add tool_* and action_* into core

Author: WannaTen

metagpt/core/actions/__init__.py

@@ -6,7 +6,7 @@
 @File    : __init__.py
 """
 
-from metagpt.core.actions.base import Action
+from metagpt.core.actions.action import Action
 from metagpt.core.actions.action_output import ActionOutput
 
 __all__ = [

metagpt/core/actions/action.py

@@ -0,0 +1,119 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2023/5/11 14:43
+@Author  : alexanderwu
+@File    : action.py
+"""
+
+from __future__ import annotations
+
+from typing import Any, Optional, Union
+
+from pydantic import BaseModel, ConfigDict, Field, model_validator
+
+from metagpt.core.actions.action_node import ActionNode
+from metagpt.core.configs.models_config import ModelsConfig
+from metagpt.core.context_mixin import ContextMixin
+from metagpt.core.provider.llm_provider_registry import create_llm_instance
+from metagpt.core.schema import (
+    CodePlanAndChangeContext,
+    CodeSummarizeContext,
+    CodingContext,
+    RunCodeContext,
+    SerializationMixin,
+    TestingContext,
+)
+
+
+class Action(SerializationMixin, ContextMixin, BaseModel):
+    model_config = ConfigDict(arbitrary_types_allowed=True)
+
+    name: str = ""
+    i_context: Union[
+        dict, CodingContext, CodeSummarizeContext, TestingContext, RunCodeContext, CodePlanAndChangeContext, str, None
+    ] = ""
+    prefix: str = ""  # aask*时会加上prefix，作为system_message
+    desc: str = ""  # for skill manager
+    node: ActionNode = Field(default=None, exclude=True)
+    # The model name or API type of LLM of the `models` in the `config2.yaml`;
+    #   Using `None` to use the `llm` configuration in the `config2.yaml`.
+    llm_name_or_type: Optional[str] = None
+
+    @model_validator(mode="after")
+    @classmethod
+    def _update_private_llm(cls, data: Any) -> Any:
+        config = ModelsConfig.default().get(data.llm_name_or_type)
+        if config:
+            llm = create_llm_instance(config)
+            llm.cost_manager = data.llm.cost_manager
+            data.llm = llm
+        return data
+
+    @property
+    def prompt_schema(self):
+        return self.config.prompt_schema
+
+    @property
+    def project_name(self):
+        return self.config.project_name
+
+    @project_name.setter
+    def project_name(self, value):
+        self.config.project_name = value
+
+    @property
+    def project_path(self):
+        return self.config.project_path
+
+    @model_validator(mode="before")
+    @classmethod
+    def set_name_if_empty(cls, values):
+        if "name" not in values or not values["name"]:
+            values["name"] = cls.__name__
+        return values
+
+    @model_validator(mode="before")
+    @classmethod
+    def _init_with_instruction(cls, values):
+        if "instruction" in values:
+            name = values["name"]
+            i = values.pop("instruction")
+            values["node"] = ActionNode(key=name, expected_type=str, instruction=i, example="", schema="raw")
+        return values
+
+    def set_prefix(self, prefix):
+        """Set prefix for later usage"""
+        self.prefix = prefix
+        self.llm.system_prompt = prefix
+        if self.node:
+            self.node.llm = self.llm
+        return self
+
+    def __str__(self):
+        return self.__class__.__name__
+
+    def __repr__(self):
+        return self.__str__()
+
+    async def _aask(self, prompt: str, system_msgs: Optional[list[str]] = None) -> str:
+        """Append default prefix"""
+        return await self.llm.aask(prompt, system_msgs)
+
+    async def _run_action_node(self, *args, **kwargs):
+        """Run action node"""
+        msgs = args[0]
+        context = "## History Messages\n"
+        context += "\n".join([f"{idx}: {i}" for idx, i in enumerate(reversed(msgs))])
+        return await self.node.fill(req=context, llm=self.llm)
+
+    async def run(self, *args, **kwargs):
+        """Run action"""
+        if self.node:
+            return await self._run_action_node(*args, **kwargs)
+        raise NotImplementedError("The run method should be implemented in a subclass.")
+
+    def override_context(self):
+        """Set `private_context` and `context` to the same `Context` object."""
+        if not self.private_context:
+            self.private_context = self.context

metagpt/core/actions/action_graph.py

@@ -0,0 +1,49 @@
+#!/usr/bin/env python
+# -*- coding: utf-8 -*-
+"""
+@Time    : 2024/1/30 13:52
+@Author  : alexanderwu
+@File    : action_graph.py
+"""
+from __future__ import annotations
+
+# from metagpt.actions.action_node import ActionNode
+
+
+class ActionGraph:
+    """ActionGraph: a directed graph to represent the dependency between actions."""
+
+    def __init__(self):
+        self.nodes = {}
+        self.edges = {}
+        self.execution_order = []
+
+    def add_node(self, node):
+        """Add a node to the graph"""
+        self.nodes[node.key] = node
+
+    def add_edge(self, from_node: "ActionNode", to_node: "ActionNode"):
+        """Add an edge to the graph"""
+        if from_node.key not in self.edges:
+            self.edges[from_node.key] = []
+        self.edges[from_node.key].append(to_node.key)
+        from_node.add_next(to_node)
+        to_node.add_prev(from_node)
+
+    def topological_sort(self):
+        """Topological sort the graph"""
+        visited = set()
+        stack = []
+
+        def visit(k):
+            if k not in visited:
+                visited.add(k)
+                if k in self.edges:
+                    for next_node in self.edges[k]:
+                        visit(next_node)
+                stack.insert(0, k)
+
+        for key in self.nodes:
+            visit(key)
+
+        self.execution_order = stack