Files
LangBot/pkg/provider/tools/toolmgr.py

106 lines
3.2 KiB
Python

from __future__ import annotations
import typing
from ...core import app
from ...utils import importutil
from . import loaders
from .loaders import mcp as mcp_loader, plugin as plugin_loader
import langbot_plugin.api.entities.builtin.resource.tool as resource_tool
importutil.import_modules_in_pkg(loaders)
class ToolManager:
"""LLM工具管理器"""
ap: app.Application
plugin_tool_loader: plugin_loader.PluginToolLoader
mcp_tool_loader: mcp_loader.MCPLoader
def __init__(self, ap: app.Application):
self.ap = ap
async def initialize(self):
self.plugin_tool_loader = plugin_loader.PluginToolLoader(self.ap)
await self.plugin_tool_loader.initialize()
self.mcp_tool_loader = mcp_loader.MCPLoader(self.ap)
await self.mcp_tool_loader.initialize()
async def get_all_tools(self) -> list[resource_tool.LLMTool]:
"""获取所有函数"""
all_functions: list[resource_tool.LLMTool] = []
all_functions.extend(await self.plugin_tool_loader.get_tools())
all_functions.extend(await self.mcp_tool_loader.get_tools())
return all_functions
async def generate_tools_for_openai(self, use_funcs: list[resource_tool.LLMTool]) -> list:
"""生成函数列表"""
tools = []
for function in use_funcs:
function_schema = {
'type': 'function',
'function': {
'name': function.name,
'description': function.description,
'parameters': function.parameters,
},
}
tools.append(function_schema)
return tools
async def generate_tools_for_anthropic(self, use_funcs: list[resource_tool.LLMTool]) -> list:
"""为anthropic生成函数列表
e.g.
[
{
"name": "get_stock_price",
"description": "Get the current stock price for a given ticker symbol.",
"input_schema": {
"type": "object",
"properties": {
"ticker": {
"type": "string",
"description": "The stock ticker symbol, e.g. AAPL for Apple Inc."
}
},
"required": ["ticker"]
}
}
]
"""
tools = []
for function in use_funcs:
function_schema = {
'name': function.name,
'description': function.description,
'input_schema': function.parameters,
}
tools.append(function_schema)
return tools
async def execute_func_call(self, name: str, parameters: dict) -> typing.Any:
"""执行函数调用"""
if await self.plugin_tool_loader.has_tool(name):
return await self.plugin_tool_loader.invoke_tool(name, parameters)
elif await self.mcp_tool_loader.has_tool(name):
return await self.mcp_tool_loader.invoke_tool(name, parameters)
else:
raise ValueError(f'未找到工具: {name}')
async def shutdown(self):
"""关闭所有工具"""
await self.plugin_tool_loader.shutdown()
await self.mcp_tool_loader.shutdown()