mirror of
https://github.com/langbot-app/LangBot.git
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139 lines
4.2 KiB
Python
139 lines
4.2 KiB
Python
from __future__ import annotations
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import typing
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import traceback
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from ...core import app, entities as core_entities
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from . import entities
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from ...plugin import context as plugin_context
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class ToolManager:
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"""LLM工具管理器"""
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ap: app.Application
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def __init__(self, ap: app.Application):
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self.ap = ap
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self.all_functions = []
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async def initialize(self):
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pass
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async def get_function_and_plugin(
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self, name: str
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) -> typing.Tuple[entities.LLMFunction, plugin_context.BasePlugin]:
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"""获取函数和插件实例"""
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for plugin in self.ap.plugin_mgr.plugins(
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enabled=True, status=plugin_context.RuntimeContainerStatus.INITIALIZED
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):
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for function in plugin.content_functions:
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if function.name == name:
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return function, plugin.plugin_inst
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return None, None
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async def get_all_functions(self, plugin_enabled: bool=None, plugin_status: plugin_context.RuntimeContainerStatus=None) -> list[entities.LLMFunction]:
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"""获取所有函数"""
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all_functions: list[entities.LLMFunction] = []
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for plugin in self.ap.plugin_mgr.plugins(
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enabled=plugin_enabled, status=plugin_status
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):
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all_functions.extend(plugin.content_functions)
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return all_functions
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async def generate_tools_for_openai(self, use_funcs: list[entities.LLMFunction]) -> list:
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"""生成函数列表"""
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tools = []
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for function in use_funcs:
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function_schema = {
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"type": "function",
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"function": {
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"name": function.name,
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"description": function.description,
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"parameters": function.parameters,
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},
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}
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tools.append(function_schema)
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return tools
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async def generate_tools_for_anthropic(
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self, use_funcs: list[entities.LLMFunction]
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) -> list:
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"""为anthropic生成函数列表
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e.g.
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[
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{
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"name": "get_stock_price",
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"description": "Get the current stock price for a given ticker symbol.",
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"input_schema": {
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"type": "object",
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"properties": {
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"ticker": {
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"type": "string",
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"description": "The stock ticker symbol, e.g. AAPL for Apple Inc."
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}
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},
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"required": ["ticker"]
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}
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}
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]
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"""
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tools = []
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for function in use_funcs:
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function_schema = {
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"name": function.name,
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"description": function.description,
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"input_schema": function.parameters,
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}
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tools.append(function_schema)
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return tools
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async def execute_func_call(
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self, query: core_entities.Query, name: str, parameters: dict
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) -> typing.Any:
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"""执行函数调用"""
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try:
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function, plugin = await self.get_function_and_plugin(name)
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if function is None:
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return None
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parameters = parameters.copy()
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parameters = {"query": query, **parameters}
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return await function.func(plugin, **parameters)
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except Exception as e:
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self.ap.logger.error(f"执行函数 {name} 时发生错误: {e}")
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traceback.print_exc()
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return f"error occurred when executing function {name}: {e}"
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finally:
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plugin = None
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for p in self.ap.plugin_mgr.plugins():
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if function in p.content_functions:
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plugin = p
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break
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if plugin is not None:
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await self.ap.ctr_mgr.usage.post_function_record(
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plugin={
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"name": plugin.plugin_name,
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"remote": plugin.plugin_source,
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"version": plugin.plugin_version,
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"author": plugin.plugin_author,
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},
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function_name=function.name,
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function_description=function.description,
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) |