chore: ruff format

Co-authored-by: gemini-code-assist[bot] <176961590+gemini-code-assist[bot]@users.noreply.github.com>

astrbot/api/event/filter/__init__.py

@@ -14,6 +14,8 @@ from astrbot.core.star.register import register_command_group as command_group
 from astrbot.core.star.register import register_custom_filter as custom_filter
 from astrbot.core.star.register import register_event_message_type as event_message_type
 from astrbot.core.star.register import register_llm_tool as llm_tool
+from astrbot.core.star.register import register_on_agent_begin as on_agent_begin
+from astrbot.core.star.register import register_on_agent_done as on_agent_done
 from astrbot.core.star.register import register_on_astrbot_loaded as on_astrbot_loaded
 from astrbot.core.star.register import (
     register_on_decorating_result as on_decorating_result,
@@ -51,6 +53,8 @@ __all__ = [
     "custom_filter",
     "event_message_type",
     "llm_tool",
+    "on_agent_begin",
+    "on_agent_done",
     "on_astrbot_loaded",
     "on_decorating_result",
     "on_llm_request",

astrbot/core/astr_agent_hooks.py

@@ -12,6 +12,15 @@ from astrbot.core.star.star_handler import EventType
 
 
 class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
+    async def on_agent_begin(
+        self, run_context: ContextWrapper[AstrAgentContext]
+    ) -> None:
+        await call_event_hook(
+            run_context.context.event,
+            EventType.OnAgentBeginEvent,
+            run_context,
+        )
+
     async def on_agent_done(self, run_context, llm_response) -> None:
         # 执行事件钩子
         if llm_response and llm_response.reasoning_content:
@@ -25,6 +34,12 @@ class MainAgentHooks(BaseAgentRunHooks[AstrAgentContext]):
             EventType.OnLLMResponseEvent,
             llm_response,
         )
+        await call_event_hook(
+            run_context.context.event,
+            EventType.OnAgentDoneEvent,
+            run_context,
+            llm_response,
+        )
 
     async def on_tool_start(
         self,

astrbot/core/star/register/__init__.py

@@ -7,6 +7,8 @@ from .star_handler import (
     register_custom_filter,
     register_event_message_type,
     register_llm_tool,
+    register_on_agent_begin,
+    register_on_agent_done,
     register_on_astrbot_loaded,
     register_on_decorating_result,
     register_on_llm_request,
@@ -31,6 +33,8 @@ __all__ = [
     "register_custom_filter",
     "register_event_message_type",
     "register_llm_tool",
+    "register_on_agent_begin",
+    "register_on_agent_done",
     "register_on_astrbot_loaded",
     "register_on_decorating_result",
     "register_on_llm_request",

astrbot/core/star/register/star_handler.py

@@ -460,6 +460,64 @@ def register_on_llm_response(**kwargs):
     return decorator
 
 
+def register_on_agent_begin(**kwargs):
+    """当 Agent 开始运行时的事件
+
+    Examples:
+    ```py
+    from astrbot.core.agent.run_context import ContextWrapper
+    from astrbot.core.astr_agent_context import AstrAgentContext
+
+    @on_agent_begin()
+    async def test(
+        self,
+        event: AstrMessageEvent,
+        run_context: ContextWrapper[AstrAgentContext],
+    ) -> None:
+        ...
+    ```
+
+    请务必接收两个参数：event, run_context
+
+    """
+
+    def decorator(awaitable):
+        _ = get_handler_or_create(awaitable, EventType.OnAgentBeginEvent, **kwargs)
+        return awaitable
+
+    return decorator
+
+
+def register_on_agent_done(**kwargs):
+    """当 Agent 运行完成后的事件
+
+    Examples:
+    ```py
+    from astrbot.core.agent.run_context import ContextWrapper
+    from astrbot.core.astr_agent_context import AstrAgentContext
+    from astrbot.api.provider import LLMResponse
+
+    @on_agent_done()
+    async def test(
+        self,
+        event: AstrMessageEvent,
+        run_context: ContextWrapper[AstrAgentContext],
+        response: LLMResponse,
+    ) -> None:
+        ...
+    ```
+
+    请务必接收三个参数：event, run_context, response
+
+    """
+
+    def decorator(awaitable):
+        _ = get_handler_or_create(awaitable, EventType.OnAgentDoneEvent, **kwargs)
+        return awaitable
+
+    return decorator
+
+
 def register_on_using_llm_tool(**kwargs):
     """当调用函数工具前的事件。
     会传入 tool 和 tool_args 参数。

astrbot/core/star/star_handler.py

@@ -71,6 +71,22 @@ class StarHandlerRegistry(Generic[T]):
         plugins_name: list[str] | None = None,
     ) -> list[StarHandlerMetadata[Callable[..., Awaitable[Any]]]]: ...
 
