Files
LangBot/src/langbot/pkg/provider/tools/loaders/plugin.py
2026-06-06 15:02:47 +08:00

67 lines
2.4 KiB
Python

from __future__ import annotations
import typing
import traceback
from langbot_plugin.api.definition.components.manifest import ComponentManifest
from langbot_plugin.api.entities.events import pipeline_query
from .. import loader
import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
# @loader.loader_class('plugin-tool-loader')
class PluginToolLoader(loader.ToolLoader):
"""插件工具加载器。
本加载器中不存储工具信息,仅负责从插件系统中获取工具信息。
"""
async def get_tools(self, bound_plugins: list[str] | None = None) -> list[resource_tool.LLMTool]:
# 从插件系统获取工具(内容函数)
all_functions: list[resource_tool.LLMTool] = []
for tool in await self.ap.plugin_connector.list_tools(bound_plugins):
tool_obj = resource_tool.LLMTool(
name=tool.metadata.name,
human_desc=tool.metadata.description.en_US,
description=tool.spec['llm_prompt'],
parameters=tool.spec['parameters'],
func=lambda parameters: {},
)
all_functions.append(tool_obj)
return all_functions
async def has_tool(self, name: str) -> bool:
"""检查工具是否存在"""
for tool in await self.ap.plugin_connector.list_tools():
if tool.metadata.name == name:
return True
return False
async def get_tool(self, name: str) -> ComponentManifest | None:
for tool in await self.ap.plugin_connector.list_tools():
if tool.metadata.name == name:
return tool
return None
async def invoke_tool(self, name: str, parameters: dict, query: pipeline_query.Query | None) -> typing.Any:
if query is None:
raise ValueError(
f'Plugin tool {name} requires a query-based host context. '
'Use MCP tools or provide a Host tool implementation that is run-scoped.'
)
try:
return await self.ap.plugin_connector.call_tool(
name, parameters, session=query.session, query_id=query.query_id
)
except Exception as e:
self.ap.logger.error(f'执行函数 {name} 时发生错误: {e}')
traceback.print_exc()
return f'error occurred when executing function {name}: {e}'
async def shutdown(self):
"""关闭工具"""
pass