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fix bugs.

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This commit is contained in:
Liu Zhicong
2024-01-25 21:48:17 -08:00
parent 9b7ca0b81a
commit c694ece59e
6 changed files with 44 additions and 28 deletions
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rootfs/agents/Jarvis/agent.toml
+6 -6
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@@ -8,7 +8,8 @@ enable_timestamp = "true"
enable_json_resp = "true"
role_desc = """
Your name is Jarvis, the super personal assistant to the master, The focus of work is the support of the schedule management and schedule affairs.
Your name is Jarvis, the super personal assistant to the master. Help the Master do a good job of schedule.Reminder before the start of the important schedule, and you should bring useful information as much as possible when reminding.
Only clearly specifying the task you completed can be completed independently.
"""
[behavior.on_message]
@@ -72,13 +73,12 @@ context="Your master is {owner}, now in {location}, time: {now}, weather: {weath
llm_context.actions.enable = ["agent.workspace.confirm_task","agent.workspace.update_task","agent.workspace.cancel_task","post_message"]
[behavior.plan_task]
## 首次处理任务
## 处理任务 Tackling Task
type="AgentPlanTask"
# 是否要加入对任务到期时间的关注？
process_description="""
The input is a task comes from a Tasklist. You need to perform a PLAN. PLAN process on TASK in combination with the known information.
The input is a task comes from a Tasklist. You are Tackling this task. Tackling process in combination with the known information.
1. Carefully think about whether the task is within your ability, and the task other than the scope of ability is directly rejected. (cancel_task).
2. Immediately perform a simple (similar to reminding one category) task. Send a message using post_message, then set the task to complete.(use update_task).
2. Immediately DO a simple (similar to reminding one category) task. Reminds at a reasonable time, Post a message using post_message, then set the task to complete.(use update_task).
3. Plan for non-simple tasks, and generate a TODO list. Every TODO MUST be an independent work with a clear goal. (set_todos)
4. If the task has been dealt with, it means that the task is ultimately completed.You need to analyze the processing report of the entire task and make new plans.
"""
@@ -86,7 +86,7 @@ The input is a task comes from a Tasklist. You need to perform a PLAN. PLAN proc
reply_format = """
The Response must be directly parsed by `python json.loads`. Here is an example:
{
think:'$think step-by-step to be sure you have the right plan.',
think:'$thinking step by step to ensure the accurate and efficient processing task.',
resp:'$determine, summary what you do'
actions: [{
name: '$action_name',
src/aios/agent/agent.py
+11 -2
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@@ -384,8 +384,8 @@ class AIAgent(BaseAIAgent):
logger.warning(f"agent {self.agent_id} is already wake up!")
async def _on_timer(self):
while True:
await asyncio.sleep(5)
while True:
try:
now = time.time()
if self.last_recover_time is None:
@@ -394,12 +394,18 @@ class AIAgent(BaseAIAgent):
if now - self.last_recover_time > 60:
self.agent_energy += (now - self.last_recover_time) / 60
self.last_recover_time = now
logger.info(f"agent {self.agent_id} recover energy to {self.agent_energy}")
if self.agent_energy <= 1:
logger.info(f"agent {self.agent_id} energy is too low!, goto sleep!")
continue
await self.llm_triage_tasklist()
task_list:List[AgentTask] = await self.prviate_workspace.task_mgr.list_task()
# Get un finished tasks
#filter = {}
#filter["state"] = AgentTaskState.TASK_STATE_WAIT
filter = None
task_list:List[AgentTask] = await self.prviate_workspace.task_mgr.list_task(filter)
for task in task_list:
if self.agent_energy <= 0:
@@ -445,6 +451,9 @@ class AIAgent(BaseAIAgent):
logger.error(f"agent {self.agent_id} on timer error:{e},{tb_str}")
