init st_game structure

examples/st_game/README.md

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+## Stanford Town Game
+
+执行入口为：`python3 run_st_game.py "Host a activity"`   
+
+`idea`为用户给第一个Agent的用户心声，并通过这个心声进行传播，看最后多智能体是否达到举办、参加活动的目标。  

examples/st_game/actions/summarize_conv.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : summarize the content of agents' conversation
+
+from metagpt.actions.action import Action
+from metagpt.schema import Message
+
+
+class SummarizeConv(Action):
+
+    def __init__(self, name="SummarizeConv", context: list[Message] = None, llm=None):
+        super().__init__(name, context, llm)

examples/st_game/actions/user_requirement.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   :
+
+from metagpt.actions import Action
+
+
+class UserRequirement(Action):
+
+    async def run(self, *args, **kwargs):
+        raise NotImplementedError

examples/st_game/maze_environment.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : maze environment
+
+from metagpt.environment import Environment
+
+
+class MazeEnvironment(Environment):
+
+    pass

examples/st_game/memory/associative_memory.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : associative_memory to store conversation、plan detail、reflection result and so on.
+
+from metagpt.memory.memory import Memory
+
+
+class AssociativeMemory(Memory):
+    pass

examples/st_game/plan/st_plan.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : st' planning execution

examples/st_game/reflect/st_reflect.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : st's reflection execution

examples/st_game/roles/st_role.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : Stanford Town role
+
+"""
+Do the steps following:
+- perceive, receive environment(Maze) info
+- retrieve, retrieve memories
+- plan, do plan like long-term plan and interact with Maze
+- reflect, do the High-level thinking based on memories and re-add into the memory
+- execute, move or else in the Maze
+"""
+
+from pydantic import Field
+from pathlib import Path
+
+from metagpt.roles.role import Role, RoleContext
+
+from ..memory.associative_memory import AssociativeMemory
+
+
+class STRoleContext(RoleContext):
+
+    memory: AssociativeMemory = Field(default=AssociativeMemory)
+
+
+class STRole(Role):
+
+    # add a role's property structure to store role's age and so on like GA's Scratch.
+
+    def __init__(self, name="", profile=""):
+        self._rc = STRoleContext()
+
+    def load_from(self, folder: Path):
+        """
+        load role data from `storage/{simulation_name}/personas/{role_name}
+        """
+        pass
+
+    def save_into(self, folder: Path):
+        """
+        save role data from `storage/{simulation_name}/personas/{role_name}
+        """
+        pass

examples/st_game/run_st_game.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : entry of Stanford Town(ST/st) game
+
+import asyncio
+import fire
+
+from stanford_town import StanfordTown
+from roles.st_role import STRole
+
+
+async def startup(idea: str,
+                  investment: float = 30.0,
+                  n_round: int = 500):
+
+    # get role names from `storage/{simulation_name}/reverie/meta.json` and then init roles
+    roles = []
+    # TODO
+
+    town = StanfordTown()
+    town.wakeup_roles(roles)
+
+    town.invest(investment)
+    town.start_project()
+
+    await town.run(n_round)
+
+
+def main(idea: str,
+         investment: float = 30.0,
+         n_round: int = 500):
+    """
+    idea works as an `inner voice` to the first agent.
+    """
+
+    asyncio.run(startup(idea=idea,
+                        investment=investment,
+                        n_round=n_round))
+
+
+if __name__ == "__main__":
+    fire.Fire(main)

examples/st_game/stanford_town.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : StanfordTown to works like SoftwareCompany
+
+from pydantic import Field
+
+from metagpt.software_company import SoftwareCompany
+from metagpt.roles.role import Role
+from metagpt.schema import Message
+
+from maze_environment import MazeEnvironment
+from actions.user_requirement import UserRequirement
+
+
+class StanfordTown(SoftwareCompany):
+
+    environment: MazeEnvironment = Field(default_factory=MazeEnvironment)
+
+    def wakeup_roles(self, roles: list[Role]):
+        self.environment.add_roles(roles)
+
+    def start_project(self, idea):
+        self.environment.publish_message(
+            Message(role="User", content=idea, cause_by=UserRequirement)
+        )

examples/st_game/storage/.gitignore

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+# path to store simulation data

examples/st_game/utils/const.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   :
+
+from pathlib import Path
+
+ROOT_PATH = Path(__file__).parent.parent
+STORAGE_PATH = ROOT_PATH.joinpath("storage")

examples/st_game/utils/mg_ga_transform.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : data transform of mg <-> ga under storage

metagpt/plan/__init__.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : plan module

metagpt/plan/plan.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : base class of planning

metagpt/reflect/__init__.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : reflection module

metagpt/reflect/reflect.py

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+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+# @Desc   : base class of reflection