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H<1_d#PNNSt literal 0 HcmV?d00001 diff --git a/agent/agent.py b/agent/agent_base.py similarity index 98% rename from agent/agent.py rename to agent/agent_base.py index 2e44ea0..55daf03 100644 --- a/agent/agent.py +++ b/agent/agent_base.py @@ -2,7 +2,7 @@ import openai import yaml -class Agent: +class AgentBase: def __init__(self, role): """ Initialize an Agent object. diff --git a/agent/manager_agent.py b/agent/manager_agent.py index 0f63727..4cc7c8c 100644 --- a/agent/manager_agent.py +++ b/agent/manager_agent.py @@ -1,24 +1,27 @@ -from agent.agent import Agent +import json +from agent.agent_base import AgentBase from work_principle.okr_principle import OKR_Object - -class ManagerAgent(Agent): +import logging +logging.basicConfig(level=logging.INFO) +class ManagerAgent(AgentBase): def __init__(self): super().__init__("你是一名总经理，负责对任务进行可量化的评估") + self.logger = logging.getLogger(__name__) - def optimization_Object(self, object:OKR_Object): - object.content # todo 待加入 PDCA循环规则 # 利用 smart 原则对目标进行评估 - for i in object.five_w_two_h.content: - r = self.call_gpt(f"你觉得'{object.content}'，说清楚了{i['descriptions']}吗？如果说清楚，返回{i}否则返回'no'") - if r == "no": - input(f"请说清楚'{object.content}'的{i}，按回车键继续") - else: - i['content'] = r - - - - for k, v in object.smart.items(): - self.call_gpt(f"你觉得'{object.content}'这个目标，就{k}来说满分是3分可以打几分，只返回给1或2或3，比如2") + for k,i in object.five_w_two_h.content.items(): + r = {'是否具备': 'no'} + content = object.content + while r["是否具备"]=="no" : + prompt = f"这是一个任务描述:'{content}'。你觉得这个任务描述具备{i['descriptions']}吗？如果具备返回格式如下：{{'是否具备': 'yes'}}，如果不具备返回格式如下：{{'是否具备': 'no', '原因': '返回具体原因即可'}}" + self.logger.info(prompt) + call_openai = self.call_gpt(prompt) + self.logger.info(call_openai) + r = json.loads(call_openai) + if r["是否具备"]=="no": + content = input(f"您的任务描述不清楚，{r['原因']}：") + i['content'] = content + self.logger.info(str(object.five_w_two_h.content)) diff --git a/agent/plan_agent.py b/agent/plan_agent.py index e89d280..bd41575 100644 --- a/agent/plan_agent.py +++ b/agent/plan_agent.py @@ -1,5 +1,5 @@ -from agent.agent import Agent +from agent.agent_base import AgentBase -class WokerAgent(Agent): +class WokerAgent(AgentBase): def __init__(self): super().__init__("你是一名计划拆解者，负责对OKR中的O进行拆解并制定KR，向总经理汇报") diff --git a/agent/woker_agent.py b/agent/woker_agent.py index d18255d..f526b04 100644 --- a/agent/woker_agent.py +++ b/agent/woker_agent.py @@ -1,5 +1,5 @@ -from agent.agent import Agent +from agent.agent_base import AgentBase -class WokerAgent(Agent): +class WokerAgent(AgentBase): def __init__(self): super().__init__("你是一名工作者，负责执行OKR中的KR，向总计划制定者汇报") diff --git a/main.py b/main.py index 100b43d..8b99bd0 100644 --- a/main.py +++ b/main.py @@ -1,6 +1,5 @@ - from agent.manager_agent import ManagerAgent -from work_principle.okr_principle import OKR +from work_principle.okr_principle import OKR_Object class AutoMate: @@ -9,10 +8,9 @@ class AutoMate: def rule_define(self): - o_kr = OKR() - o_kr.set_objective(input("请输入任务: ")) - ManagerAgent().call_gpt(o_kr) - + # o_kr = OKR_Object(input("请输入任务: ")) + o_kr = OKR_Object("对比一下copilot和curson谁更好用") + ManagerAgent().optimization_Object(o_kr) diff --git a/work_principle/__pycache__/five_w_two_h.cpython-39.pyc b/work_principle/__pycache__/five_w_two_h.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..8f8a0126c8671635610ebe5f28e649de6b5afc5f GIT binary patch literal 622 zcmY*Xy=&V*6u*ymSd}x^#47LjR9jEj!7at#s%+t2OF_-}}1vd-w6qYcv)R$eZ(TY|B7sq=TxM z5Ih5jxE=u7??Fx-w5~E z>sL8{(R8qy6HI0z_Hm_~_G^IWfOG|v?nBLQ<@&q5>ByV-ae!`!B}QmbzxG(p)<$}OI1);$3I0m7`e&j0`b literal 0 HcmV?d00001 diff --git a/work_principle/__pycache__/okr_principle.cpython-39.pyc b/work_principle/__pycache__/okr_principle.cpython-39.pyc new file mode 100644 index 0000000000000000000000000000000000000000..b3d47e2b168fcbe09fe5fc847a9a3fcac3ce3ec1 GIT binary patch literal 2720 zcma)8&2QsG6rZu3#BtNzr7RV@g~fa-Mi3P(5>i!FMIb<0ZB}X*kfNfI>zTH096OzH zS{h|f-6KMRzo2`p_Fv#H@s-n_5aPy(_r|gF)k;h>FY{*Jym?>q8~e-44uSUa*O%h& zDj|O&Gu=#JwxO#}fN;WTM0&JCDfyOggPYF@H!qBi0i4Avz*T@Vd3Bd~wO6o%cr>ej z6P}76pPnV(1voR^3}CjQtIvT5(xIGm3{JW6oPZXSTksEhc@_REyvA+#ukt!~;J?O~ z;FLz@JbARkp6nlsAPrDo(Qu6YE9mM0kP#gbMh*#3%5iL@<^^&VC%fdzXiExGUL~sq zNt}u}&6c|2oJpYuQK~Y#FOx%Hltisr;{d#3XDmHS*pX*smJ-o{tiaM0kr>l|9|jwH zT%3w1>F@c2G?K_};adIk%w{Z%!;~@9q--FBR`qZA`oz&z zA+_K!=1Y5g9|j|GOfKn&zJPp<=%q0tIMUwIwr5I6ILWGhzb|5*Eh~|-M8^?4^9)(X zRc8_c?Nv^eaOsxMIh!owoU(ur+MvUGQ^wB91sLU`VJJ(Jw}Hu%kA{CuF6c9w(!2~t z6!{A(KjsxoUA&T-Bj8gD=^CcdK*zjl``QC`LAP1~g8Bc+c?MBACchac)^46HkIEXX zLL!aUddKL>d2gM~C{$^X^!i(OK=2>vWZ0VWa?t0HV8~`(C9TaU3H(TH!Jyc9tz`-n zsZ}6g*DbV*ldkatq2vT^0yt#6;;`7(_CQw92W{%Sf%VNp5sRPua_cn|xeH|Y>Ho5? 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