) as db:
cursor = await db.execute("""
@@ -153,7 +155,7 @@ class CalenderEnvironment(Environment):
return "No event."
return json.dumps(result, indent=4, sort_keys=True)
async def _update_event(self,event_id, new_title=None, new_participants=None, new_location=None, new_details=None ,start_time=None, end_time=None):
fields_to_update = []
values = []
@@ -191,8 +193,8 @@ class CalenderEnvironment(Environment):
WHERE id = ?;
"""
values.append(event_id)
values.append(event_id)
async with aiosqlite.connect(self.db_file) as db:
await db.execute(sql_update_query, values)
await db.commit()
@@ -212,16 +214,16 @@ class CalenderEnvironment(Environment):
async def start(self) -> None:
if self.is_run:
return
return
self.is_run = True
await self.init_db()
self.register_get_handler("now",self.get_now)
async def timer_loop():
while True:
if self.is_run == False:
break
await asyncio.sleep(1.0)
now = datetime.now()
formatted_time = now.strftime('%Y-%m-%d %H:%M:%S')
@@ -238,13 +240,13 @@ class CalenderEnvironment(Environment):
def get_now(self)->str:
now = datetime.now()
formatted_time = now.strftime('%Y-%m-%d %H:%M:%S')
return formatted_time
return formatted_time
async def _get_now(self) -> str:
now = datetime.now()
formatted_time = now.strftime('%Y-%m-%d %H:%M:%S')
return formatted_time
# Default Workflow Environment(Context)
class WorkflowEnvironment(Environment):
def __init__(self, env_id: str,db_file:str) -> None:
@@ -252,6 +254,7 @@ class WorkflowEnvironment(Environment):
self.db_file = db_file
self.local = threading.local()
self.table_name = "WorkflowEnv_" + env_id
self.add_ai_function(TextToSpeechFunction())
def _get_conn(self):
@@ -259,7 +262,7 @@ class WorkflowEnvironment(Environment):
if not hasattr(self.local, 'conn'):
self.local.conn = self._create_connection()
return self.local.conn
def _create_connection(self):
""" create a database connection to a SQLite database """
conn = None
@@ -273,10 +276,10 @@ class WorkflowEnvironment(Environment):
self._create_table(conn)
return conn
def close(self):
if not hasattr(self.local, 'conn'):
return
return
self.local.conn.close()
def _create_table(self, conn):
@@ -293,7 +296,7 @@ class WorkflowEnvironment(Environment):
conn.commit()
except Error as e:
logging.error("Error occurred while creating tables: %s", e)
def _do_get_value(self, key: str) -> str | None:
try:
conn = self._get_conn()
@@ -311,7 +314,7 @@ class WorkflowEnvironment(Environment):
super().set_value(key,str_value)
if is_storage is False:
return
try:
conn = self._get_conn()
conn.execute("""
src/service/aios_shell/aios_shell.py
+55 -44
View File
@@ -59,6 +59,9 @@ class AIOS_Shell:
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()
async def _handle_no_target_msg(self,bus:AIBus,msg:AgentMsg) -> bool:
target_id = msg.target.split(".")[0]
@@ -66,14 +69,14 @@ class AIOS_Shell:
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:
@@ -98,7 +101,15 @@ class AIOS_Shell:
logger.error("openai node initial failed!")
return False
ComputeKernel.get_instance().add_compute_node(open_ai_node)
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}")
return False
llama_ai_node = LocalLlama_ComputeNode()
await llama_ai_node.start()
# ComputeKernel.get_instance().add_compute_node(llama_ai_node)
@@ -115,19 +126,19 @@ class AIOS_Shell:
contact_config_path =os.path.abspath(f"{user_data_dir}/contacts.toml")
cm = ContactManager.get_instance(contact_config_path)
cm.load_data()
tunnels_config_path = os.path.abspath(f"{user_data_dir}/etc/tunnels.cfg.toml")
tunnel_config = None
try:
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!")
KnowledgePipline.get_instance().initial()
return True
return True
def get_version(self) -> str:
return "0.5.1"
@@ -158,25 +169,25 @@ class AIOS_Shell:
case "email":
tunnel_config["type"] = "EmailTunnel"
case _:
error_text = FormattedText([("class:error", f"tunnel type {tunnel_type}not support!")])
