95 lines
4.8 KiB
Python
95 lines
4.8 KiB
Python
# 本源代码中, ⭐ = 关键步骤
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"""
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测试：
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- show me the solution of $x^2=cos(x)$, solve this problem with figure, and plot and save image to t.jpg
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Testing:
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- Crop the image, keeping the bottom half.
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- Swap the blue channel and red channel of the image.
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- Convert the image to grayscale.
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- Convert the CSV file to an Excel spreadsheet.
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"""
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from toolbox import CatchException, update_ui, gen_time_str, trimmed_format_exc, ProxyNetworkActivate
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from toolbox import get_conf, select_api_key, update_ui_lastest_msg, Singleton
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from crazy_functions.crazy_utils import request_gpt_model_in_new_thread_with_ui_alive, get_plugin_arg
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from crazy_functions.crazy_utils import input_clipping, try_install_deps
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from crazy_functions.agent_fns.persistent import GradioMultiuserManagerForPersistentClasses
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from crazy_functions.agent_fns.auto_agent import AutoGenMath
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import time
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@CatchException
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def 多智能体终端(txt, llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port):
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"""
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txt 输入栏用户输入的文本，例如需要翻译的一段话，再例如一个包含了待处理文件的路径
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llm_kwargs gpt模型参数，如温度和top_p等，一般原样传递下去就行
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plugin_kwargs 插件模型的参数
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chatbot 聊天显示框的句柄，用于显示给用户
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history 聊天历史，前情提要
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system_prompt 给gpt的静默提醒
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web_port 当前软件运行的端口号
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"""
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# 检查当前的模型是否符合要求
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supported_llms = ['gpt-3.5-turbo-16k', 'gpt-4', 'gpt-4-32k',
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'api2d-gpt-3.5-turbo-16k', 'api2d-gpt-4']
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llm_kwargs['api_key'] = select_api_key(llm_kwargs['api_key'], llm_kwargs['llm_model'])
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if llm_kwargs['llm_model'] not in supported_llms:
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chatbot.append([f"处理任务: {txt}", f"当前插件只支持{str(supported_llms)}, 当前模型{llm_kwargs['llm_model']}."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# 检查当前的模型是否符合要求
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API_URL_REDIRECT = get_conf('API_URL_REDIRECT')
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if len(API_URL_REDIRECT) > 0:
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chatbot.append([f"处理任务: {txt}", f"暂不支持中转."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# 尝试导入依赖，如果缺少依赖，则给出安装建议
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try:
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import autogen, docker
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except:
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chatbot.append([ f"处理任务: {txt}",
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f"导入软件依赖失败。使用该模块需要额外依赖，安装方法```pip install --upgrade pyautogen docker```。"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# 尝试导入依赖，如果缺少依赖，则给出安装建议
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try:
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import autogen
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import glob, os, time, subprocess
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subprocess.Popen(['docker', '--version'])
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except:
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chatbot.append([f"处理任务: {txt}", f"缺少docker运行环境！"])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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return
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# 解锁插件
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chatbot.get_cookies()['lock_plugin'] = None
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persistent_class_multi_user_manager = GradioMultiuserManagerForPersistentClasses()
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user_uuid = chatbot.get_cookies().get('uuid')
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persistent_key = f"{user_uuid}->多智能体终端"
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if persistent_class_multi_user_manager.already_alive(persistent_key):
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# 当已经存在一个正在运行的多智能体终端时，直接将用户输入传递给它，而不是再次启动一个新的多智能体终端
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print('[debug] feed new user input')
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executor = persistent_class_multi_user_manager.get(persistent_key)
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exit_reason = yield from executor.main_process_ui_control(txt, create_or_resume="resume")
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else:
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# 运行多智能体终端 (首次)
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print('[debug] create new executor instance')
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history = []
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chatbot.append(["正在启动: 多智能体终端", "插件动态生成, 执行开始, 作者 Microsoft & Binary-Husky."])
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yield from update_ui(chatbot=chatbot, history=history) # 刷新界面
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executor = AutoGenMath(llm_kwargs, plugin_kwargs, chatbot, history, system_prompt, web_port)
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persistent_class_multi_user_manager.set(persistent_key, executor)
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exit_reason = yield from executor.main_process_ui_control(txt, create_or_resume="create")
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if exit_reason == "wait_feedback":
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# 当用户点击了“等待反馈”按钮时，将executor存储到cookie中，等待用户的再次调用
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executor.chatbot.get_cookies()['lock_plugin'] = 'crazy_functions.多智能体->多智能体终端'
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else:
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executor.chatbot.get_cookies()['lock_plugin'] = None
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yield from update_ui(chatbot=executor.chatbot, history=executor.history) # 更新状态
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