General Agent 一个简单、通用、可定制的Agent框架 --知识铺

1

git clone https://github.com/CosmosShadow/GeneralAgent cd GeneralAgent python setup.py install

1

GeneralAgent --workspace ./test --new # worksapce: Set workspace directory, default ./general_agent_data # new: if workspace exists, create a new workspace

1

import asyncio from GeneralAgent.agent import Agent async def main(): agent = Agent.empty() while True: input_content = input('>>>') await agent.run(input_content) if __name__ == '__main__': asyncio.run(main())

1

import asyncio from GeneralAgent.agent import Agent async def main(): agent = Agent.default() while True: input_content = input() await agent.run(input_content) if __name__ == '__main__': asyncio.run(main())

1

import re import asyncio from GeneralAgent.agent import Agent from GeneralAgent.interpreter import Interpreter from GeneralAgent.utils import confirm_to_run python_prompt = """ # Run python * Remember use print() to output * format is : ```python\\nthe_code\\n``` * the code will be executed * python version is 3.9 """ class BasicPythonInterpreter(Interpreter): @property def match_template(self) -> bool: return r'```python\n([\s\S]*)\n```' def parse(self, string) -> (str, bool): pattern = re.compile(self.match_template, re.DOTALL) code = pattern.search(string).group(1) if confirm_to_run(): exec(code) return '' , False def prompt(self, messages) -> str: return python_prompt def match(self, string) -> bool: super().match(string) async def main(): agent = Agent(output_interpreters=[BasicPythonInterpreter()]) while True: input_content = input('>>>') await agent.run(input_content) if __name__ == '__main__': asyncio.run(main())

1

import asyncio from GeneralAgent.agent import Agent async def custom_output(token): if token is None: print('[output end]') else: print(token, end='', flush=True) async def main(): agent = Agent.default('./basic') while True: input_content = input('>>>') await agent.run(input_content, output_recall=custom_output) if __name__ == '__main__': asyncio.run(main())

1

""" Now: {{now}} You are GeneralAgent, a agent on the {{os_version}} computer to help the user solve the problem. Remember, you can control the computer and access the internet. Solve the task step by step if you need to. If a plan is not provided, explain your plan first simply and clearly. You can use the following skills to help you solve the problem directly without explain and ask for permission: """

1

RoleInterpreter(system_prompt='xxxx')

1

def get_weather(city:str): """ get weather from city """ return 'weather is good, sunny.'

1

import asyncio from GeneralAgent.tools import Tools from GeneralAgent.agent import Agent from GeneralAgent.interpreter import PythonInterpreter from tool_get_weather import get_weather import_code = """ import os, sys, math from tool_get_weather import get_weather """ async def main(): workspace = './' tools = Tools([get_weather]) python_interpreter = PythonInterpreter(tools=tools, import_code=import_code) agent = Agent(workspace, input_interpreters=[], output_interpreters=[python_interpreter]) while True: input_content = input('>>>') await agent.run(input_content) if __name__ == '__main__': asyncio.run(main()) [lichen@examples]$ python add_tools.py >>>what's the weather of chengdu? To get the weather of Chengdu, we can use the `get_weather` function provided in the prompt. Here's the code to get the weather of Chengdu: \`\`\`python weather = get_weather('Chengdu') print(weather) \`\`\` weather is good, sunny. Glad to hear that the weather in Chengdu is good and sunny! Is there anything else I can help you with? >>>Is there anything else I can help you with? >>>

1

agent = Agent.default(workspace='./test') await agent.run('Hi, My Name is Chen Li'). agent = None agent = Agent.default(workspace('./test')) await agent.run('What is my Name?') # expect to output Chen Li

1

# 配置OpenAI的API Key export OPENAI_API_KEY='xx' # OpenAI Request URL export OPENAI_API_BASE='https://api.openai.com/v1' # MLL Model, defualt gpt-3.5-turbo export OPENAI_API_MODEL='gpt-3.5-turbo' # model temperature, default 0.5 TEMPERATURE=0.5 # cache llm inference and embedding, useful when develop and debug export LLM_CACHE='no' # otherwise yes export LLM_CACHE_PATH='./llm_cache.json' # google search tool at https://google.serper.dev export SERPER_API_KEY='xxx' # 是否自动运行python、shell、applescript等代码 # 默认否: n export AUTO_RUN='y' # y or n