+    @overload
+    def get_handlers_by_event_type(
+        self,
+        event_type: Literal[EventType.OnAgentBeginEvent],
+        only_activated=True,
+        plugins_name: list[str] | None = None,
+    ) -> list[StarHandlerMetadata[Callable[..., Awaitable[Any]]]]: ...
+
+    @overload
+    def get_handlers_by_event_type(
+        self,
+        event_type: Literal[EventType.OnAgentDoneEvent],
+        only_activated=True,
+        plugins_name: list[str] | None = None,
+    ) -> list[StarHandlerMetadata[Callable[..., Awaitable[Any]]]]: ...
+
     @overload
     def get_handlers_by_event_type(
         self,
@@ -213,6 +229,8 @@ class EventType(enum.Enum):
     OnWaitingLLMRequestEvent = enum.auto()  # 等待调用 LLM（在获取锁之前，仅通知）
     OnLLMRequestEvent = enum.auto()  # 收到 LLM 请求（可以是用户也可以是插件）
     OnLLMResponseEvent = enum.auto()  # LLM 响应后
+    OnAgentBeginEvent = enum.auto()  # Agent 开始运行
+    OnAgentDoneEvent = enum.auto()  # Agent 运行完成
     OnDecoratingResultEvent = enum.auto()  # 发送消息前
     OnCallingFuncToolEvent = enum.auto()  # 调用函数工具
     OnUsingLLMToolEvent = enum.auto()  # 使用 LLM 工具

astrbot/dashboard/routes/plugin.py

@@ -79,6 +79,8 @@ class PluginRoute(Route):
             EventType.AdapterMessageEvent: "平台消息下发时",
             EventType.OnLLMRequestEvent: "LLM 请求时",
             EventType.OnLLMResponseEvent: "LLM 响应后",
+            EventType.OnAgentBeginEvent: "Agent 开始运行时",
+            EventType.OnAgentDoneEvent: "Agent 运行完成后",
             EventType.OnDecoratingResultEvent: "回复消息前",
             EventType.OnCallingFuncToolEvent: "函数工具",
             EventType.OnAfterMessageSentEvent: "发送消息后",

docs/en/dev/star/guides/listen-message-event.md

@@ -289,6 +289,94 @@ async def on_llm_resp(self, event: AstrMessageEvent, resp: LLMResponse): # Note
 
 > You cannot use yield to send messages here. If you need to send, please use the `event.send()` method directly.
 
+#### On Agent Begin
+
+> Requires AstrBot version > v4.23.1
+
+When the Agent starts running, the `on_agent_begin` hook is triggered.
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_begin()
+async def on_agent_begin(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext]): # Note there are three parameters
+    print("Agent started")
+```
+
+> You cannot use yield to send messages here. If you need to send, please use the `event.send()` method directly.
+
+#### Before LLM Tool Call
+
+> Requires AstrBot version > v4.23.1
+
+When the Agent is about to call an LLM tool, the `on_using_llm_tool` hook is triggered.
+
+You can obtain the `FunctionTool` object and tool call arguments.
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_using_llm_tool()
+async def on_using_llm_tool(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+):
+    print(tool.name, tool_args)
+```
+
+> You cannot use yield to send messages here. If you need to send, please use the `event.send()` method directly.
+
+#### After LLM Tool Call
+
+> Requires AstrBot version > v4.23.1
+
+After the LLM tool call completes, the `on_llm_tool_respond` hook is triggered.
+
+You can obtain the `FunctionTool` object, tool call arguments, and tool call result.
+
+```python
+from mcp.types import CallToolResult
+
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_llm_tool_respond()
+async def on_llm_tool_respond(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+    tool_result: CallToolResult | None,
+):
+    print(tool.name, tool_args, tool_result)
+```
+
+> You cannot use yield to send messages here. If you need to send, please use the `event.send()` method directly.
+
+#### On Agent Done
+
+> Requires AstrBot version > v4.23.1
+
+After the Agent finishes running, the `on_agent_done` hook is triggered. This hook is triggered after `on_llm_response`.
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.api.provider import LLMResponse
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_done()
+async def on_agent_done(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext], resp: LLMResponse): # Note there are four parameters
+    print(resp)
+```
+
+> You cannot use yield to send messages here. If you need to send, please use the `event.send()` method directly.
+
 #### Before Sending Message
 
