ai-agent-book 精选快照（<2MB 代码与文档，来自 github.com/bojieli/ai-agent-book）

chapter9/gaia-experience/AWorld/aworld/tools/README.md

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+# Environments
+
+Virtual environments for execution of various tools.
+
+Running on the local, we assume that the virtual environment completes startup when the python application starts.
+
+![Environment Architecture](../../readme_assets/framework_environment.png)
+
+# Be tool
+
+You also can convert locally defined functions into tools for use in a task.
+
+NOTE: The function must have a return value, preferably a string, as observed content.
+
+```python
+from pydantic import Field
+
+from aworld.core.tool.func_to_tool import be_tool
+
+
+@be_tool(tool_name='example', tool_desc="example description")
+def example_1() -> str:
+    return "example_1"
+
+
+@be_tool(tool_name='example')
+def example_2(param: str) -> str:
+    return f"example_2{param}"
+
+
+@be_tool(tool_name='example', name="example_3_alias_name", desc="example_3 description")
+def example_3(param_1: str = "param",
+              param_2: str = Field(default="", description="param2 description")) -> str:
+    return f"example_3{param_1}{param_2}"
+```
+
+The name of the tool is `example`, now, you can use these functions as tools in the framework.
+
+# Write tool
+
+Detailed steps for building a tool:
+
+1. Register action of your tool to action factory, and inherit `ExecutableAction`
+2. Optional implement the `act` or `async_act` method
+3. Register your tool to tool factory, and inherit `Tool` or `AsyncTool`
+4. Write the `step` method to execute the abilities in the tool and generate observation, update finished Status.
+
+```python
+from typing import List, Tuple, Dict, Any
+
+from aworld.core.common import ActionModel, Observation
+from aworld.core.tool.action import ExecutableAction
+from aworld.core.tool.base import ActionFactory, ToolFactory, AgentInput
+from aworld.tools.template_tool import TemplateTool
+
+from examples.common.tools.tool_action import GymAction
+
+
+@ToolFactory.register(name="openai_gym", desc="gym classic control game", supported_action=GymAction)
+class OpenAIGym(TemplateTool):
+    def step(self, action: List[ActionModel], **kwargs) -> Tuple[AgentInput, float, bool, bool, Dict[str, Any]]:
+        ...
+        state, reward, terminal, truncate, info = self.env.step(action)
+        ...
+        return (Observation(content=state),
+                reward,
+                terminal,
+                truncate,
+                info)
+
+
+@ActionFactory.register(name=GymAction.PLAY.value.name,
+                        desc=GymAction.PLAY.value.desc,
+                        tool_name="openai_gym")
+class Play(ExecutableAction):
+    """There is only one Action, it can be implemented in the tool, registration is required here."""
+```
+
+You can view the example [code](gym_tool/openai_gym.py) to learn more.