From 1545a702ccd4610c14acd818ae8fc6a19fd8d84d Mon Sep 17 00:00:00 2001
From: =?UTF-8?q?=E8=8E=98=E6=9D=83=20=E9=A9=AC?= <mashenquan@fuzhi.ai>
Date: Sat, 26 Aug 2023 22:28:41 +0800
Subject: [PATCH] fixbug: skill_yaml_file_name

---
 metagpt/actions/meta_action.py | 64 ----------------------------------
 metagpt/roles/assistant.py     |  5 ++-
 2 files changed, 4 insertions(+), 65 deletions(-)
 delete mode 100644 metagpt/actions/meta_action.py

diff --git a/metagpt/actions/meta_action.py b/metagpt/actions/meta_action.py
deleted file mode 100644
index 4c52e7cfd..000000000
--- a/metagpt/actions/meta_action.py
+++ /dev/null
@@ -1,64 +0,0 @@
-#!/usr/bin/env python
-# -*- coding: utf-8 -*-
-"""
-@Time    : 2023/8/7
-@Author  : mashenquan
-@File    : meta_action.py
-@Desc   : I am attempting to incorporate certain symbol concepts from UML into MetaGPT, enabling it to have the
-            ability to freely construct flows through symbol concatenation. Simultaneously, I am also striving to
-            make these symbols configurable and standardized, making the process of building flows more convenient.
-            For more about `fork` node in activity diagrams, see: `https://www.uml-diagrams.org/activity-diagrams.html`
-          This file defines a meta action capable of generating arbitrary actions at runtime based on a
-            configuration file.
-"""
-
-from typing import Type
-
-from metagpt.actions import Action
-from metagpt.logs import logger
-from metagpt.roles.uml_meta_role_options import MetaActionOptions
-from metagpt.schema import Message
-
-
-class MetaAction(Action):
-    def __init__(self, options, action_options: MetaActionOptions, llm=None, **kwargs):
-        super(MetaAction, self).__init__(options=options,
-                                         name=action_options.name,
-                                         context=kwargs.get("context"),
-                                         llm=llm)
-        self.prompt = action_options.format_prompt(**kwargs)
-        self.action_options = action_options
-        self.kwargs = kwargs
-
-    def __str__(self):
-        """Return `topic` value when str()"""
-        return self.action_options.topic
-
-    def __repr__(self):
-        """Show `topic` value when debug"""
-        return self.action_options.topic
-
-    async def run(self, messages, *args, **kwargs):
-        if len(messages) < 1 or not isinstance(messages[0], Message):
-            raise ValueError("Invalid args, a tuple of List[Message] is expected")
-
-        logger.debug(self.prompt)
-        rsp = await self._aask(prompt=self.prompt)
-        logger.debug(rsp)
-        self._set_result(rsp)
-        return self.rsp
-
-    def _set_result(self, rsp):
-        if self.action_options.rsp_begin_tag and self.action_options.rsp_begin_tag in rsp:
-            ix = rsp.index(self.action_options.rsp_begin_tag)
-            rsp = rsp[ix + len(self.action_options.rsp_begin_tag):]
-        if self.action_options.rsp_end_tag and self.action_options.rsp_end_tag in rsp:
-            ix = rsp.index(self.action_options.rsp_end_tag)
-            rsp = rsp[0:ix]
-        self.rsp = rsp.strip()
-
-    @staticmethod
-    def get_action_type(topic: str):
-        """Create a runtime :class:`Action` subclass"""
-        action_type: Type["Action"] = type(topic, (Action,), {"name": topic})
-        return action_type
diff --git a/metagpt/roles/assistant.py b/metagpt/roles/assistant.py
index c001d69f0..a3af715e3 100644
--- a/metagpt/roles/assistant.py
+++ b/metagpt/roles/assistant.py
@@ -14,6 +14,7 @@
 
 """
 import asyncio
+from pathlib import Path
 
 from metagpt.actions import ActionOutput
 from metagpt.actions.skill_action import SkillAction, ArgumentsParingAction
@@ -29,6 +30,7 @@ from metagpt.schema import Message
 DEFAULT_MAX_TOKENS = 1500
 COMMAND_TOKENS = 500
 BRAIN_MEMORY = "BRAIN_MEMORY"
+SKILL_PATH = "SKILL_PATH"
 
 
 class Assistant(Role):
@@ -40,7 +42,8 @@ class Assistant(Role):
                                         goal=goal, constraints=constraints, desc=desc, *args, **kwargs)
         brain_memory = options.get(BRAIN_MEMORY)
         self.memory = BrainMemory(**brain_memory) if brain_memory else BrainMemory()
-        self.skills = SkillLoader()
+        skill_path = Path(options.get(SKILL_PATH)) if options.get(SKILL_PATH) else None
+        self.skills = SkillLoader(skill_yaml_file_name=skill_path)
 
     async def think(self) -> bool:
         """Everything will be done part by part."""