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)])
intro_text = FormattedText([("class:prompt", tunnel_introduce)])
print_formatted_text(intro_text,style=shell_style)
for key,item in intpu_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
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")
try:
try:
all_tunnels = toml.load(tunnels_config_path)
if all_tunnels is not None:
all_tunnels[tunnel_config["tunnel_id"]] = tunnel_config
@@ -234,7 +245,7 @@ class AIOS_Shell:
prompt.messages.append({"role": "user", "content":" ".join(args[1:])})
result = await KnowledgeBase().query_prompt(prompt)
print_formatted_text(result.as_str())
async def call_func(self,func_name, args):
match func_name:
case 'send':
@@ -251,13 +262,13 @@ class AIOS_Shell:
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!")])
return show_text
case 'connect':
show_text = FormattedText([("class:title", "args error, /connect $target telegram | email")])
@@ -295,8 +306,8 @@ class AIOS_Shell:
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!"
return self.username + " login success!"
case 'history':
num = 10
offset = 0
@@ -326,9 +337,9 @@ class AIOS_Shell:
return FormattedText([("class:title", f"help~~~")])
##########################################################################################################################
##########################################################################################################################
history = FileHistory('aios_shell_history.txt')
session = PromptSession(history=history)
session = PromptSession(history=history)
def parse_function_call(func_string):
if len(func_string) > 2:
@@ -339,7 +350,7 @@ def parse_function_call(func_string):
return func_name, params
else:
return None
async def try_get_input(desc:str,check_func:callable = None) -> str:
user_input = await session.prompt_async(f"{desc} \nType /exit to abort. \nPlease input:",style=shell_style)
err_str = ""
@@ -349,13 +360,13 @@ async def try_get_input(desc:str,check_func:callable = None) -> str:
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)])
error_text = FormattedText([("class:error", err_str)])
print_formatted_text(error_text,style=shell_style)
return await try_get_input(desc,check_func)
@@ -375,7 +386,7 @@ async def main_daemon_loop(shell:AIOS_Shell):
return 0
def print_welcome_screen():
print("\033[1;31m")
print("\033[1;31m")
logo = """
\t _______ ____________________ __
\t __ __ \______________________ __ \__ |__ | / /
@@ -386,9 +397,9 @@ def print_welcome_screen():
"""
print(logo)
print("\033[0m")
print("\033[0m")
print("\033[1;32m \t\tWelcome to OpenDAN - Your Personal AI OS\033[0m\n")
print("\033[1;32m \t\tWelcome to OpenDAN - Your Personal AI OS\033[0m\n")
introduce = """
\tThe core goal of version 0.5.1 is to turn the concept of AIOS into code and get it up and running as quickly as possible.
@@ -398,12 +409,12 @@ def print_welcome_screen():
\twe intend to strengthen some components. This document will explain these changes and provide an update
\ton the current development progress of MVP(0.5.1,0.5.2)
"""
"""
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(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")
@@ -414,19 +425,19 @@ async def main():
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')
if os.path.isdir(f"{directory}/../../../rootfs"):
AIStorage.get_instance().is_dev_mode = True
else:
AIStorage.get_instance().is_dev_mode = False
AIStorage.get_instance().is_dev_mode = False
is_daemon = False
if os.name != 'nt':
if os.getppid() == 1:
is_daemon = True
shell = AIOS_Shell("user")
shell.declare_all_user_config()
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:
@@ -437,7 +448,7 @@ async def main():
#Remind users to enter necessary configurations.
if await get_user_config_from_input(check_result) is False:
return 1
init_result = await shell.initial()
if init_result is False:
if is_daemon:
@@ -453,18 +464,18 @@ async def main():
proxy.apply_storage()
#TODO: read last input config
completer = WordCompleter(['/send $target $msg $topic',
'/open $target $topic',
completer = WordCompleter(['/send $target $msg $topic',
'/open $target $topic',
'/history $num $offset',
'/login $username',
'/connect $target',
'/knowledge add email | dir',
'/knowledge add email | dir',
'/knowledge journal [$topn]',
'/knowledge query $query'
'/set_config $key',
'/list_config',
'/show',
'/exit',
'/exit',
'/help'], ignore_case=True)
current = AIStorage.get_instance().get_user_config().get_value("shell.current")
@@ -472,7 +483,7 @@ async def main():
shell.current_target = current[1]
shell.current_topic = current[0]
await asyncio.sleep(0.2)
await asyncio.sleep(0.2)
while True:
user_input = await session.prompt_async(f"{shell.username}<->{shell.current_topic}@{shell.current_target}$ ",completer=completer,style=shell_style)
if len(user_input) <= 1:
@@ -493,6 +504,6 @@ async def main():
#print_formatted_text(f"{shell.username}<->{shell.current_topic}@{shell.current_target} >>> {resp}",style=shell_style)
if __name__ == "__main__":
if __name__ == "__main__":
asyncio.run(main())