 Before sending a message, the `on_decorating_result` hook is triggered.

docs/zh/dev/star/guides/listen-message-event.md

@@ -305,6 +305,94 @@ async def on_llm_resp(self, event: AstrMessageEvent, resp: LLMResponse): # 请
 
 > 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
 
+#### Agent 开始运行时
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 开始运行时，会触发 `on_agent_begin` 钩子。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_begin()
+async def on_agent_begin(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext]):
+    print("Agent 开始运行")
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+#### LLM 工具调用前
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 准备调用 LLM 工具时，会触发 `on_using_llm_tool` 钩子。
+
+可以获取到 `FunctionTool` 对象和工具调用参数。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_using_llm_tool()
+async def on_using_llm_tool(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+):
+    print(tool.name, tool_args)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+#### LLM 工具调用后
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 LLM 工具调用完成后，会触发 `on_llm_tool_respond` 钩子。
+
+可以获取到 `FunctionTool` 对象、工具调用参数和工具调用结果。
+
+```python
+from mcp.types import CallToolResult
+
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_llm_tool_respond()
+async def on_llm_tool_respond(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+    tool_result: CallToolResult | None,
+):
+    print(tool.name, tool_args, tool_result)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+#### Agent 运行完成时
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 运行完成后，会触发 `on_agent_done` 钩子。这个钩子会在 `on_llm_response` 之后触发。本质上和 `on_llm_response` 一样。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.api.provider import LLMResponse
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_done()
+async def on_agent_done(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext], resp: LLMResponse):
+    print(resp)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
 #### 发送消息前
 
 在发送消息前，会触发 `on_decorating_result` 钩子。

docs/zh/dev/star/plugin.md

@@ -507,6 +507,96 @@ async def on_llm_resp(self, event: AstrMessageEvent, resp: LLMResponse): # 请
 
 > 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
 
+##### Agent 开始运行时
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 开始运行时，会触发 `on_agent_begin` 钩子。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_begin()
+async def on_agent_begin(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext]): # 请注意有三个参数
+    print("Agent 开始运行")
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+##### LLM 工具调用前
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 准备调用 LLM 工具时，会触发 `on_using_llm_tool` 钩子。
+
+可以获取到 `FunctionTool` 对象和工具调用参数。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_using_llm_tool()
+async def on_using_llm_tool(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+):
+    print(tool.name, tool_args)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+##### LLM 工具调用后
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 LLM 工具调用完成后，会触发 `on_llm_tool_respond` 钩子。
+
+可以获取到 `FunctionTool` 对象、工具调用参数和工具调用结果。
+
+```python
+from mcp.types import CallToolResult
+
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.core.agent.tool import FunctionTool
+
+@filter.on_llm_tool_respond()
+async def on_llm_tool_respond(
+    self,
+    event: AstrMessageEvent,
+    tool: FunctionTool,
+    tool_args: dict | None,
+    tool_result: CallToolResult | None,
+):
+    print(tool.name, tool_args, tool_result)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
+##### Agent 运行完成时
+
+> 适用于 AstrBot 版本 > v4.23.1
+
+在 Agent 运行完成后，会触发 `on_agent_done` 钩子。这个钩子会在 `on_llm_response` 之后触发。
+
+可以获取到 `LLMResponse` 对象，可以对其进行修改。
+
+```python
+from astrbot.api.event import filter, AstrMessageEvent
+from astrbot.api.provider import LLMResponse
+from astrbot.core.agent.run_context import ContextWrapper
+from astrbot.core.astr_agent_context import AstrAgentContext
+
+@filter.on_agent_done()
+async def on_agent_done(self, event: AstrMessageEvent, run_context: ContextWrapper[AstrAgentContext], resp: LLMResponse): # 请注意有四个参数
+    print(resp)
+```
+
+> 这里不能使用 yield 来发送消息。如需发送，请直接使用 `event.send()` 方法。
+
 ##### 发送消息前
 
 在发送消息前，会触发 `on_decorating_result` 钩子。