continue
# Because the LLM itself is very slow, the accuracy of the system processing task is in minutes.
await asyncio.sleep(30)
src/aios/agent/llm_do_task.py
+1 -1
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@@ -155,7 +155,7 @@ class AgentPlanTask(LLMAgentBaseProcess):
logger.error(f"execute action failed! {e}")
result_str = "execute action failed!,error:" + str(e)
worklog = AgentWorkLog.create_by_content(agent_task.task_id,"plan",llm_result.resp,self.memory.agent_id)
worklog = AgentWorkLog.create_by_content(agent_task.task_id,"tackling",llm_result.resp,self.memory.agent_id)
worklog.result = result_str
await self.memory.append_worklog(worklog)
src/aios/agent/workspace.py
+4 -2
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@@ -288,6 +288,7 @@ class LocalAgentTaskManger(AgentTaskManager):
continue
task_item = await self._get_task_by_fullpath(entry.path)
if task_item:
if filter is None:
if task_item.is_finish():
continue
@@ -516,7 +517,8 @@ class AgentWorkspace:
"title" : {"type": "string", "description": "task title,Simple and clear, try to include the task \ Related personnel \ place \ key conditions \ time element involved in the event"},
"detail" : {"type": "string", "description": "task detail(simple task can not be filled)"},
"priority" : {"type": "int", "description": "task priority from 1-10"},
"due_date" : {"type": "isoformat time string", "description": "task due date"},
#"due_date": {"type": "isoformat time string", "description": "optional,confirm task due date"},
#"expiration_time": {"type": "isoformat time string", "description": "optional,confirm task expiration time"},
"parent": {"type": "string", "description": "optional,parent task id"},
})
create_task_action = SimpleAIFunction(
@@ -573,8 +575,8 @@ class AgentWorkspace:
return "confirm task ok"
parameters = ParameterDefine.create_parameters({
"task_id": {"type": "string", "description": "task id which want to confirm"},
"expiration_time": {"type": "isoformat time string", "description": "optional,confirm task expiration time"},
"next_attention_time": {"type": "isoformat time string", "description": "optional,confirm task next attention time"},
"expiration_time": {"type": "isoformat time string", "description": "optional,confirm task expiration time"},
#"due_date": {"type": "isoformat time string", "description": "optional,confirm task due date"},
"priority": {"type": "int", "description": "optional,task priority from 1-10"},
})
src/aios/proto/agent_task.py
+9 -5
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@@ -325,17 +325,16 @@ class AgentTask:
return False
def can_plan(self) -> bool:
if self.state == AgentTaskState.TASK_STATE_CONFIRMED:
return True
if self.state == AgentTaskState.TASK_STATE_CHECKFAILED:
return True
if self.state == AgentTaskState.TASK_STATE_CONFIRMED or self.state == AgentTaskState.TASK_STATE_CHECKFAILED:
if self.next_attention_time:
try:
next_attention_time = datetime.fromisoformat(self.next_attention_time).timestamp()
if next_attention_time >= time.time():
if time.time() >= next_attention_time:
return True
except Exception as e:
logger.warning(f"invalid next_attention_time {self.next_attention_time}")
else:
return True
return False
@@ -344,9 +343,14 @@ class AgentTask:
result["task_id"] = self.task_id
result["title"] = self.title
result["priority"] = self.priority
result["detail"] = self.detail
result["create_time"] = self.create_time
if self.due_date:
result["due_date"] = self.due_date
if self.expiration_time:
result["expiration_time"] = self.expiration_time
if self.next_attention_time:
result["next_attention_time"] = self.next_attention_time
return result
src/service/aios_shell/aios_shell.py
+2 -1
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@@ -19,7 +19,7 @@ from prompt_toolkit.auto_suggest import AutoSuggestFromHistory
from prompt_toolkit.completion import WordCompleter
from prompt_toolkit.styles import Style
from slack_tunnel import SlackTunnel
directory = os.path.dirname(__file__)
sys.path.append(directory + '/../../')
@@ -46,6 +46,7 @@ from knowledge_manager import KnowledgePipelineManager
from tg_tunnel import TelegramTunnel
from email_tunnel import EmailTunnel
from discord_tunnel import DiscordTunnel
from slack_tunnel import SlackTunnel
from common_environment import LocalKnowledgeBase, FilesystemEnvironment, ShellEnvironment, ScanLocalDocument, ParseLocalDocument
from compute_node_config import *