new

agent/agent_base.py

@@ -2,7 +2,7 @@ import openai
 import yaml
 
 
-class Agent:
+class AgentBase:
     def __init__(self, role):
         """
         Initialize an Agent object.

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))

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")

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")

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)
 
 
 

work_principle/five_w_two_h.py

@@ -1,11 +1,8 @@
 class FiveWTwoH:
     def __init__(self) -> None:
         self.content = {
-            "who": {"content": "", "descriptions": "谁来做这个任务"},
-            "what": {"content": "", "descriptions": "这个任务是什么"},
-            "when": {"content": "", "descriptions": "什么时候完成这个任务"},
-            "where": {"content": "", "descriptions": "在哪里做这个任务"},
+            "what": {"content": "", "descriptions": "任务主体、动作、数量"},
             "why": {"content": "", "descriptions": "为什么要做这个任务"},
-            "how": {"content": "", "descriptions": "这个任务如何做"},
+            # "how": {"content": "", "descriptions": "这个任务如何做", "example": ["通过线上直播发布会，合作伙伴渠道和社交媒体宣传", "通过增加人员、改善流程和引入新的服务软件"]},
             "how_much": {"content": "", "descriptions": "这个任务要做成什么程度"}
-        }
+        }   

work_principle/okr_principle.py

@@ -1,13 +1,14 @@
-from work_principle.okr_principle import OKR_KeyResult
 from work_principle.five_w_two_h import FiveWTwoH
+
 class OKR_Object:
+
     def __init__(self, content):
         self.content = content
         self.key_results = []
         self.progress = 0
         self.five_w_two_h = FiveWTwoH()
 
-    def add_key_result(self, key_result:OKR_KeyResult):
+    def add_key_result(self, key_result):
         self.key_results.append(key_result)
         key_result.set_objective(self)