Files
AstrBot/astrbot/core/astr_agent_tool_exec.py
T

247 lines
8.6 KiB
Python

import asyncio
import inspect
import traceback
import typing as T
import mcp
from astrbot import logger
from astrbot.core.agent.handoff import HandoffTool
from astrbot.core.agent.mcp_client import MCPTool
from astrbot.core.agent.run_context import ContextWrapper
from astrbot.core.agent.tool import FunctionTool, ToolSet
from astrbot.core.agent.tool_executor import BaseFunctionToolExecutor
from astrbot.core.astr_agent_context import AstrAgentContext
from astrbot.core.message.message_event_result import (
CommandResult,
MessageChain,
MessageEventResult,
)
from astrbot.core.provider.register import llm_tools
class FunctionToolExecutor(BaseFunctionToolExecutor[AstrAgentContext]):
@classmethod
async def execute(cls, tool, run_context, **tool_args):
"""执行函数调用。
Args:
event (AstrMessageEvent): 事件对象, 当 origin 为 local 时必须提供。
**kwargs: 函数调用的参数。
Returns:
AsyncGenerator[None | mcp.types.CallToolResult, None]
"""
if isinstance(tool, HandoffTool):
async for r in cls._execute_handoff(tool, run_context, **tool_args):
yield r
return
elif isinstance(tool, MCPTool):
async for r in cls._execute_mcp(tool, run_context, **tool_args):
yield r
return
else:
async for r in cls._execute_local(tool, run_context, **tool_args):
yield r
return
@classmethod
async def _execute_handoff(
cls,
tool: HandoffTool,
run_context: ContextWrapper[AstrAgentContext],
**tool_args,
):
input_ = tool_args.get("input")
# make toolset for the agent
tools = tool.agent.tools
if tools:
toolset = ToolSet()
for t in tools:
if isinstance(t, str):
_t = llm_tools.get_func(t)
if _t:
toolset.add_tool(_t)
elif isinstance(t, FunctionTool):
toolset.add_tool(t)
else:
toolset = None
ctx = run_context.context.context
event = run_context.context.event
umo = event.unified_msg_origin
prov_id = await ctx.get_current_chat_provider_id(umo)
llm_resp = await ctx.tool_loop_agent(
event=event,
chat_provider_id=prov_id,
prompt=input_,
system_prompt=tool.agent.instructions,
tools=toolset,
max_steps=30,
run_hooks=tool.agent.run_hooks,
)
yield mcp.types.CallToolResult(
content=[mcp.types.TextContent(type="text", text=llm_resp.completion_text)]
)
@classmethod
async def _execute_local(
cls,
tool: FunctionTool,
run_context: ContextWrapper[AstrAgentContext],
**tool_args,
):
event = run_context.context.event
if not event:
raise ValueError("Event must be provided for local function tools.")
is_override_call = False
for ty in type(tool).mro():
if "call" in ty.__dict__ and ty.__dict__["call"] is not FunctionTool.call:
is_override_call = True
break
# 检查 tool 下有没有 run 方法
if not tool.handler and not hasattr(tool, "run") and not is_override_call:
raise ValueError("Tool must have a valid handler or override 'run' method.")
awaitable = None
method_name = ""
if tool.handler:
awaitable = tool.handler
method_name = "decorator_handler"
elif is_override_call:
awaitable = tool.call
method_name = "call"
elif hasattr(tool, "run"):
awaitable = getattr(tool, "run")
method_name = "run"
if awaitable is None:
raise ValueError("Tool must have a valid handler or override 'run' method.")
wrapper = call_local_llm_tool(
context=run_context,
handler=awaitable,
method_name=method_name,
**tool_args,
)
while True:
try:
resp = await asyncio.wait_for(
anext(wrapper),
timeout=run_context.tool_call_timeout,
)
if resp is not None:
if isinstance(resp, mcp.types.CallToolResult):
yield resp
else:
text_content = mcp.types.TextContent(
type="text",
text=str(resp),
)
yield mcp.types.CallToolResult(content=[text_content])
else:
# NOTE: Tool 在这里直接请求发送消息给用户
# TODO: 是否需要判断 event.get_result() 是否为空?
# 如果为空,则说明没有发送消息给用户,并且返回值为空,将返回一个特殊的 TextContent,其内容如"工具没有返回内容"
if res := run_context.context.event.get_result():
if res.chain:
try:
await event.send(
MessageChain(
chain=res.chain,
type="tool_direct_result",
)
)
except Exception as e:
logger.error(
f"Tool 直接发送消息失败: {e}",
exc_info=True,
)
yield None
except asyncio.TimeoutError:
raise Exception(
f"tool {tool.name} execution timeout after {run_context.tool_call_timeout} seconds.",
)
except StopAsyncIteration:
break
@classmethod
async def _execute_mcp(
cls,
tool: FunctionTool,
run_context: ContextWrapper[AstrAgentContext],
**tool_args,
):
res = await tool.call(run_context, **tool_args)
if not res:
return
yield res
async def call_local_llm_tool(
context: ContextWrapper[AstrAgentContext],
handler: T.Callable[..., T.Awaitable[T.Any]],
method_name: str,
*args,
**kwargs,
) -> T.AsyncGenerator[T.Any, None]:
"""执行本地 LLM 工具的处理函数并处理其返回结果"""
ready_to_call = None # 一个协程或者异步生成器
trace_ = None
event = context.context.event
try:
if method_name == "run" or method_name == "decorator_handler":
ready_to_call = handler(event, *args, **kwargs)
elif method_name == "call":
ready_to_call = handler(context, *args, **kwargs)
else:
raise ValueError(f"未知的方法名: {method_name}")
except ValueError as e:
logger.error(f"调用本地 LLM 工具时出错: {e}", exc_info=True)
except TypeError:
logger.error("处理函数参数不匹配,请检查 handler 的定义。", exc_info=True)
except Exception as e:
trace_ = traceback.format_exc()
logger.error(f"调用本地 LLM 工具时出错: {e}\n{trace_}")
if not ready_to_call:
return
if inspect.isasyncgen(ready_to_call):
_has_yielded = False
try:
async for ret in ready_to_call:
# 这里逐步执行异步生成器, 对于每个 yield 返回的 ret, 执行下面的代码
# 返回值只能是 MessageEventResult 或者 None(无返回值)
_has_yielded = True
if isinstance(ret, (MessageEventResult, CommandResult)):
# 如果返回值是 MessageEventResult, 设置结果并继续
event.set_result(ret)
yield
else:
# 如果返回值是 None, 则不设置结果并继续
# 继续执行后续阶段
yield ret
if not _has_yielded:
# 如果这个异步生成器没有执行到 yield 分支
yield
except Exception as e:
logger.error(f"Previous Error: {trace_}")
raise e
elif inspect.iscoroutine(ready_to_call):
# 如果只是一个协程, 直接执行
ret = await ready_to_call
if isinstance(ret, (MessageEventResult, CommandResult)):
event.set_result(ret)
yield
else:
yield ret